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  • A Hot Topic - Profitability and Cost Management

    - by john.orourke(at)oracle.com
    Maybe it's due to the recent recession, or current economic recovery but a hot topic and area of focus for many organizations these days is profitability and cost management.  For most organizations, aggressive cost-cutting and cost management were critical to remaining profitable while top line revenue was flat or shrinking.  However, now we are seeing many organizations taking a more "surgical" approach to profitability and cost management, by accurately allocating revenue and costs to individual product lines, services, customer segments, locations, channels and other lines of business to understand which ones are truly profitable and which ones are not.  Based on these insights, managers can make more informed decisions about which products or services to invest in or retire, how to price their products or services for different customer segments, and where to focus their marketing and customer service resources. The most common industries where this product, service and customer-focused costing and profitability analysis is being adopted include financial services, consumer packaged goods, retail and manufacturing.  However we are seeing adoption of profitability and cost management applications in other industries and use cases.  Here are a few examples: Telecommunications Industry:  Network Costing and Management to identify the most cost effective and/or profitable network areas, to optimize existing resources, infrastructure and network capacity.  Regulatory Cost Accounting to perform more accurate allocations of revenue and costs across services and customer segments, improve ability to set billing rates for future periods, for various products and customer segments and more easily develop analysis needed for rate case proposals. Healthcare Insurance:  Visually, justifiable Medical Loss Ratio results, better knowledge of the cost to service healthcare plans and members, accurate understanding of member segment and plan profitability, improved marketing programs through better member segmentation. Public Sector:  Statutory / Regulatory Compliance:  A variety of statutory and regulatory documents state explicitly or implicitly that the use of government resources must be properly tracked and tied to performance goals.  Managerial costing methods implemented through Cost Management applications provide unparalleled visibility into costs and shared services usage throughout a Public Sector agency. Funding Support:  Regulations require public sector funding requests to be evaluated based upon the ability to achieve performance goals against the associated cost.   Improved visibility and understanding of costs of different programs/services means that organizations can demonstrably monitor performance and the associated resource costs improve the chances of having their funding requests granted. Profitability and Cost Management is one of the fastest-growing solution areas in Oracle's Enterprise Performance Management product line and we are seeing a growing number of customer successes across geographies and industries.  Listed below are just a few examples.  Here's a link to the replay from a recent webcast on this topic which featured Schroders Plc, a UK-based Financial Services company: http://www.oracle.com/go/?&Src=7011668&Act=168&pcode=WWMK10037859MPP043 Here's a link to a case study on Shenhua Guohua Power in China: http://www.oracle.com/us/corporate/customers/shenhua-snapshot-159574.pdf Here's a link to information on Oracle's web site about our profitability and cost management solutions: http://www.oracle.com/us/solutions/ent-performance-bi/performance-management/profitability-cost-mgmt/index.html

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  • SQL Server Master class winner

    - by Testas
     The winner of the SQL Server MasterClass competition courtesy of the UK SQL Server User Group and SQL Server Magazine!    Steve Hindmarsh     There is still time to register for the seminar yourself at:  www.regonline.co.uk/kimtrippsql     More information about the seminar     Where: Radisson Edwardian Heathrow Hotel, London  When: Thursday 17th June 2010  This one-day MasterClass will focus on many of the top issues companies face when implementing and maintaining a SQL Server-based solution. In the case where a company has no dedicated DBA, IT managers sometimes struggle to keep the data tier performing well and the data available. This can be especially troublesome when the development team is unfamiliar with the affect application design choices have on database performance. The Microsoft SQL Server MasterClass 2010 is presented by Paul S. Randal and Kimberly L. Tripp, two of the most experienced and respected people in the SQL Server world. Together they have over 30 years combined experience working with SQL Server in the field, and on the SQL Server product team itself. This is a unique opportunity to hear them present at a UK event which will: Debunk many of the ingrained misconceptions around SQL Server's behaviour    Show you disaster recovery techniques critical to preserving your company's life-blood - the data    Explain how a common application design pattern can wreak havoc in the database Walk through the top-10 points to follow around operations and maintenance for a well-performing and available data tier! Please Note: Agenda may be subject to change  Sessions Abstracts  KEYNOTE: Bridging the Gap Between Development and Production    Applications are commonly developed with little regard for how design choices will affect performance in production. This is often because developers don't realize the implications of their design on how SQL Server will be able to handle a high workload (e.g. blocking, fragmentation) and/or because there's no full-time trained DBA that can recognize production problems and help educate developers. The keynote sets the stage for the rest of the day. Discussing some of the issues that can arise, explaining how some can be avoided and highlighting some of the features in SQL 2008 that can help developers and DBAs make better use of SQL Server, and troubleshoot when things go wrong.   SESSION ONE: SQL Server Mythbusters  It's amazing how many myths and misconceptions have sprung up and persisted over the years about SQL Server - after many years helping people out on forums, newsgroups, and customer engagements, Paul and Kimberly have heard it all. Are there really non-logged operations? Can interrupting shrinks or rebuilds cause corruption? Can you override the server's MAXDOP setting? Will the server always do a table-scan to get a row count? Many myths lead to poor design choices and inappropriate maintenance practices so these are just a few of many, many myths that Paul and Kimberly will debunk in this fast-paced session on how SQL Server operates and should be managed and maintained.   SESSION TWO: Database Recovery Techniques Demo-Fest  Even if a company has a disaster recovery strategy in place, they need to practice to make sure that the plan will work when a disaster does strike. In this fast-paced demo session Paul and Kimberly will repeatedly do nasty things to databases and then show how they are recovered - demonstrating many techniques that can be used in production for disaster recovery. Not for the faint-hearted!   SESSION THREE: GUIDs: Use, Abuse, and How To Move Forward   Since the addition of the GUID (Microsoft’s implementation of the UUID), my life as a consultant and "tuner" has been busy. I’ve seen databases designed with GUID keys run fairly well with small workloads but completely fall over and fail because they just cannot scale. And, I know why GUIDs are chosen - it simplifies the handling of parent/child rows in your batches so you can reduce round-trips or avoid dealing with identity values. And, yes, sometimes it's even for distributed databases and/or security that GUIDs are chosen. I'm not entirely against ever using a GUID but overusing and abusing GUIDs just has to be stopped! Please, please, please let me give you better solutions and explanations on how to deal with your parent/child rows, round-trips and clustering keys!   SESSION 4: Essential Database Maintenance  In this session, Paul and Kimberly will run you through their top-ten database maintenance recommendations, with a lot of tips and tricks along the way. These are distilled from almost 30 years combined experience working with SQL Server customers and are geared towards making your databases more performant, more available, and more easily managed (to save you time!). Everything in this session will be practical and applicable to a wide variety of databases. Topics covered include: backups, shrinks, fragmentation, statistics, and much more! Focus will be on 2005 but we'll explain some of the key differences for 2000 and 2008 as well. Speaker Biographies     Kimberley L. Tripp Paul and Kimberly are a husband-and-wife team who own and run SQLskills.com, a world-renowned SQL Server consulting and training company. They are both SQL Server MVPs and Microsoft Regional Directors, with over 30 years of combined experience on SQL Server. Paul worked on the SQL Server team for nine years in development and management roles, writing many of the DBCC commands, and ultimately with responsibility for core Storage Engine for SQL Server 2008. Paul writes extensively on his blog (SQLskills.com/blogs/Paul) and for TechNet Magazine, for which he is also a Contributing Editor. Kimberly worked on the SQL Server team in the early 1990s as a tester and writer before leaving to found SQLskills and embrace her passion for teaching and consulting. Kimberly has been a staple at worldwide conferences since she first presented at TechEd in 1996, and she blogs at SQLskills.com/blogs/Kimberly. They have written Microsoft whitepapers and books for SQL Server 2000, 2005 and 2008, and are regular, top-rated presenters worldwide on database maintenance, high availability, disaster recovery, performance tuning, and SQL Server internals. Together they teach the SQL MCM certification and throughout Microsoft.In their spare time, they like to find frogfish in remote corners of the world.   Speaker Testimonials  "To call them good trainers is an epic understatement. They know how to deliver technical material in ways that illustrate it well. I had to stop Paul at one point and ask him how long it took to build a particular slide because the animations were so good at conveying a hard-to-describe process." "These are not beginner presenters, and they put an extreme amount of preparation and attention to detail into everything that they do. Completely, utterly professional." "When it comes to the instructors themselves, Kimberly and Paul simply have no equal. Not only are they both ultimate authorities, but they have endless enthusiasm about the material, and spot on delivery. If either ever got tired they never showed it, even after going all day and all week. We witnessed countless demos over the course of the week, some extremely involved, multi-step processes, and I can’t recall one that didn’t go the way it was supposed to." "You might think that with this extreme level of skill comes extreme levels of egotism and lack of patience. Nothing could be further from the truth. ... They simply know how to teach, and are approachable, humble, and patient." "The experience Paul and Kimberly have had with real live customers yields a lot more information and things to watch out for than you'd ever get from documentation alone." “Kimberly, I just wanted to send you an email to let you know how awesome you are! I have applied some of your indexing strategies to our website’s homegrown CMS and we are experiencing a significant performance increase. WOW....amazing tips delivered in an exciting way!  Thanks again” 

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  • Formatting data from management database

    - by bVector
    I've got some data that goes like this: Config_Name Question Answer Cisco WAN Sensitivity: High Cisco WAN Authorized Users: Brent, Charles Cisco WAN Last Audited: n/a Cisco WAN Next Audit: 3/30/2012 Cisco WAN Audit Signature: Cisco WAN Username: MYCOMPANY Cisco WAN Password: Cisco WAN Encrypted-A ENCRYPTED DATA Cisco WAN Encrypted-B Cisco WAN Encrypted-C vCenter server Sensitivity: High vCenter server Authorized Users: Brent, Charles vCenter server Last Audited: vCenter server Next Audit: 3/30/2012 vCenter server Audit Signature: ENCRYPTED DATA vCenter server Username: administrator vCenter server Password: vCenter server Encrypted-A ENCRYPTED DATA vCenter server Encrypted-B vCenter server Encrypted-C AKSC-NE01 IPMI Sensitivity: High AKSC-NE01 IPMI Authorized Users: Brent, Charles AKSC-NE01 IPMI Last Audited: AKSC-NE01 IPMI Next Audit: 3/30/2012 AKSC-NE01 IPMI Audit Signature: ENCRYPTED DATA AKSC-NE01 IPMI Username: MYCOMPANY AKSC-NE01 IPMI Password: AKSC-NE01 IPMI Encrypted-A ENCRYPTED DATA AKSC-NE01 IPMI Encrypted-B AKSC-NE01 IPMI Encrypted-C and I need it to be in this format: Config_Name Sensitivity: Authorized Users: Last Audited: Next Audit: Audit Signature: Username: Password: Encrypted-A Encrypted-B Encrypted-C AKSC-NE01 IPMI High Brent, Charles 3/30/2012 ENCRYPTED DATA MYCOMPANY ENCRYPTED DATA Cisco ASA5505 WAN High Brent, Charles n/a 3/30/2012 ENCRYPTED DATA MYCOMPANY ENCRYPTED DATA vCenter server High Brent, Charles 3/30/2012 ENCRYPTED DATA administrator ENCRYPTED DATA the tabs get messed up on here but hopefully you get my drift. does anyone know an easy way to do this? I haven't found one with excel just yet.

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  • Major Analyst Report Chooses Oracle As An ECM Leader

    - by brian.dirking(at)oracle.com
    Oracle announced that Gartner, Inc. has named Oracle as a Leader in its latest "Magic Quadrant for Enterprise Content Management" in a press release issued this morning. Gartner's Magic Quadrant reports position vendors within a particular quadrant based on their completeness of vision and ability to execute. According to Gartner, "Leaders have the highest combined scores for Ability to Execute and Completeness of Vision. They are doing well and are prepared for the future with a clearly articulated vision. In the context of ECM, they have strong channel partners, presence in multiple regions, consistent financial performance, broad platform support and good customer support. In addition, they dominate in one or more technology or vertical market. Leaders deliver a suite that addresses market demand for direct delivery of the majority of core components, though these are not necessarily owned by them, tightly integrated, unique or best-of-breed in each area. We place more emphasis this year on demonstrated enterprise deployments; integration with other business applications and content repositories; incorporation of Web 2.0 and XML capabilities; and vertical-process and horizontal-solution focus. Leaders should drive market transformation." "To extend content governance and best practices across the enterprise, organizations need an enterprise content management solution that delivers a broad set of functionality and is tightly integrated with business processes," said Andy MacMillan, vice president, Product Management, Oracle. "We believe that Oracle's position as a Leader in this report is recognition of the industry-leading performance, integration and scalability delivered in Oracle Enterprise Content Management Suite 11g." With Oracle Enterprise Content Management Suite 11g, Oracle offers a comprehensive, integrated and high-performance content management solution that helps organizations increase efficiency, reduce costs and improve content security. In the report, Oracle is grouped among the top three vendors for execution, and is the furthest to the right, placing Oracle as the most visionary vendor. This vision stems from Oracle's integration of content management right into key business processes, delivering content in context as people need it. Using a PeopleSoft Accounts Payable user as an example, as an employee processes an invoice, Oracle ECM Suite brings that invoice up on the screen so the processor can verify the content right in the process, improving speed and accuracy. Oracle integrates content into business processes such as Human Resources, Travel and Expense, and others, in the major enterprise applications such as PeopleSoft, JD Edwards, Siebel, and E-Business Suite. As part of Oracle's Enterprise Application Documents strategy, you can see an example of these integrations in this webinar: Managing Customer Documents and Marketing Assets in Siebel. You can also get a white paper of the ROI Embry Riddle achieved using Oracle Content Management integrated with enterprise applications. Embry Riddle moved from a point solution for content management on accounts payable to an infrastructure investment - they are now using Oracle Content Management for accounts payable with Oracle E-Business Suite, and for student on-boarding with PeopleSoft e-Campus. They continue to expand their use of Oracle Content Management to address further use cases from a core infrastructure. Oracle also shows its vision in the ability to deliver content optimized for online channels. Marketers can use Oracle ECM Suite to deliver digital assets and offers as part of an integrated campaign that understands website visitors and ensures that they are given the most pertinent information and offers. Oracle also provides full lifecycle management through its built-in records management. Companies are able to manage the lifecycle of content (both records and non-records) through built-in retention management. And with the integration of Oracle ECM Suite and Sun Storage Archive Manager, content can be routed to the appropriate storage media based upon content type, usage data or other business rules. This ensures that the most accessed content is instantly available, and archived content is stored on a more appropriate medium like tape. You can learn more in this webinar - Oracle Content Management and Sun Tiered Storage. If you are interested in reading more about why Oracle was chosen as a Leader, view the Gartner Magic Quadrant for Enterprise Content Management.

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  • SQL SERVER – Guest Post – Architecting Data Warehouse – Niraj Bhatt

    - by pinaldave
    Niraj Bhatt works as an Enterprise Architect for a Fortune 500 company and has an innate passion for building / studying software systems. He is a top rated speaker at various technical forums including Tech·Ed, MCT Summit, Developer Summit, and Virtual Tech Days, among others. Having run a successful startup for four years Niraj enjoys working on – IT innovations that can impact an enterprise bottom line, streamlining IT budgets through IT consolidation, architecture and integration of systems, performance tuning, and review of enterprise applications. He has received Microsoft MVP award for ASP.NET, Connected Systems and most recently on Windows Azure. When he is away from his laptop, you will find him taking deep dives in automobiles, pottery, rafting, photography, cooking and financial statements though not necessarily in that order. He is also a manager/speaker at BDOTNET, Asia’s largest .NET user group. Here is the guest post by Niraj Bhatt. As data in your applications grows it’s the database that usually becomes a bottleneck. It’s hard to scale a relational DB and the preferred approach for large scale applications is to create separate databases for writes and reads. These databases are referred as transactional database and reporting database. Though there are tools / techniques which can allow you to create snapshot of your transactional database for reporting purpose, sometimes they don’t quite fit the reporting requirements of an enterprise. These requirements typically are data analytics, effective schema (for an Information worker to self-service herself), historical data, better performance (flat data, no joins) etc. This is where a need for data warehouse or an OLAP system arises. A Key point to remember is a data warehouse is mostly a relational database. It’s built on top of same concepts like Tables, Rows, Columns, Primary keys, Foreign Keys, etc. Before we talk about how data warehouses are typically structured let’s understand key components that can create a data flow between OLTP systems and OLAP systems. There are 3 major areas to it: a) OLTP system should be capable of tracking its changes as all these changes should go back to data warehouse for historical recording. For e.g. if an OLTP transaction moves a customer from silver to gold category, OLTP system needs to ensure that this change is tracked and send to data warehouse for reporting purpose. A report in context could be how many customers divided by geographies moved from sliver to gold category. In data warehouse terminology this process is called Change Data Capture. There are quite a few systems that leverage database triggers to move these changes to corresponding tracking tables. There are also out of box features provided by some databases e.g. SQL Server 2008 offers Change Data Capture and Change Tracking for addressing such requirements. b) After we make the OLTP system capable of tracking its changes we need to provision a batch process that can run periodically and takes these changes from OLTP system and dump them into data warehouse. There are many tools out there that can help you fill this gap – SQL Server Integration Services happens to be one of them. c) So we have an OLTP system that knows how to track its changes, we have jobs that run periodically to move these changes to warehouse. The question though remains is how warehouse will record these changes? This structural change in data warehouse arena is often covered under something called Slowly Changing Dimension (SCD). While we will talk about dimensions in a while, SCD can be applied to pure relational tables too. SCD enables a database structure to capture historical data. This would create multiple records for a given entity in relational database and data warehouses prefer having their own primary key, often known as surrogate key. As I mentioned a data warehouse is just a relational database but industry often attributes a specific schema style to data warehouses. These styles are Star Schema or Snowflake Schema. The motivation behind these styles is to create a flat database structure (as opposed to normalized one), which is easy to understand / use, easy to query and easy to slice / dice. Star schema is a database structure made up of dimensions and facts. Facts are generally the numbers (sales, quantity, etc.) that you want to slice and dice. Fact tables have these numbers and have references (foreign keys) to set of tables that provide context around those facts. E.g. if you have recorded 10,000 USD as sales that number would go in a sales fact table and could have foreign keys attached to it that refers to the sales agent responsible for sale and to time table which contains the dates between which that sale was made. These agent and time tables are called dimensions which provide context to the numbers stored in fact tables. This schema structure of fact being at center surrounded by dimensions is called Star schema. A similar structure with difference of dimension tables being normalized is called a Snowflake schema. This relational structure of facts and dimensions serves as an input for another analysis structure called Cube. Though physically Cube is a special structure supported by commercial databases like SQL Server Analysis Services, logically it’s a multidimensional structure where dimensions define the sides of cube and facts define the content. Facts are often called as Measures inside a cube. Dimensions often tend to form a hierarchy. E.g. Product may be broken into categories and categories in turn to individual items. Category and Items are often referred as Levels and their constituents as Members with their overall structure called as Hierarchy. Measures are rolled up as per dimensional hierarchy. These rolled up measures are called Aggregates. Now this may seem like an overwhelming vocabulary to deal with but don’t worry it will sink in as you start working with Cubes and others. Let’s see few other terms that we would run into while talking about data warehouses. ODS or an Operational Data Store is a frequently misused term. There would be few users in your organization that want to report on most current data and can’t afford to miss a single transaction for their report. Then there is another set of users that typically don’t care how current the data is. Mostly senior level executives who are interesting in trending, mining, forecasting, strategizing, etc. don’t care for that one specific transaction. This is where an ODS can come in handy. ODS can use the same star schema and the OLAP cubes we saw earlier. The only difference is that the data inside an ODS would be short lived, i.e. for few months and ODS would sync with OLTP system every few minutes. Data warehouse can periodically sync with ODS either daily or weekly depending on business drivers. Data marts are another frequently talked about topic in data warehousing. They are subject-specific data warehouse. Data warehouses that try to span over an enterprise are normally too big to scope, build, manage, track, etc. Hence they are often scaled down to something called Data mart that supports a specific segment of business like sales, marketing, or support. Data marts too, are often designed using star schema model discussed earlier. Industry is divided when it comes to use of data marts. Some experts prefer having data marts along with a central data warehouse. Data warehouse here acts as information staging and distribution hub with spokes being data marts connected via data feeds serving summarized data. Others eliminate the need for a centralized data warehouse citing that most users want to report on detailed data. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Best Practices, Business Intelligence, Data Warehousing, Database, Pinal Dave, PostADay, Readers Contribution, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Prevent master to fall back to master after failure

    - by Chrille
    I'm using keepalived to setup a virtual ip that points to a master server. When a failover happens it should point the virtual ip to the backup, and the IP should stay there until I manually enable (fix) the master. The reason this is important is that I'm running mysql replication on the servers and writes should only be on the master. When I failover I promote the slave to master. The master server: global_defs { ! this is who emails will go to on alerts notification_email { [email protected] ! add a few more email addresses here if you would like } notification_email_from [email protected] ! I use the local machine to relay mail smtp_server 127.0.0.1 smtp_connect_timeout 30 ! each load balancer should have a different ID ! this will be used in SMTP alerts, so you should make ! each router easily identifiable lvs_id APP1 } vrrp_instance APP1 { interface eth0 state EQUAL virtual_router_id 61 priority 999 nopreempt virtual_ipaddress { 217.x.x.129 } smtp_alert } Backup server: global_defs { ! this is who emails will go to on alerts notification_email { [email protected] ! add a few more email addresses here if you would like } notification_email_from [email protected] ! I use the local machine to relay mail smtp_server 127.0.0.1 smtp_connect_timeout 30 ! each load balancer should have a different ID ! this will be used in SMTP alerts, so you should make ! each router easily identifiable lvs_id APP2 } vrrp_instance APP2 { interface eth0 state EQUAL virtual_router_id 61 priority 100 virtual_ipaddress { 217.xx.xx.129 } notify_master "/etc/keepalived/notify.sh del app2" notify_backup "/etc/keepalived/notify.sh add app2" notify_fault "/etc/keepalived/notify.sh add app2” smtp_alert }

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  • master-slave-slave replication: master will become bottleneck for writes

    - by JMW
    hi, the mysql database has arround 2TB of data. i have a master-slave-slave replication running. the application that uses the database does read (SELECT) queries just on one of the 2 slaves and write (DELETE/INSERT/UPDATE) queries on the master. the application does way more reads, than writes. if we have a problem with the read (SELECT) queries, we can just add another slave database and tell the application, that there is another salve. so it scales well... Currently, the master is running arround 40% disk io due to the writes. So i'm thinking about how to scale the the database in the future. Because one day the master will be overloaded. What could be a solution there? maybe mysql cluster? if so, are there any pitfalls or limitations in switching the database to ndb? thanks a lot in advance... :)

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  • Absence Management White Papers to Assist with your Implementations

    - by Carolyn Cozart
    Absence Management Setup – Additional Resources PeopleSoft is committed to helping our customers sharing our knowledge expertise in our applications. We have prepared a collection of documents (White Papers) containing examples, tips, and techniques to help you when making important decisions during your Absence Management implementation.   These documents can all be found on My Oracle Support. Absence Management Entitlement and Take Setup This document (Document ID 1493866.1) provides an overview of how to set up the main components of Absence Management, such as Absence Entitlement and Take elements, as well as other supporting elements relevant to your Absence Management implementation. Absence Management System Elements This document (Document ID 1493879.1) provides an overview of the system elements related to Absence Management. System elements are building blocks used during the design and construction of your Absence Rules. Knowing how they work and when to use them should help you expedite the implementation of your Absence Policy rules in your company Absence Management Self Service Setup This document (Document ID 1493867.1) provides an overview and guidance on some of the important areas when setting up Absence Self Service. Throughout this document we are providing examples of different configurations supported in Self Service. 

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  • Today @ OOW: Identity Management for the SoMoClo world

    - by B Shashikumar
    Today at OpenWord, we have a very interesting lineup of Identity Management sessions that discuss how to extend identity management securrley to cloud, mobile and social ecosystems. Here are 3 of the can’t miss identity management sessions today: Identity Management and the Cloud: Security is regularly identified as the #1 barrier to cloud service adoption. Oracle Identity Management is designed to help customers extend and connect core identity services to SaaS applications and systems. This session explores how organizations are using Oracle Identity Management with cloud services and how some customers are offering identity management as a cloud service. Real-time External Authorization for Applications, Middleware and Databases: Externalization of authorization is key to manageability and audit. This session covers enterprise wide authorization solution deployment best practices and real-world examples of using Oracle Entitlements Server—the one-stop standards-compliant authorization solution—for middleware, applications, and data. Delivering Secure WiFi on the Tube as an Olympics Legacy from London 2012: In this session, Virgin Media, the U.K.’s first combined provider of broadband, TV, mobile, and home phone services, shares how it is providing free secure Wi-Fi services to the London Underground, using Oracle Virtual Directory and Oracle Entitlements Server, leveraging back-end legacy systems that were never designed to be externalized. As an Olympics 2012 legacy, the Oracle architecture will form a platform to be consumed by other Virgin Media services such as video on demand. Here is the complete lineup of Identity Management sessions today at OOW.

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  • Data Mining Resources

    - by Dejan Sarka
    There are many different types of analyses, each one with its own pros and cons. Relational reports have a predefined structure, and end users cannot change it. They are simple to use for end users. Reports can use real-time data and snapshots of data to show the state of a report at specific points in time. One of the drawbacks is that report authoring is limited to IT pros and advanced users. Any kind of dynamic restructuring is very limited. If real-time data is used for a report, the report has a negative impact on the performance of the source system. Processing of the reports might be slow because the data comes from relational database management systems, which are not optimized for reporting only. If you create a semantic model of your data, your end users can create ad-hoc report structures. However, the development is more complex because a developer is needed to create these semantic models. For OLAP, you typically use specialized database management systems. You get lightning speed of analyses. End users can use rich and thin clients to interactively change the structure of the report. Typically, they do it graphically. However, the development of an OLAP system is many times quite complex. It involves the preparation and maintenance of an enterprise data warehouse and OLAP cubes. In order to exploit the possibility of real-time restructuring of reports, the users must be both active and educated. The data is usually stale, as it is loaded into data warehouses and OLAP cubes with a scheduled process. With data mining, a structure is not selected in advance; it searches for the structure. As a result, data mining can give you the most valuable results because you can discover patterns you did not expect. A data mining model structure is limited only by the attributes that you use to train the model. One of the drawbacks is that a lot of knowledge is needed for a successful data mining project. End users have to understand the results. Subject matter experts and IT professionals need to understand business problem thoroughly. The development might be sometimes even more complex than the development of OLAP cubes. Each type of analysis has its own place in an enterprise system. SQL Server has tools for all kinds of analyses. However, data mining is the most advanced way of analyzing the data; this is the “I” in BI. In order to get the most out of it, you need to learn quite a lot. In this blog post, I am gathering together resources for learning, including forthcoming events. Books Multiple authors: SQL Server MVP Deep Dives – I wrote an introductory data mining chapter there. Erik Veerman, Teo Lachev and Dejan Sarka: MCTS Self-Paced Training Kit (Exam 70-448): Microsoft SQL Server 2008 - Business Intelligence Development and Maintenance – you can find a good overview of a complete BI solution, including data mining, in this book. Jamie MacLennan, ZhaoHui Tang, and Bogdan Crivat: Data Mining with Microsoft SQL Server 2008 – can’t miss this book if you want to mine your data with SQL Server tools. Michael Berry, Gordon Linoff: Mastering Data Mining: The Art and Science of Customer Relationship Managementdata mining from both, business and technical perspective. Dorian Pyle: Data Preparation for Data Mining – an in-depth book about data preparation. Thomas and Ronald Wonnacott: Introductory Statistics – if you thought that you could get away without statistics, then you are not serious about data mining. Jiawei Han and Micheline Kamber: Data Mining Concepts and Techniques – in-depth explanation of the most popular data mining algorithms. Michael Berry and Gordon Linoff: Data Mining Techniques – another book that explains data mining algorithms, more fro a business perspective. Paolo Guidici: Applied Data Mining – very mathematical book, only if you enjoy statistics and mathematics in general. Forthcoming presentations I am presenting two data mining related sessions during the PASS Summit in Charlotte, NC: Wednesday, October 16th, 2013 - Fraud Detection: Notes from the Field – I am showing how to use data mining for a specific business problem. The presentation is based on real-life projects. Friday, October 18th: Excel 2013 Advanced Analytics – I am focusing on Excel Data Mining Add-ins, and how to use them together with Power Pivot and other add-ins. This is the most you can get out of Excel. Sinergija 2013, Belgrade, Serbia Tuesday, October 22nd: Excel 2013 Analytics to the Max – another presentation focusing on the most advanced analytics you can get in Excel. SQL Rally Amsterdam, Netherlands Thursday, November 7th: Advanced Analytics in Excel 2013 – and again I am presenting about data mining in Excel. Why three different titles for the same presentation? I don’t know, I guess I forgot the name I proposed every time right after I sent the proposal. Courses Data Mining with SQL Server 2012 – I wrote a 3-day course for SolidQ. If you are interested in this course, which I could also deliver in a shorter seminar way, you can contact your closes SolidQ subsidiary, or, of course, me directly on addresses [email protected] or [email protected]. This course could also complement the existing courseware portfolio of training providers, which are welcome to contact me as well. OK, now you know: no more excuses, start learning data mining, get the most out of your data

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  • Looking for Cutting-Edge Data Integration: 2010 Innovation Awards

    - by dain.hansen
    This year's Oracle Fusion Middleware Innovation Awards will honor customers and partners who are creatively using to various products across Oracle Fusion Middleware. Brand new to this year's awards is a category for Data Integration. Think you have something unique and innovative with one of our Oracle Data Integration products? We'd love to hear from you! Please submit today The deadline for the nomination is 5 p.m. PT Friday, August 6th 2010, and winning organizations will be notified by late August 2010. What you win! FREE pass to Oracle OpenWorld 2010 in San Francisco for select winners in each category. Honored by Oracle executives at awards ceremony held during Oracle OpenWorld 2010 in San Francisco. Oracle Middleware Innovation Award Winner Plaque 1-3 meetings with Oracle Executives during Oracle OpenWorld 2010 Feature article placement in Oracle Magazine and placement in Oracle Press Release Customer snapshot and video testimonial opportunity, to be hosted on oracle.com Podcast interview opportunity with Senior Oracle Executive

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  • Data Integration 12c Raising the Big Data Roof at Oracle OpenWorld

    - by Tanu Sood
    Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-family:"Times New Roman","serif"; mso-fareast-font-family:"MS Mincho";} Author: Dain Hansen, Director, Oracle It was an exciting OpenWorld 2013 for us in the Data Integration track. Our theme this year was all about ‘being future ready’ - previewing one of our biggest releases this year: Oracle Data Integration 12c. Just this week we followed up with this preview by announcing the general availability of 12c release for Oracle’s key data integration products: Oracle Data Integrator 12c and Oracle GoldenGate 12c. The new release delivers extreme performance, increase IT productivity, and simplify deployment, while helping IT organizations to keep pace with new data-oriented technology trends including cloud computing, big data analytics, real-time business intelligence. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-family:"Times New Roman","serif"; mso-fareast-font-family:"MS Mincho";} Mark Hurd's keynote on day one set the tone for the Data Integration sessions. Mark focused on big data analytics and the changing consumer expectations. Especially real-time insight is a key theme for Oracle overall and data integration products. In Mark Hurd's keynote we heard from key customers, such as Airbus and Thomson Reuters, how real-time analysis of operational data including machine data creates value, in some cases even saves lives. Thomas Kurian gave a deeper look into Oracle's big data and fast data solutions. In the initial lead Data Integration track session - Brad Adelberg, VP of Development, presented Oracle’s Data Integration 12c product strategy based on key trends from the initial OpenWorld keynotes. Brad talked about how Oracle's data integration products address the new data integration requirements that evolved with cloud computing, big data, and changing consumer expectations and how they set the key themes in our products’ road map. Brad explained why and how fast-time to value, high-performance and future-ready solutions is the top focus areas for product development. If you were not able to attend OpenWorld or this session I recommend reading the white paper: Five New Data Integration Requirements and How to Meet them with Oracle Data Integration, which provides an in-depth look into how Oracle addresses the new trends in the DI market. Following Brad’s session, Nick Wagner provided in depth review of Oracle GoldenGate’s latest features and roadmap. Nick discussed how Oracle GoldenGate’s tight integration with Oracle Database sets the product apart from the competition. We also heard that heterogeneity of the product is still a major focus for GoldenGate’s development and there will be more news on that front when there is a major release. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-family:"Times New Roman","serif"; mso-fareast-font-family:"MS Mincho";} After GoldenGate’s product strategy session, Denis Gray from the PM team presented Oracle Data Integrator’s product strategy session, talking about the latest and greatest on ODI. Another good session was delivered by long-time GoldenGate users, Comcast.  Jason Hurd and Amit Patel of Comcast talked about the various use cases they deploy Oracle GoldenGate throughout their enterprise, from database upgrades, feeding reporting systems, to active-active database synchronization.  The Comcast team shared many good tips on how to use GoldenGate for both zero downtime upgrades and active-active replication with conflict management requirement. One of our other important goals we had this year for the Data Integration track at OpenWorld was hearing from our customers. We ended day 1 on just that, with a wonderful award ceremony for Oracle Excellence Awards for Oracle Fusion Middleware Innovation. The ceremony was held in the Yerba Buena Center for the Arts. Congratulations to Royal Bank of Scotland and Yalumba Wine Company, the winners in the Data Integration category. You can find more information on the award and the winners in our previous blog post: 2013 Oracle Excellence Awards for Fusion Middleware Innovation… Selected for their innovation use of Oracle’s Data Integration products; the winners for the Data Integration Category are Royal Bank of Scotland and The Yalumba Wine Company. Congratulations!!! Royal Bank of Scotland’s Market and International Banking division provides clients across the globe with seamless trading and competitive pricing, underpinned by a deep knowledge of risk management across the full spectrum of financial products. They handle millions of transactions daily to keep the lifeblood of their clients’ businesses flowing – whether through payment management solutions or through bespoke trade finance solutions. Royal Bank of Scotland is leveraging Oracle GoldenGate and Oracle Data Integrator along with Oracle Business Intelligence Enterprise Edition and the Oracle Database for a variety of solutions. Mainly, Oracle GoldenGate and Oracle Data Integrator are used to feed their data warehouse – providing a real-time data integration solution that feeds transactional data to their analytics system in minutes to enable improved decision making with timely, accurate data for their business users. Oracle Data Integrator’s in-database transformation capabilities and its ability to integrate with Oracle GoldenGate for real-time data capture is the foundation of this implementation. This solution makes it such that changes happening in the analytics systems are available the same day they are deployed on the operational system with 100% data quality guaranteed. Additionally, the solution has helped to reduce their operational database size from 150GB to 10GB. Impressive! Now what if I told you this solution was built in 3 months and had a less than 6 month return on investment? That’s outstanding! The Yalumba Wine Company is situated in the Barossa Valley of Australia. It is the oldest family owned winery in Australia with a unique way of aging their wines in specially crafted 100 liter barrels. Did you know that “Yalumba” is Aboriginal for “all the land around”? The Yalumba Wine Company is growing rapidly, and was in need of introducing a more modern standard to the existing manufacturing processes to meet globalization demands, overall time-to-market, and better operational efficiency objectives of product development. The Yalumba Wine Company worked with a partner, Bristlecone to develop a unique solution whereby Oracle Data Integrator is leveraged to pull data from Salesforce.com and JD Edwards, in addition to their other pre-existing source systems, for consumption into their data warehouse. They have emphasized the overall ease of developing integration workflows with Oracle Data Integrator. The solution has brought better visibility for the business users, shorter data loading and transformation performance to their data warehouse with rapid incorporation of new data sources, and a solid future-proof foundation for their organization. Moving forward, they plan on leveraging more from Oracle’s Data Integration portfolio. Terrific! In addition to these two customers on Tuesday we featured many other important Oracle Data Integrator and Oracle GoldenGate customers. On Tuesday the GoldenGate panel included: Land O’Lakes, Smuckers, and Veolia Water. Besides giving us yummy nutrition and healthy water, these companies have another aspect in common. They all use GoldenGate to boost their ERP application. Please read the recap by Irem Radzik. On Wednesday, the ODI Panel included: Barry Ralston and Ryan Weber of Infinity Insurance, Paul Stracke of Paychex Inc., and Ian Wall of Vertex Pharmaceuticals for a session filled with interesting projects, use cases and approaches to leveraging Oracle Data Integrator. Please read the recap by Sandrine Riley for more. Thanks to everyone who joined with us and we hope to stay connected! To hear more about our Data Integration12c products join us in an upcoming webcast to learn more. Follow us www.twitter.com/ORCLGoldenGate or goto our website at www.oracle.com/goto/dataintegration

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  • Five Key Strategies in Master Data Management

    - by david.butler(at)oracle.com
    Here is a very interesting Profit Magazine article on MDM: A recent customer survey reveals the deleterious effects of data fragmentation. by Trevor Naidoo, December 2010   Across industries and geographies, IT organizations have grown in complexity, whether due to mergers and acquisitions, or decentralized systems supporting functional or departmental requirements. With systems architected over time to support unique, one-off process needs, they are becoming costly to maintain, and the Internet has only further added to the complexity. Data fragmentation has become a key inhibitor in delivering flexible, user-friendly systems. The Oracle Insight team conducted a survey assessing customers' master data management (MDM) capabilities over the past two years to get a sense of where they are in terms of their capabilities. The responses, by 27 respondents from six different industries, reveal five key areas in which customers need to improve their data management in order to get better financial results. 1. Less than 15 percent of organizations surveyed understand the sources and quality of their master data, and have a roadmap to address missing data domains. Examples of the types of master data domains referred to are customer, supplier, product, financial and site. Many organizations have multiple sources of master data with varying degrees of data quality in each source -- customer data stored in the customer relationship management system is inconsistent with customer data stored in the order management system. Imagine not knowing how many places you stored your customer information, and whether a customer's address was the most up to date in each source. In fact, more than 55 percent of the respondents in the survey manage their data quality on an ad-hoc basis. It is important for organizations to document their inventory of data sources and then profile these data sources to ensure that there is a consistent definition of key data entities throughout the organization. Some questions to ask are: How do we define a customer? What is a product? How do we define a site? The goal is to strive for one common repository for master data that acts as a cross reference for all other sources and ensures consistent, high-quality master data throughout the organization. 2. Only 18 percent of respondents have an enterprise data management strategy to ensure that data is treated as an asset to the organization. Most respondents handle data at the department or functional level and do not have an enterprise view of their master data. The sales department may track all their interactions with customers as they move through the sales cycle, the service department is tracking their interactions with the same customers independently, and the finance department also has a different perspective on the same customer. The salesperson may not be aware that the customer she is trying to sell to is experiencing issues with existing products purchased, or that the customer is behind on previous invoices. The lack of a data strategy makes it difficult for business users to turn data into information via reports. Without the key building blocks in place, it is difficult to create key linkages between customer, product, site, supplier and financial data. These linkages make it possible to understand patterns. A well-defined data management strategy is aligned to the business strategy and helps create the governance needed to ensure that data stewardship is in place and data integrity is intact. 3. Almost 60 percent of respondents have no strategy to integrate data across operational applications. Many respondents have several disparate sources of data with no strategy to keep them in sync with each other. Even though there is no clear strategy to integrate the data (see #2 above), the data needs to be synced and cross-referenced to keep the business processes running. About 55 percent of respondents said they perform this integration on an ad hoc basis, and in many cases, it is done manually with the help of Microsoft Excel spreadsheets. For example, a salesperson needs a report on global sales for a specific product, but the product has different product numbers in different countries. Typically, an analyst will pull all the data into Excel, manually create a cross reference for that product, and then aggregate the sales. The exact same procedure has to be followed if the same report is needed the following month. A well-defined consolidation strategy will ensure that a central cross-reference is maintained with updates in any one application being propagated to all the other systems, so that data is synchronized and up to date. This can be done in real time or in batch mode using integration technology. 4. Approximately 50 percent of respondents spend manual efforts cleansing and normalizing data. Information stored in various systems usually follows different standards and formats, making it difficult to match the data. A customer's address can be stored in different ways using a variety of abbreviations -- for example, "av" or "ave" for avenue. Similarly, a product's attributes can be stored in a number of different ways; for example, a size attribute can be stored in inches and can also be entered as "'' ". These types of variations make it difficult to match up data from different sources. Today, most customers rely on manual, heroic efforts to match, cleanse, and de-duplicate data -- clearly not a scalable, sustainable model. To solve this challenge, organizations need the ability to standardize data for customers, products, sites, suppliers and financial accounts; however, less than 10 percent of respondents have technology in place to automatically resolve duplicates. It is no wonder, therefore, that we get communications about products we don't own, at addresses we don't reside, and using channels (like direct mail) we don't like. An all-too-common example of a potential challenge follows: Customers end up receiving duplicate communications, which not only impacts customer satisfaction, but also incurs additional mailing costs. Cleansing, normalizing, and standardizing data will help address most of these issues. 5. Only 10 percent of respondents have the ability to share data that was mastered in a master data hub. Close to 60 percent of respondents have efforts in place that profile, standardize and cleanse data manually, and the output of these efforts are stored in spreadsheets in various parts of the organization. This valuable information is not easily shared with the rest of the organization and, more importantly, this enriched information cannot be sent back to the source systems so that the data is fixed at the source. A key benefit of a master data management strategy is not only to clean the data, but to also share the data back to the source systems as well as other systems that need the information. Aside from the source systems, another key beneficiary of this data is the business intelligence system. Having clean master data as input to business intelligence systems provides more accurate and enhanced reporting.  Characteristics of Stellar MDM When deciding on the right master data management technology, organizations should look for solutions that have four main characteristics: enterprise-grade MDM performance complete technology that can be rapidly deployed and addresses multiple business issues end-to-end MDM process management with data quality monitoring and assurance pre-built MDM business relevant applications with data stores and workflows These master data management capabilities will aid in moving closer to a best-practice maturity level, delivering tremendous efficiencies and savings as well as revenue growth opportunities as a result of better understanding your customers.  Trevor Naidoo is a senior director in Industry Strategy and Insight at Oracle. 

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  • Fast Data - Big Data's achilles heel

    - by thegreeneman
    At OOW 2013 in Mark Hurd and Thomas Kurian's keynote, they discussed Oracle's Fast Data software solution stack and discussed a number of customers deploying Oracle's Big Data / Fast Data solutions and in particular Oracle's NoSQL Database.  Since that time, there have been a large number of request seeking clarification on how the Fast Data software stack works together to deliver on the promise of real-time Big Data solutions.   Fast Data is a software solution stack that deals with one aspect of Big Data, high velocity.   The software in the Fast Data solution stack involves 3 key pieces and their integration:  Oracle Event Processing, Oracle Coherence, Oracle NoSQL Database.   All three of these technologies address a high throughput, low latency data management requirement.   Oracle Event Processing enables continuous query to filter the Big Data fire hose, enable intelligent chained events to real-time service invocation and augments the data stream to provide Big Data enrichment. Extended SQL syntax allows the definition of sliding windows of time to allow SQL statements to look for triggers on events like breach of weighted moving average on a real-time data stream.    Oracle Coherence is a distributed, grid caching solution which is used to provide very low latency access to cached data when the data is too big to fit into a single process, so it is spread around in a grid architecture to provide memory latency speed access.  It also has some special capabilities to deploy remote behavioral execution for "near data" processing.   The Oracle NoSQL Database is designed to ingest simple key-value data at a controlled throughput rate while providing data redundancy in a cluster to facilitate highly concurrent low latency reads.  For example, when large sensor networks are generating data that need to be captured while analysts are simultaneously extracting the data using range based queries for upstream analytics.  Another example might be storing cookies from user web sessions for ultra low latency user profile management, also leveraging that data using holistic MapReduce operations with your Hadoop cluster to do segmented site analysis.  Understand how NoSQL plays a critical role in Big Data capture and enrichment while simultaneously providing a low latency and scalable data management infrastructure thru clustered, always on, parallel processing in a shared nothing architecture. Learn how easily a NoSQL cluster can be deployed to provide essential services in industry specific Fast Data solutions. See these technologies work together in a demonstration highlighting the salient features of these Fast Data enabling technologies in a location based personalization service. The question then becomes how do these things work together to deliver an end to end Fast Data solution.  The answer is that while different applications will exhibit unique requirements that may drive the need for one or the other of these technologies, often when it comes to Big Data you may need to use them together.   You may have the need for the memory latencies of the Coherence cache, but just have too much data to cache, so you use a combination of Coherence and Oracle NoSQL to handle extreme speed cache overflow and retrieval.   Here is a great reference to how these two technologies are integrated and work together.  Coherence & Oracle NoSQL Database.   On the stream processing side, it is similar as with the Coherence case.  As your sliding windows get larger, holding all the data in the stream can become difficult and out of band data may need to be offloaded into persistent storage.  OEP needs an extreme speed database like Oracle NoSQL Database to help it continue to perform for the real time loop while dealing with persistent spill in the data stream.  Here is a great resource to learn more about how OEP and Oracle NoSQL Database are integrated and work together.  OEP & Oracle NoSQL Database.

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  • Oracle Announces Oracle Big Data Appliance X3-2 and Enhanced Oracle Big Data Connectors

    - by jgelhaus
    Enables Customers to Easily Harness the Business Value of Big Data at Lower Cost Engineered System Simplifies Big Data for the Enterprise Oracle Big Data Appliance X3-2 hardware features the latest 8-core Intel® Xeon E5-2600 series of processors, and compared with previous generation, the 18 compute and storage servers with 648 TB raw storage now offer: 33 percent more processing power with 288 CPU cores; 33 percent more memory per node with 1.1 TB of main memory; and up to a 30 percent reduction in power and cooling Oracle Big Data Appliance X3-2 further simplifies implementation and management of big data by integrating all the hardware and software required to acquire, organize and analyze big data. It includes: Support for CDH4.1 including software upgrades developed collaboratively with Cloudera to simplify NameNode High Availability in Hadoop, eliminating the single point of failure in a Hadoop cluster; Oracle NoSQL Database Community Edition 2.0, the latest version that brings better Hadoop integration, elastic scaling and new APIs, including JSON and C support; The Oracle Enterprise Manager plug-in for Big Data Appliance that complements Cloudera Manager to enable users to more easily manage a Hadoop cluster; Updated distributions of Oracle Linux and Oracle Java Development Kit; An updated distribution of open source R, optimized to work with high performance multi-threaded math libraries Read More   Data sheet: Oracle Big Data Appliance X3-2 Oracle Big Data Appliance: Datacenter Network Integration Big Data and Natural Language: Extracting Insight From Text Thomson Reuters Discusses Oracle's Big Data Platform Connectors Integrate Hadoop with Oracle Big Data Ecosystem Oracle Big Data Connectors is a suite of software built by Oracle to integrate Apache Hadoop with Oracle Database, Oracle Data Integrator, and Oracle R Distribution. Enhancements to Oracle Big Data Connectors extend these data integration capabilities. With updates to every connector, this release includes: Oracle SQL Connector for Hadoop Distributed File System, for high performance SQL queries on Hadoop data from Oracle Database, enhanced with increased automation and querying of Hive tables and now supported within the Oracle Data Integrator Application Adapter for Hadoop; Transparent access to the Hive Query language from R and introduction of new analytic techniques executing natively in Hadoop, enabling R developers to be more productive by increasing access to Hadoop in the R environment. Read More Data sheet: Oracle Big Data Connectors High Performance Connectors for Load and Access of Data from Hadoop to Oracle Database

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  • Best approach to accessing multiple data source in a web application

    - by ced
    I've a base web application developed with .net technologies (asp.net) used into our LAN by 30 users simultanousley. From this web application I've developed two verticalization used from online users. In future i expect hundreds users simultanousley. Our company has different locations. Each site use its own database. The web application needs to retrieve information from all existing databases. Currently there are 3 database, but it's not excluded in the future expansion of new offices. My question then is: What is the best strategy for a web application to retrieve information from different databases (which have the same schema) whereas the main objective performance data access and high fault tolerance? There are case studies in the literature that I can take as an example? Do you know some good documents to study? Do you have any tips to implement this task so efficient? Intuitively I would say that two possible strategy are: perform queries from different sources in real time and aggregate data on the fly; create a repository that contains the union of the entities of interest and perform queries directly on repository;

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  • Introducing the First Global Web Experience Management Content Management System

    - by kellsey.ruppel
    By Calvin Scharffs, VP of Marketing and Product Development, Lingotek Globalizing online content is more important than ever. The total spending power of online consumers around the world is nearly $50 trillion, a recent Common Sense Advisory report found. Three years ago, enterprises would have to translate content into 37 language to reach 98 percent of Internet users. This year, it takes 48 languages to reach the same amount of users.  For companies seeking to increase global market share, “translate frequently and fast” is the name of the game. Today’s content is dynamic and ever-changing, covering the gamut from social media sites to company forums to press releases. With high-quality translation and localization, enterprises can tailor content to consumers around the world.  Speed and Efficiency in Translation When it comes to the “frequently and fast” part of the equation, enterprises run into problems. Professional service providers provide translated content in files, which company workers then have to manually insert into their CMS. When companies update or edit source documents, they have to hunt down all the translated content and change each document individually.  Lingotek and Oracle have solved the problem by making the Lingotek Collaborative Translation Platform fully integrated and interoperable with Oracle WebCenter Sites Web Experience Management. Lingotek combines best-in-class machine translation solutions, real-time community/crowd translation and professional translation to enable companies to publish globalized content in an efficient and cost-effective manner. WebCenter Sites Web Experience Management simplifies the creation and management of different types of content across multiple channels, including social media.  Globalization Without Interrupting the Workflow The combination of the Lingotek platform with WebCenter Sites ensures that process of authoring, publishing, targeting, optimizing and personalizing global Web content is automated, saving companies the time and effort of manually entering content. Users can seamlessly integrate translation into their WebCenter Sites workflows, optimizing their translation and localization across web, social and mobile channels in multiple languages. The original structure and formatting of all translated content is maintained, saving workers the time and effort involved with inserting the text translation and reformatting.  In addition, Lingotek’s continuous publication model addresses the dynamic nature of content, automatically updating the status of translated documents within the WebCenter Sites Workflow whenever users edit or update source documents. This enables users to sync translations in real time. The translation, localization, updating and publishing of Web Experience Management content happens in a single, uninterrupted workflow.  The net result of Lingotek Inside for Oracle WebCenter Sites Web Experience Management is a system that more than meets the need for frequent and fast global translation. Workflows are accelerated. The globalization of content becomes faster and more streamlined. Enterprises save time, cost and effort in translation project management, and can address the needs of each of their global markets in a timely and cost-effective manner.  About Lingotek Lingotek is an Oracle Gold Partner and is going to be one of the first Oracle Validated Integrator (OVI) partners with WebCenter Sites. Lingotek is also an OVI partner with Oracle WebCenter Content.  Watch a video about how Lingotek Inside for Oracle WebCenter Sites works! Oracle WebCenter will be hosting a webinar, “Hitachi Data Systems Improves Global Web Experiences with Oracle WebCenter," tomorrow, September 13th. To attend the webinar, please register now! For more information about Lingotek for Oracle WebCenter, please visit http://www.lingotek.com/oracle.

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  • Management and Monitoring Tools for Windows Azure

    - by BuckWoody
    With such a large platform, Windows Azure has a lot of moving parts. We’ve done our best to keep the interface as simple as possible, while giving you the most control and visibility we can. However, as with most Microsoft products, there are multiple ways to do something – and I’ve always found that to be a good strength. Depending on the situation, I might want a graphical interface, a command-line interface, or just an API so I can incorporate the management into my own tools, or have third-party companies write other tools. While by no means exhaustive, I thought I might put together a quick list of a few tools you can use to manage and monitor Windows Azure components, from our IaaS, SaaS and PaaS offerings. Some of the products focus on one area more than another, but all are available today. I’ll try and maintain this list to keep it current, but make sure you check the date of this post’s update – if it’s more than six months old, it’s most likely out of date. Things move fast in the cloud. The Windows Azure Management Portal The primary tool for managing Windows Azure is our portal – most everything you need is there, from creating new services to querying a database. There are two versions as of this writing – a Silverlight client version, and a newer HTML5 version. The latter is being updated constantly to be in parity with the Silverlight client. There’s a balance in this portal between simplicity and power – we’re following the “less is more” approach, with increasing levels of detail as you work through the portal rather than overwhelming you with a single, long “more is more” page. You can find the Portal here: http://windowsazure.com (then click “Log In” and then “Portal”) Windows Azure Management API You can also use programming tools to either write your own interface, or simply provide management functions directly within your solution. You have two options – you can use the more universal REST API’s, which area bit more complex but work with any system that can write to them, or the more approachable .NET API calls in code. You can find the reference for the API’s here: http://msdn.microsoft.com/en-us/library/windowsazure/ee460799.aspx  All Class Libraries, for each part of Windows Azure: http://msdn.microsoft.com/en-us/library/ee393295.aspx  PowerShell Command-lets PowerShell is one of the most powerful scripting languages I’ve used with Windows – and it’s baked into all of our products. When you need to work with multiple servers, scripting is really the only way to go, and the Windows Azure PowerShell Command-Lets allow you to work across most any part of the platform – and can even be used within the services themselves. You can do everything with them from creating a new IaaS, PaaS or SaaS service, to controlling them and even working with security and more. You can find more about the Command-Lets here: http://wappowershell.codeplex.com/documentation (older link, still works, will point you to the new ones as well) We have command-line utilities for other operating systems as well: https://www.windowsazure.com/en-us/manage/downloads/  Video walkthrough of using the Command-Lets: http://channel9.msdn.com/Events/BUILD/BUILD2011/SAC-859T  System Center System Center is actually a suite of graphical tools you can use to manage, deploy, control, monitor and tune software from Microsoft and even other platforms. This will be the primary tool we’ll recommend for managing a hybrid or contiguous management process – and as time goes on you’ll see more and more features put into System Center for the entire Windows Azure suite of products. You can find the Management Pack and README for it here: http://www.microsoft.com/en-us/download/details.aspx?id=11324  SQL Server Management Studio / Data Tools / Visual Studio SQL Server has two built-in management and development, and since Version 2008 R2, you can use them to manage Windows Azure Databases. Visual Studio also lets you connect to and manage portions of Windows Azure as well as Windows Azure Databases. You can read more about Visual Studio here: http://msdn.microsoft.com/en-us/library/windowsazure/ee405484  You can read more about the SQL tools here: http://msdn.microsoft.com/en-us/library/windowsazure/ee621784.aspx  Vendor-Provided Tools Microsoft does not suggest or endorse a specific third-party product. We do, however, use them, and see lots of other customers use them. You can browse to these sites to learn more, and chat with their folks directly on how they support Windows Azure. Cerebrata: Tools for managing from the command-line, graphical diagnostics, graphical storage management - http://www.cerebrata.com/  Quest Cloud Tools: Monitoring, Storage Management, and costing tools - http://communities.quest.com/community/cloud-tools  Paraleap: Monitoring tool - http://www.paraleap.com/AzureWatch  Cloudgraphs: Monitoring too -  http://www.cloudgraphs.com/  Opstera: Monitoring for Windows Azure and a Scale-out pattern manager - http://www.opstera.com/products/Azureops/  Compuware: SaaS performance monitoring, load testing -  http://www.compuware.com/application-performance-management/gomez-apm-products.html  SOASTA: Penetration and Security Testing - http://www.soasta.com/cloudtest/enterprise/  LoadStorm: Load-testing tool - http://loadstorm.com/windows-azure  Open-Source Tools This is probably the most specific set of tools, and the list I’ll have to maintain most often. Smaller projects have a way of coming and going, so I’ll try and make sure this list is current. Windows Azure MMC: (I actually use this one a lot) http://wapmmc.codeplex.com/  Windows Azure Diagnostics Monitor: http://archive.msdn.microsoft.com/wazdmon  Azure Application Monitor: http://azuremonitor.codeplex.com/  Azure Web Log: http://www.xentrik.net/software/azure_web_log.html  Cloud Ninja:Multi-Tennant billing and performance monitor -  http://cnmb.codeplex.com/  Cloud Samurai: Multi-Tennant Management- http://cloudsamurai.codeplex.com/    If you have additions to this list, please post them as a comment and I’ll research and then add them. Thanks!

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  • Management and Monitoring Tools for Windows Azure

    - by BuckWoody
    With such a large platform, Windows Azure has a lot of moving parts. We’ve done our best to keep the interface as simple as possible, while giving you the most control and visibility we can. However, as with most Microsoft products, there are multiple ways to do something – and I’ve always found that to be a good strength. Depending on the situation, I might want a graphical interface, a command-line interface, or just an API so I can incorporate the management into my own tools, or have third-party companies write other tools. While by no means exhaustive, I thought I might put together a quick list of a few tools you can use to manage and monitor Windows Azure components, from our IaaS, SaaS and PaaS offerings. Some of the products focus on one area more than another, but all are available today. I’ll try and maintain this list to keep it current, but make sure you check the date of this post’s update – if it’s more than six months old, it’s most likely out of date. Things move fast in the cloud. The Windows Azure Management Portal The primary tool for managing Windows Azure is our portal – most everything you need is there, from creating new services to querying a database. There are two versions as of this writing – a Silverlight client version, and a newer HTML5 version. The latter is being updated constantly to be in parity with the Silverlight client. There’s a balance in this portal between simplicity and power – we’re following the “less is more” approach, with increasing levels of detail as you work through the portal rather than overwhelming you with a single, long “more is more” page. You can find the Portal here: http://windowsazure.com (then click “Log In” and then “Portal”) Windows Azure Management API You can also use programming tools to either write your own interface, or simply provide management functions directly within your solution. You have two options – you can use the more universal REST API’s, which area bit more complex but work with any system that can write to them, or the more approachable .NET API calls in code. You can find the reference for the API’s here: http://msdn.microsoft.com/en-us/library/windowsazure/ee460799.aspx  All Class Libraries, for each part of Windows Azure: http://msdn.microsoft.com/en-us/library/ee393295.aspx  PowerShell Command-lets PowerShell is one of the most powerful scripting languages I’ve used with Windows – and it’s baked into all of our products. When you need to work with multiple servers, scripting is really the only way to go, and the Windows Azure PowerShell Command-Lets allow you to work across most any part of the platform – and can even be used within the services themselves. You can do everything with them from creating a new IaaS, PaaS or SaaS service, to controlling them and even working with security and more. You can find more about the Command-Lets here: http://wappowershell.codeplex.com/documentation (older link, still works, will point you to the new ones as well) We have command-line utilities for other operating systems as well: https://www.windowsazure.com/en-us/manage/downloads/  Video walkthrough of using the Command-Lets: http://channel9.msdn.com/Events/BUILD/BUILD2011/SAC-859T  System Center System Center is actually a suite of graphical tools you can use to manage, deploy, control, monitor and tune software from Microsoft and even other platforms. This will be the primary tool we’ll recommend for managing a hybrid or contiguous management process – and as time goes on you’ll see more and more features put into System Center for the entire Windows Azure suite of products. You can find the Management Pack and README for it here: http://www.microsoft.com/en-us/download/details.aspx?id=11324  SQL Server Management Studio / Data Tools / Visual Studio SQL Server has two built-in management and development, and since Version 2008 R2, you can use them to manage Windows Azure Databases. Visual Studio also lets you connect to and manage portions of Windows Azure as well as Windows Azure Databases. You can read more about Visual Studio here: http://msdn.microsoft.com/en-us/library/windowsazure/ee405484  You can read more about the SQL tools here: http://msdn.microsoft.com/en-us/library/windowsazure/ee621784.aspx  Vendor-Provided Tools Microsoft does not suggest or endorse a specific third-party product. We do, however, use them, and see lots of other customers use them. You can browse to these sites to learn more, and chat with their folks directly on how they support Windows Azure. Cerebrata: Tools for managing from the command-line, graphical diagnostics, graphical storage management - http://www.cerebrata.com/  Quest Cloud Tools: Monitoring, Storage Management, and costing tools - http://communities.quest.com/community/cloud-tools  Paraleap: Monitoring tool - http://www.paraleap.com/AzureWatch  Cloudgraphs: Monitoring too -  http://www.cloudgraphs.com/  Opstera: Monitoring for Windows Azure and a Scale-out pattern manager - http://www.opstera.com/products/Azureops/  Compuware: SaaS performance monitoring, load testing -  http://www.compuware.com/application-performance-management/gomez-apm-products.html  SOASTA: Penetration and Security Testing - http://www.soasta.com/cloudtest/enterprise/  LoadStorm: Load-testing tool - http://loadstorm.com/windows-azure  Open-Source Tools This is probably the most specific set of tools, and the list I’ll have to maintain most often. Smaller projects have a way of coming and going, so I’ll try and make sure this list is current. Windows Azure MMC: (I actually use this one a lot) http://wapmmc.codeplex.com/  Windows Azure Diagnostics Monitor: http://archive.msdn.microsoft.com/wazdmon  Azure Application Monitor: http://azuremonitor.codeplex.com/  Azure Web Log: http://www.xentrik.net/software/azure_web_log.html  Cloud Ninja:Multi-Tennant billing and performance monitor -  http://cnmb.codeplex.com/  Cloud Samurai: Multi-Tennant Management- http://cloudsamurai.codeplex.com/    If you have additions to this list, please post them as a comment and I’ll research and then add them. Thanks!

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  • Mobile Identity Management at SuperValu

    - by Tanu Sood
    While organizations are fast embracing BYOD (Bring Your Own Device) culture to attract and retain best talent, improve productivity, bring agility and drive down costs, SuperValu coined their own term (and trend): TYDH – Take Your Device Home. Yes, SuperValu, a Minn based, 18,000 employees strong, food retailer handed out 2,200 iPads to store directors at locations across the country. The motivation behind this reverse trend? Phillip Black, Director of Identity & Access Management at SuperValu, shared the reasoning behind this trend in his talk at last week’s Oracle OpenWorld 2012. "It gives them productivity tools to better manage their store," says Black. Intrigued? Find out more in this recently published news article. And learn more about Oracle Identity Management 11gR2 mobile- and social- ready sign-on features today. Additional Resources: Press Release: Oracle announces Identity Management 11g Release 2 On-Demand webcast: Identity Management 11gR2 Launch Oracle Magazine: Security on the Move Website: Oracle Identity Management Blog Post: Mobile and Social Sign-on with Oracle Access Management

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  • SQL SERVER – Introduction to Big Data – Guest Post

    - by pinaldave
    BIG Data – such a big word – everybody talks about this now a days. It is the word in the database world. In one of the conversation I asked my friend Jasjeet Sigh the same question – what is Big Data? He instantly came up with a very effective write-up.  Jasjeet is working as a Technical Manager with Koenig Solutions. He leads the SQL domain, and holds rich IT industry experience. Talking about Koenig, it is a 19 year old IT training company that offers several certification choices. Some of its courses include SharePoint Training, Project Management certifications, Microsoft Trainings, Business Intelligence programs, Web Design and Development courses etc. Big Data, as the name suggests, is about data that is BIG in nature. The data is BIG in terms of size, and it is difficult to manage such enormous data with relational database management systems that are quite popular these days. Big Data is not just about being large in size, it is also about the variety of the data that differs in form or type. Some examples of Big Data are given below : Scientific data related to weather and atmosphere, Genetics etc Data collected by various medical procedures, such as Radiology, CT scan, MRI etc Data related to Global Positioning System Pictures and Videos Radio Frequency Data Data that may vary very rapidly like stock exchange information Apart from difficulties in managing and storing such data, it is difficult to query, analyze and visualize it. The characteristics of Big Data can be defined by four Vs: Volume: It simply means a large volume of data that may span Petabyte, Exabyte and so on. However it also depends organization to organization that what volume of data they consider as Big Data. Variety: As discussed above, Big Data is not limited to relational information or structured Data. It can also include unstructured data like pictures, videos, text, audio etc. Velocity:  Velocity means the speed by which data changes. The higher is the velocity, the more efficient should be the system to capture and analyze the data. Missing any important point may lead to wrong analysis or may even result in loss. Veracity: It has been recently added as the fourth V, and generally means truthfulness or adherence to the truth. In terms of Big Data, it is more of a challenge than a characteristic. It is difficult to ascertain the truth out of the enormous amount of data and the one that has high velocity. There are always chances of having un-precise and uncertain data. It is a challenging task to clean such data before it is analyzed. Big Data can be considered as the next big thing in the IT sector in terms of innovation and development. If appropriate technologies are developed to analyze and use the information, it can be the driving force for almost all industrial segments. These include Retail, Manufacturing, Service, Finance, Healthcare etc. This will help them to automate business decisions, increase productivity, and innovate and develop new products. Thanks Jasjeet Singh for an excellent write up.  Jasjeet Sign is working as a Technical Manager with Koenig Solutions. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Database, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Big Data

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  • Creating a Corporate Data Hub

    - by BuckWoody
    The Windows Azure Marketplace has a rich assortment of data and software offerings for you to use – a type of Software as a Service (SaaS) for IT workers, not necessarily for end-users. Among those offerings is the “Data Hub” – a  codename for a project that ironically actually does what the codename says. In many of our organizations, we have multiple data quality issues. Finding data is one problem, but finding it just once is often a bigger problem. Lots of departments and even individuals have stored the same data more than once, and in some cases, made changes to one of the copies. It’s difficult to know which location or version of the data is authoritative. Then there’s the problem of accessing the data. It’s fairly straightforward to publish a database, share or other location internally to store the data. But then you have to figure out who owns it, how it is controlled, and pass out the various connection strings to those who want to use it. And then you need to figure out how to let folks access the internal data externally – bringing up all kinds of security issues. Finally, in many cases our user community wants us to combine data from the internally sources with external data, bringing up the security, strings, and exploration features up all over again. Enter the Data Hub. This is an online offering, where you assign an administrator and data stewards. You import the data into the service, and it’s available to you - and only you and your organization if you wish. The basic steps for this service are to set up the portal for your company, assign administrators and permissions, and then you assign data areas and import data into them. From there you make them discoverable, and then you have multiple options that you or your users can access that data. You’re then able, if you wish, to combine that data with other data in one location. So how does all that work? What about security? Is it really that easy? And can you really move the data definition off to the Subject Matter Experts (SME’s) that know the particular data stack better than the IT team does? Well, nothing good is easy – but using the Data Hub is actually pretty simple. I’ll give you a link in a moment where you can sign up and try this yourself. Once you sign up, you assign an administrator. From there you’ll create data areas, and then use a simple interface to bring the data in. All of this is done in a portal interface – nothing to install, configure, update or manage. After the data is entered in, and you’ve assigned meta-data to describe it, your users have multiple options to access it. They can simply use the portal – which actually has powerful visualizations you can use on any platform, even mobile phones or tablets.     Your users can also hit the data with Excel – which gives them ultimate flexibility for display, all while using an authoritative, single reference for the data. Since the service is online, they can do this wherever they are – given the proper authentication and permissions. You can also hit the service with simple API calls, like this one from C#: http://msdn.microsoft.com/en-us/library/hh921924  You can make HTTP calls instead of code, and the data can even be exposed as an OData Feed. As you can see, there are a lot of options. You can check out the offering here: http://www.microsoft.com/en-us/sqlazurelabs/labs/data-hub.aspx and you can read the documentation here: http://msdn.microsoft.com/en-us/library/hh921938

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  • Creating a Corporate Data Hub

    - by BuckWoody
    The Windows Azure Marketplace has a rich assortment of data and software offerings for you to use – a type of Software as a Service (SaaS) for IT workers, not necessarily for end-users. Among those offerings is the “Data Hub” – a  codename for a project that ironically actually does what the codename says. In many of our organizations, we have multiple data quality issues. Finding data is one problem, but finding it just once is often a bigger problem. Lots of departments and even individuals have stored the same data more than once, and in some cases, made changes to one of the copies. It’s difficult to know which location or version of the data is authoritative. Then there’s the problem of accessing the data. It’s fairly straightforward to publish a database, share or other location internally to store the data. But then you have to figure out who owns it, how it is controlled, and pass out the various connection strings to those who want to use it. And then you need to figure out how to let folks access the internal data externally – bringing up all kinds of security issues. Finally, in many cases our user community wants us to combine data from the internally sources with external data, bringing up the security, strings, and exploration features up all over again. Enter the Data Hub. This is an online offering, where you assign an administrator and data stewards. You import the data into the service, and it’s available to you - and only you and your organization if you wish. The basic steps for this service are to set up the portal for your company, assign administrators and permissions, and then you assign data areas and import data into them. From there you make them discoverable, and then you have multiple options that you or your users can access that data. You’re then able, if you wish, to combine that data with other data in one location. So how does all that work? What about security? Is it really that easy? And can you really move the data definition off to the Subject Matter Experts (SME’s) that know the particular data stack better than the IT team does? Well, nothing good is easy – but using the Data Hub is actually pretty simple. I’ll give you a link in a moment where you can sign up and try this yourself. Once you sign up, you assign an administrator. From there you’ll create data areas, and then use a simple interface to bring the data in. All of this is done in a portal interface – nothing to install, configure, update or manage. After the data is entered in, and you’ve assigned meta-data to describe it, your users have multiple options to access it. They can simply use the portal – which actually has powerful visualizations you can use on any platform, even mobile phones or tablets.     Your users can also hit the data with Excel – which gives them ultimate flexibility for display, all while using an authoritative, single reference for the data. Since the service is online, they can do this wherever they are – given the proper authentication and permissions. You can also hit the service with simple API calls, like this one from C#: http://msdn.microsoft.com/en-us/library/hh921924  You can make HTTP calls instead of code, and the data can even be exposed as an OData Feed. As you can see, there are a lot of options. You can check out the offering here: http://www.microsoft.com/en-us/sqlazurelabs/labs/data-hub.aspx and you can read the documentation here: http://msdn.microsoft.com/en-us/library/hh921938

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  • git: 'log master..origin/master' not behaving as expected

    - by steve jaffe
    I'm trying to compare my copy of 'master' to that on the remote repository which it tracks. I thought that the following command would work, and often it seems to. However, sometimes it produces nothing and yet I know that the remote branch has many changes, which I can confirm by doing a pull. git log master..origin/master Can anyone explain this behavior and tell me what command I should be using to determine the changes between local and remote? [Another piece of data: I've had it happen that 'git log master..origin/master' produces nothing. Then I do a pull. The pull fails because I have a working copy of some file. After this, 'git log master..origin/master' does show me the differences. It seems the pull has updated some local log? If so, how could I achieve this without doing (or attempting to do) a pull?]

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