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  • Oracle Data Integration 12c: Perspectives of Industry Experts, Customers and Partners

    - by Irem Radzik
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 As you may have seen from our recent blog posts on Oracle Data Integrator 12c and Oracle GoldenGate 12c, we are very excited to share with you the great new features the 12c release brings to Oracle’s data integration solutions. And, fortunately we are not alone in this sentiment. Since the press announcement October 17th, which incorporates our customers' and experts' testimonials, we have seen positive comments in leading technology publications and social media as well. Here are some examples: In CIO and PCWorld you can find Joab Jackson’s article, Oracle Data Integrator 12c ready for real-time analysis, where wrote about the tight integration between Oracle Data Integrator and Oracle GoldenGate . He noted “Heeding the call from enterprise customers who clamor for more immediacy in their data-driven reports, Oracle has updated its data-integration software portfolio so that it can more rapidly deliver data to data warehouses and analysis applications.” Integration Developer News’ Vance McCarthy wrote the article Oracle Ships ‘Future Proofs’ Integration Tools for Traditional, Cloud, Big Data, Real-Time Projects and mentioned that “Oracle Data Integrator 12c and Oracle GoldenGate 12c sport a wide range of improvements to let devs more easily deliver data integration for cloud, analytics, big data and other new projects that leverage multiple datasets for business.“ InformationWeek’s Doug Henschen gave a great overview to several key features including the new flow-based UI in Oracle Data Integrator. Doug said “Oracle Data Integrator 12c introduces a complete makeover of the job-building experience, while real-time oriented GoldenGate 12c introduces performance gains “. In Database Trends and Applications’ article Oracle Strengthens Data Integration with Release of Oracle Data Integrator 12c and Oracle GoldenGate 12c highlighted the productivity aspect of the new solution with his remarks: “tight integration between Oracle Data Integrator 12c and Oracle GoldenGate 12c enables developers to leverage Oracle GoldenGate’s low overhead, real-time change data capture completely within the Oracle Data Integrator Studio without additional training”. We are also thrilled about what our customers and partners have to say about our products and the new release. And we are equally excited to share those perspectives with you in our upcoming launch video webcast on November 12th. SolarWorld Industries America’s Senior Database Manager, Russ Toyama will join our executives in our studio in Redwood Shores to discuss GoldenGate’s core benefits and the new release, while Surren Partharb, CTO of Strategic Technology Services for BT, and Mark Rittman, CTO of Rittman Mead, will provide their comments via the interviews conducted in the UK. This interactive panel discussion in the video webcast will unveil the new release with the expertise of our development executives and the great insight from our customers and partners. In addition, our product experts will be available online to answer chat questions. This is really a great opportunity to learn how Oracle's data integration offering has changed the integration and replication technology space with the new release, and established itself as the new leader. If you have not registered for this free event yet, you can do so via this link. We will run the live event at 8am PT/4pm GMT, followed by a replay of the event with live chat for Q&A  at 10am PT/6pm GMT. The replay will be available on-demand for those who register but cannot attend either session on November 12th. /* 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-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Times New Roman","serif"; mso-fareast-font-family:"Times New Roman";}

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  • Is Master Data Management CRM's Secret Sauce?

    - by divya.malik
    This was the title of a recent blog entry by our colleagues in EMEA. Having a good master data management system enables organizations to get a unified, accurate and complete understanding of their customers. Gartner Group's John Radcliffe explains why MDM is destined to be at the heart of future CRM and social CRM projects. Experts are predicting big things for master data management (MDM) in the immediate future. While far from being a new kid on the block, its potential benefits at a time when organisations are drowning in data mean that it is in the right place at the right time. "MDM is not 'nice to have'," explains John Radcliffe, research vice president at Gartner. "If tackled in the right way it can provide near term business value that plays into an organisation's new focus on cost efficiencies, risk management and regulatory compliance, while supporting growth and future transformative strategies." The complete article can be found here.

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  • Custommer Centric Wealth Management

    - by michael.seback
    While the world continues to search their way out of the recent financial turmoil and recession, it has no doubt churned out the inherent faults in the wealth management industry and the larger financial system. In order to counter these apprehensions, wealth management firms are now actively seeking and evaluating avenues to re-build the lost trust. They are looking at engaging their customers in managing their investments in a more collaborative and transparent manner. At the same time, wealth managers are also seeking to empower themselves with complete and comprehensive customer information in order to provide the best advice and the best solution at the right time. Read your copy of this new global White Paper on Wealth Management.

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  • Generating Landed Cost Management Charges using Custom Pricing Attributes

    - by ChristineS-Oracle
    Learn how to incorporate Custom Pricing Attributes into Landed Cost Management through a new whitepaper.  The new application, Landed Cost Management (LCM), enables exact shipment charges to be applied to incoming receipts. These charges are calculated using the Freight and Special Charges functionality from Advanced Pricing within the Pricing Transaction Entity of “Purchasing”.Advanced Pricing is very flexible in that custom attributes can be defined to derive specific charges. The way that Landed Cost Management builds these attributes is different from the processing for Advanced Pricing with Purchasing.The whitepaper can be downloaded from document Oracle Advanced Pricing White Papers, Doc ID 136687.1.

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  • Project life cycle management - Maven vs 'manual' approach

    - by jb10210
    I have a question concerning the life cycle management of a/multiple project(s), more specific to the advantages/disadvantages of using technologies such as Maven. Currently we work in a continuous-integration environment but lots of things still need to be manually performed (dependency management, deploying, setting up documentation, generating stats, ...). My impression is that this approach often leads to errors, miscommunications or things just are forgotten. I know and have used Maven in the past but in smaller environments and I was always really enthusiastic about it. But I was wondering if someone could share some insights, experiences, pros, contras, ... about the use of Maven (or similar technology) in larger environments and for multiple projects. I would like to use the suggestions made here to start the debate about moving to the next level in project management!

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  • Webcast: Oracle Transportation Management Installation

    - by ChristineS
    Webcast: Oracle Transportation Management Installation Date:  November 19, 2013 at 9:30 pm India Time (Mumbai, GMT+05:30), 11:00 am ET, 10:00 am CT, 9:00 am MT, 8:00 PT This one-hour session is recommended for Technical Users, System Administrators, and DBAs who will be installing Oracle Transportation Management. This webcast walks through the steps to install WebLogic, OTM Installer and OHS Installer. We are covering following topics in this Webcast : Review required steps before doing them Ask questions to live OTM Expert while going through the steps Reduce the number of errors while installing Reduce the need to log an SR during the installation process Details & Registration : Doc ID 1591674.1.Direct registration link If you have a suggestion for an Advisor Webcast to be planned in future, please post in our Community Forum What Order Management Advisor Webcast topics do YOU want to see presented?. Remember that you can access a full listing of all future webcasts as well as replays from Doc ID 740966.1. 

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  • New Big Data Appliance Security Features

    - by mgubar
    The Oracle Big Data Appliance (BDA) is an engineered system for big data processing.  It greatly simplifies the deployment of an optimized Hadoop Cluster – whether that cluster is used for batch or real-time processing.  The vast majority of BDA customers are integrating the appliance with their Oracle Databases and they have certain expectations – especially around security.  Oracle Database customers have benefited from a rich set of security features:  encryption, redaction, data masking, database firewall, label based access control – and much, much more.  They want similar capabilities with their Hadoop cluster.    Unfortunately, Hadoop wasn’t developed with security in mind.  By default, a Hadoop cluster is insecure – the antithesis of an Oracle Database.  Some critical security features have been implemented – but even those capabilities are arduous to setup and configure.  Oracle believes that a key element of an optimized appliance is that its data should be secure.  Therefore, by default the BDA delivers the “AAA of security”: authentication, authorization and auditing. Security Starts at Authentication A successful security strategy is predicated on strong authentication – for both users and software services.  Consider the default configuration for a newly installed Oracle Database; it’s been a long time since you had a legitimate chance at accessing the database using the credentials “system/manager” or “scott/tiger”.  The default Oracle Database policy is to lock accounts thereby restricting access; administrators must consciously grant access to users. Default Authentication in Hadoop By default, a Hadoop cluster fails the authentication test. For example, it is easy for a malicious user to masquerade as any other user on the system.  Consider the following scenario that illustrates how a user can access any data on a Hadoop cluster by masquerading as a more privileged user.  In our scenario, the Hadoop cluster contains sensitive salary information in the file /user/hrdata/salaries.txt.  When logged in as the hr user, you can see the following files.  Notice, we’re using the Hadoop command line utilities for accessing the data: $ hadoop fs -ls /user/hrdataFound 1 items-rw-r--r--   1 oracle supergroup         70 2013-10-31 10:38 /user/hrdata/salaries.txt$ hadoop fs -cat /user/hrdata/salaries.txtTom Brady,11000000Tom Hanks,5000000Bob Smith,250000Oprah,300000000 User DrEvil has access to the cluster – and can see that there is an interesting folder called “hrdata”.  $ hadoop fs -ls /user Found 1 items drwx------   - hr supergroup          0 2013-10-31 10:38 /user/hrdata However, DrEvil cannot view the contents of the folder due to lack of access privileges: $ hadoop fs -ls /user/hrdata ls: Permission denied: user=drevil, access=READ_EXECUTE, inode="/user/hrdata":oracle:supergroup:drwx------ Accessing this data will not be a problem for DrEvil. He knows that the hr user owns the data by looking at the folder’s ACLs. To overcome this challenge, he will simply masquerade as the hr user. On his local machine, he adds the hr user, assigns that user a password, and then accesses the data on the Hadoop cluster: $ sudo useradd hr $ sudo passwd $ su hr $ hadoop fs -cat /user/hrdata/salaries.txt Tom Brady,11000000 Tom Hanks,5000000 Bob Smith,250000 Oprah,300000000 Hadoop has not authenticated the user; it trusts that the identity that has been presented is indeed the hr user. Therefore, sensitive data has been easily compromised. Clearly, the default security policy is inappropriate and dangerous to many organizations storing critical data in HDFS. Big Data Appliance Provides Secure Authentication The BDA provides secure authentication to the Hadoop cluster by default – preventing the type of masquerading described above. It accomplishes this thru Kerberos integration. Figure 1: Kerberos Integration The Key Distribution Center (KDC) is a server that has two components: an authentication server and a ticket granting service. The authentication server validates the identity of the user and service. Once authenticated, a client must request a ticket from the ticket granting service – allowing it to access the BDA’s NameNode, JobTracker, etc. At installation, you simply point the BDA to an external KDC or automatically install a highly available KDC on the BDA itself. Kerberos will then provide strong authentication for not just the end user – but also for important Hadoop services running on the appliance. You can now guarantee that users are who they claim to be – and rogue services (like fake data nodes) are not added to the system. It is common for organizations to want to leverage existing LDAP servers for common user and group management. Kerberos integrates with LDAP servers – allowing the principals and encryption keys to be stored in the common repository. This simplifies the deployment and administration of the secure environment. Authorize Access to Sensitive Data Kerberos-based authentication ensures secure access to the system and the establishment of a trusted identity – a prerequisite for any authorization scheme. Once this identity is established, you need to authorize access to the data. HDFS will authorize access to files using ACLs with the authorization specification applied using classic Linux-style commands like chmod and chown (e.g. hadoop fs -chown oracle:oracle /user/hrdata changes the ownership of the /user/hrdata folder to oracle). Authorization is applied at the user or group level – utilizing group membership found in the Linux environment (i.e. /etc/group) or in the LDAP server. For SQL-based data stores – like Hive and Impala – finer grained access control is required. Access to databases, tables, columns, etc. must be controlled. And, you want to leverage roles to facilitate administration. Apache Sentry is a new project that delivers fine grained access control; both Cloudera and Oracle are the project’s founding members. Sentry satisfies the following three authorization requirements: Secure Authorization:  the ability to control access to data and/or privileges on data for authenticated users. Fine-Grained Authorization:  the ability to give users access to a subset of the data (e.g. column) in a database Role-Based Authorization:  the ability to create/apply template-based privileges based on functional roles. With Sentry, “all”, “select” or “insert” privileges are granted to an object. The descendants of that object automatically inherit that privilege. A collection of privileges across many objects may be aggregated into a role – and users/groups are then assigned that role. This leads to simplified administration of security across the system. Figure 2: Object Hierarchy – granting a privilege on the database object will be inherited by its tables and views. Sentry is currently used by both Hive and Impala – but it is a framework that other data sources can leverage when offering fine-grained authorization. For example, one can expect Sentry to deliver authorization capabilities to Cloudera Search in the near future. Audit Hadoop Cluster Activity Auditing is a critical component to a secure system and is oftentimes required for SOX, PCI and other regulations. The BDA integrates with Oracle Audit Vault and Database Firewall – tracking different types of activity taking place on the cluster: Figure 3: Monitored Hadoop services. At the lowest level, every operation that accesses data in HDFS is captured. The HDFS audit log identifies the user who accessed the file, the time that file was accessed, the type of access (read, write, delete, list, etc.) and whether or not that file access was successful. The other auditing features include: MapReduce:  correlate the MapReduce job that accessed the file Oozie:  describes who ran what as part of a workflow Hive:  captures changes were made to the Hive metadata The audit data is captured in the Audit Vault Server – which integrates audit activity from a variety of sources, adding databases (Oracle, DB2, SQL Server) and operating systems to activity from the BDA. Figure 4: Consolidated audit data across the enterprise.  Once the data is in the Audit Vault server, you can leverage a rich set of prebuilt and custom reports to monitor all the activity in the enterprise. In addition, alerts may be defined to trigger violations of audit policies. Conclusion Security cannot be considered an afterthought in big data deployments. Across most organizations, Hadoop is managing sensitive data that must be protected; it is not simply crunching publicly available information used for search applications. The BDA provides a strong security foundation – ensuring users are only allowed to view authorized data and that data access is audited in a consolidated framework.

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  • How to present a stable data model in a public API that allows internal data structures to be changed without breaking the public view of the data?

    - by Max Palmer
    I am in the process of developing an application that allows users to write C# scripts. These scripts allow users to call selected methods and to access and manipulate data in a document. This works well, however, in the development version, scripts access the document's (internal) data structures directly. This means that if we were to change the internal data model/structure, there is a good chance that someone's script will no longer compile. We obviously want to prevent this breaking change from happening, but still want to allow the user to write sensible C# code (whilst not restricting how we develop our internal data model as a result). We therefore need to decouple our scripting API and its data structures from our internal methods and data structures. We've a few ideas as to how we might allow the user to access a what is effectively a stable public version of the document's internal data*, but I wanted to throw the question out there to someone who might have some real experience of this problem. NB our internal document's data structure is quite complex and it could be quite difficult to wrap. We know we want to expose as little as possible in our public API, especially as once it's out there, it's out there for good. Can anyone help? How do scripting languages / APIs decouple their public API and data structures from their internal data structures? Is there no real alternative to having to write a complex interaction layer? If we need to do this, what's a good approach or pattern for wrapping complex data structures that include nested objects, including collections? I've looked at the API facade pattern, which looks like it's trying to address these kinds of issues, but are there alternatives? *One idea is to build a data facade that is kept stable across versions of our application. The facade exposes a set of facade data objects that are used in the script code. These maintain backwards compatibility and wrap access to our internal document's data model.

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  • Integrating Oracle Hyperion Smart View Data Queries with MS Word and Power Point

    - by Andreea Vaduva
    Untitled Document table { border: thin solid; } Most Smart View users probably appreciate that they can use just one add-in to access data from the different sources they might work with, like Oracle Essbase, Oracle Hyperion Planning, Oracle Hyperion Financial Management and others. But not all of them are aware of the options to integrate data analyses not only in Excel, but also in MS Word or Power Point. While in the past, copying and pasting single numbers or tables from a recent analysis in Excel made the pasted content a static snapshot, copying so called Data Points now creates dynamic, updateable references to the data source. It also provides additional nice features, which can make life easier and less stressful for Smart View users. So, how does this option work: after building an ad-hoc analysis with Smart View as usual in an Excel worksheet, any area including data cells/numbers from the database can be highlighted in order to copy data points - even single data cells only.   TIP It is not necessary to highlight and copy the row or column descriptions   Next from the Smart View ribbon select Copy Data Point. Then transfer to the Word or Power Point document into which the selected content should be copied. Note that in these Office programs you will find a menu item Smart View;from it select the Paste Data Point icon. The copied details from the Excel report will be pasted, but showing #NEED_REFRESH in the data cells instead of the original numbers. =After clicking the Refresh icon on the Smart View menu the data will be retrieved and displayed. (Maybe at that moment a login window pops up and you need to provide your credentials.) It works in the same way if you just copy one single number without any row or column descriptions, for example in order to incorporate it into a continuous text: Before refresh: After refresh: From now on for any subsequent updates of the data shown in your documents you only need to refresh data by clicking the Refresh button on the Smart View menu, without copying and pasting the context or content again. As you might realize, trying out this feature on your own, there won’t be any Point of View shown in the Office document. Also you have seen in the example, where only a single data cell was copied, that there aren’t any member names or row/column descriptions copied, which are usually required in an ad-hoc report in order to exactly define where data comes from or how data is queried from the source. Well, these definitions are not visible, but they are transferred to the Word or Power Point document as well. They are stored in the background for each individual data cell copied and can be made visible by double-clicking the data cell as shown in the following screen shot (but which is taken from another context).   So for each cell/number the complete connection information is stored along with the exact member/cell intersection from the database. And that’s not all: you have the chance now to exchange the members originally selected in the Point of View (POV) in the Excel report. Remember, at that time we had the following selection:   By selecting the Manage POV option from the Smart View meny in Word or Power Point…   … the following POV Manager – Queries window opens:   You can now change your selection for each dimension from the original POV by either double-clicking the dimension member in the lower right box under POV: or by selecting the Member Selector icon on the top right hand side of the window. After confirming your changes you need to refresh your document again. Be aware, that this will update all (!) numbers taken from one and the same original Excel sheet, even if they appear in different locations in your Office document, reflecting your recent changes in the POV. TIP Build your original report already in a way that dimensions you might want to change from within Word or Power Point are placed in the POV. And there is another really nice feature I wouldn’t like to miss mentioning: Using Dynamic Data Points in the way described above, you will never miss or need to search again for your original Excel sheet from which values were taken and copied as data points into an Office document. Because from even only one single data cell Smart View is able to recreate the entire original report content with just a few clicks: Select one of the numbers from within your Word or Power Point document by double-clicking.   Then select the Visualize in Excel option from the Smart View menu. Excel will open and Smart View will rebuild the entire original report, including POV settings, and retrieve all data from the most recent actual state of the database. (It might be necessary to provide your credentials before data is displayed.) However, in order to make this work, an active online connection to your databases on the server is necessary and at least read access to the retrieved data. But apart from this, your newly built Excel report is fully functional for ad-hoc analysis and can be used in the common way for drilling, pivoting and all the other known functions and features. So far about embedding Dynamic Data Points into Office documents and linking them back into Excel worksheets. You can apply this in the described way with ad-hoc analyses directly on Essbase databases or using Hyperion Planning and Hyperion Financial Management ad-hoc web forms. If you are also interested in other new features and smart enhancements in Essbase or Hyperion Planning stay tuned for coming articles or check our training courses and web presentations. You can find general information about offerings for the Essbase and Planning curriculum or other Oracle-Hyperion products here (please make sure to select your country/region at the top of this page) or in the OU Learning paths section , where Planning, Essbase and other Hyperion products can be found under the Fusion Middleware heading (again, please select the right country/region). Or drop me a note directly: [email protected] . About the Author: Bernhard Kinkel started working for Hyperion Solutions as a Presales Consultant and Consultant in 1998 and moved to Hyperion Education Services in 1999. He joined Oracle University in 2007 where he is a Principal Education Consultant. Based on these many years of working with Hyperion products he has detailed product knowledge across several versions. He delivers both classroom and live virtual courses. His areas of expertise are Oracle/Hyperion Essbase, Oracle Hyperion Planning and Hyperion Web Analysis.  

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  • EPM 11.1.2.2 Architecture: Financial Performance Management Applications

    - by Marc Schumacher
     Financial Management can be accessed either by a browser based client or by SmartView. Starting from release 11.1.2.2, the Financial Management Windows client does not longer access the Financial Management Consolidation server. All tasks that require an on line connection (e.g. load and extract tasks) can only be done using the web interface. Any client connection initiated by a browser or SmartView is send to the Oracle HTTP server (OHS) first. Based on the path given (e.g. hfmadf, hfmofficeprovider) in the URL, OHS makes a decision to forward this request either to the new Financial Management web application based on the Oracle Application Development Framework (ADF) or to the .NET based application serving SmartView retrievals running on Internet Information Server (IIS). Any requests send to the ADF web interface that need to be processed by the Financial Management application server are send to the IIS using HTTP protocol and will be forwarded further using DCOM to the Financial Management application server. SmartView requests, which are processes by IIS in first row, are forwarded to the Financial Management application server using DCOM as well. The Financial Management Application Server uses OLE DB database connections via native database clients to talk to the Financial Management database schema. Communication between the Financial Management DME Listener, which handles requests from EPMA, and the Financial Management application server is based on DCOM.  Unlike most other components Essbase Analytics Link (EAL) does not have an end user interface. The only user interface is a plug-in for the Essbase Administration Services console, which is used for administration purposes only. End users interact with a Transparent or Replicated Partition that is created in Essbase and populated with data by EAL. The Analytics Link Server deployed on WebLogic communicates through HTTP protocol with the Analytics Link Financial Management Connector that is deployed in IIS on the Financial Management web server. Analytics Link Server interacts with the Data Synchronisation server using the EAL API. The Data Synchronization server acts as a target of a Transparent or Replicated Partition in Essbase and uses a native database client to connect to the Financial Management database. Analytics Link Server uses JDBC to connect to relational repository databases and Essbase JAPI to connect to Essbase.  As most Oracle EPM System products, browser based clients and SmartView can be used to access Planning. The Java based Planning web application is deployed on WebLogic, which is configured behind an Oracle HTTP Server (OHS). Communication between Planning and the Planning RMI Registry Service is done using Java Remote Message Invocation (RMI). Planning uses JDBC to access relational repository databases and talks to Essbase using the CAPI. Be aware of the fact that beside the Planning System database a dedicated database schema is needed for each application that is set up within Planning.  As Planning, Profitability and Cost Management (HPCM) has a pretty simple architecture. Beside the browser based clients and SmartView, a web service consumer can be used as a client too. All clients access the Java based web application deployed on WebLogic through Oracle HHTP Server (OHS). Communication between Profitability and Cost Management and EPMA Web Server is done using HTTP protocol. JDBC is used to access the relational repository databases as well as data sources. Essbase JAPI is utilized to talk to Essbase.  For Strategic Finance, two clients exist, SmartView and a Windows client. While SmartView communicates through the web layer to the Strategic Finance Server, Strategic Finance Windows client makes a direct connection to the Strategic Finance Server using RPC calls. Connections from Strategic Finance Web as well as from Strategic Finance Web Services to the Strategic Finance Server are made using RPC calls too. The Strategic Finance Server uses its own file based data store. JDBC is used to connect to the EPM System Registry from web and application layer.  Disclosure Management has three kinds of clients. While the browser based client and SmartView interact with the Disclosure Management web application directly through Oracle HTTP Server (OHS), Taxonomy Designer does not connect to the Disclosure Management server. Communication to relational repository databases is done via JDBC, to connect to Essbase the Essbase JAPI is utilized.

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  • Data Management Business Continuity Planning

    Business Continuity Governance In order to ensure data continuity for an organization, they need to ensure they know how to handle a data or network emergency because all systems have the potential to fail. Data Continuity Checklist: Disaster Recovery Plan/Policy Backups Redundancy Trained Staff Business Continuity Policies In order to protect data in case of any emergency a company needs to put in place a Disaster recovery plan and policies that can be executed by IT staff to ensure the continuity of the existing data and/or limit the amount of data that is not contiguous.  A disaster recovery plan is a comprehensive statement of consistent actions to be taken before, during and after a disaster, according to Geoffrey H. Wold. He also states that the primary objective of disaster recovery planning is to protect the organization in the event that all or parts of its operations and/or computer services are rendered unusable. Furthermore, companies can mandate through policies that IT must maintain redundant hardware in case of any hardware failures and redundant network connectivity incase the primary internet service provider goes down.  Additionally, they can require that all staff be trained in regards to the Disaster recovery policy to ensure that all parties evolved are knowledgeable to execute the recovery plan. Business Continuity Procedures Business continuity procedure vary from organization to origination, however there are standard procedures that most originations should follow. Standard Business Continuity Procedures Backup and Test Backups to ensure that they work Hire knowledgeable and trainable staff  Offer training on new and existing systems Regularly monitor, test, maintain, and upgrade existing system hardware and applications Maintain redundancy regarding all data, and critical business functionality

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  • Why Cornell University Chose Oracle Data Masking

    - by Troy Kitch
    One of the eight Ivy League schools, Cornell University found itself in the unfortunate position of having to inform over 45,000 University community members that their personal information had been breached when a laptop was stolen. To ensure this wouldn’t happen again, Cornell took steps to ensure that data used for non-production purposes is de-identified with Oracle Data Masking. A recent podcast highlights why organizations like Cornell are choosing Oracle Data Masking to irreversibly de-identify production data for use in non-production environments. Organizations often copy production data, that contains sensitive information, into non-production environments so they can test applications and systems using “real world” information. Data in non-production has increasingly become a target of cyber criminals and can be lost or stolen due to weak security controls and unmonitored access. Similar to production environments, data breaches in non-production environments can cost millions of dollars to remediate and cause irreparable harm to reputation and brand. Cornell’s applications and databases help carry out the administrative and academic mission of the university. They are running Oracle PeopleSoft Campus Solutions that include highly sensitive faculty, student, alumni, and prospective student data. This data is supported and accessed by a diverse set of developers and functional staff distributed across the university. Several years ago, Cornell experienced a data breach when an employee’s laptop was stolen.  Centrally stored backup information indicated there was sensitive data on the laptop. With no way of knowing what the criminal intended, the university had to spend significant resources reviewing data, setting up service centers to handle constituent concerns, and provide free credit checks and identity theft protection services—all of which cost money and took time away from other projects. To avoid this issue in the future Cornell came up with several options; one of which was to sanitize the testing and training environments. “The project management team was brought in and they developed a project plan and implementation schedule; part of which was to evaluate competing products in the market-space and figure out which one would work best for us.  In the end we chose Oracle’s solution based on its architecture and its functionality.” – Tony Damiani, Database Administration and Business Intelligence, Cornell University The key goals of the project were to mask the elements that were identifiable as sensitive in a consistent and efficient manner, but still support all the previous activities in the non-production environments. Tony concludes,  “What we saw was a very minimal impact on performance. The masking process added an additional three hours to our refresh window, but it was well worth that time to secure the environment and remove the sensitive data. I think some other key points you can keep in mind here is that there was zero impact on the production environment. Oracle Data Masking works in non-production environments only. Additionally, the risk of exposure has been significantly reduced and the impact to business was minimal.” With Oracle Data Masking organizations like Cornell can: Make application data securely available in non-production environments Prevent application developers and testers from seeing production data Use an extensible template library and policies for data masking automation Gain the benefits of referential integrity so that applications continue to work Listen to the podcast to hear the complete interview.  Learn more about Oracle Data Masking by registering to watch this SANS Institute Webcast and view this short demo.

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  • Removing Barriers to Create Effective Data Models

    After years of creating and maintaining data models, I have started to notice common barriers that decrease the accuracy and usefulness of models. In my opinion, the main causes of these barriers are the lack of knowledge and communication from within a company. The lack of knowledge in regards to data models or data modeling can take many forms. Company Culture Knowledge Whether documented or undocumented, existing business rules of a company can affect how data is modeled. For example, if a company only allows 1 assigned person per customer to be able to manipulate a customer’s record then then a data model that includes an associated table that joins customers and employee’s would be unneeded because that would allow for the possibility of multiple employees to handle a customer because of the potential for a many to many relationship between Customers and Employees. Technical Knowledge Depending on the data modeler’s proficiency in modeling data they can inadvertently cause issues and/or complications with a design without even noticing. It is important that companies share data modeling responsibilities so that the models are developed from multiple perspectives of a system, company and the original problem.  In addition, the tools that a company selects to create data models can also affect the accuracy of the model if designer are not familiar with the tools or the tools are too complex to use for the designer. Existing System Knowledge In order for a data modeler to model data for an existing system so that new changes can be applied to a system then they need to at least know the basic concepts of a system so that they can work within it. This will promote reusability of data and prevent the chance of duplicating data. Project Knowledge This should be pretty obvious, but it is very hard to create an accurate data model without knowing what data needs to be modeled. I have always found it strange that I have been asked to start modeling data prior to a client formalizing any requirements. Usually when this happens I have to make several iterations to a model, and the client still does not know exactly what they want.  In addition additional issues can arise when certain stakeholders of a project are not consulted prior to the design or after the project is over because it can cause miss understandings and confusion by the end user as well as possibly not solving the original problem for which a project is intended to solve. One common thread between each type of knowledge is that they can all be avoided through the use of good communication. For example, if a modeler is new to a company then they should ask older employees about any business specific rules that may be documented or undocumented that must be applied to projects in general. Furthermore, if a modeler is not really familiar with a specific data modeling software then they need to speak up and ask for help form other employees or their manager. This will not only help the modeler in the project, but also help them in future projects that they do for the company. Additionally, if a project is not clearly defined prior to a data modeler being assigned the modeling project then it is their responsibility to communicate with the other stakeholders to clarify any part of a project that is unclear so that the data model that is created is accurately aligned with a project.

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  • How often do you use data structures (ie Binary Trees, Linked Lists) in your jobs/side projects?

    - by Chris2021
    It seems to me that, for everyday use, more primitive data structures like arrays get the job done just as well as a binary tree would. My question is how common is to use these structures when writing code for projects at work or projects that you pursue in your free time? I understand the better insertion time/deletion time/sorting time for certain structures but would that really matter that much if you were working with a relatively small amount of data?

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  • UPMC Picks Oracle Identity Management

    - by Naresh Persaud
    UPMC, a $10-billion integrated global health enterprise, has selected Oracle as a key technology partner in UPMC’s $100-million analytics initiative designed to help “unlock the secrets of human health and disease” by consolidating and analyzing data from 200 separate sources across UPMC’s far-flung network.As part of the project UPMC also selected Oracle Identity Management to secure the interaction and insure regulatory compliance. Read complete article here. As healthcare organizations create new services on-line to provide better care Identity Management can provide a foundation for collaboration.

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  • Latest Fusion DOO White Paper - Overcoming Order Management Complexity in Global Organizations

    - by Pam Petropoulos
    Check out this latest Fusion Distributed Order Orchestration white paper entitled “Overcoming Order Management Complexity in Global Organizations”.  Discover how Oracle Fusion DOO enables large, complex organizations to streamline their order management processes and take advantage of lower costs, higher margins, and improved customer service. Click here to read the whitepaper.

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  • Why would you use data structures (ie Binary Trees, Linked Lists) in your jobs/side projects? [closed]

    - by Chris2021
    It seems to me that, for everyday use, more primitive data structures like arrays get the job done just as well as a binary tree would. My question is how common is to use these structures when writing code for projects at work or projects that you pursue in your free time? I understand the better insertion time/deletion time/sorting time for certain structures but would that really matter that much if you were working with a relatively small amount of data?

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  • Queued Loadtest to remove Concurrency issues using Shared Data Service in OpenScript

    - by stefan.thieme(at)oracle.com
    Queued Processing to remove Concurrency issues in Loadtest ScriptsSome scripts act on information returned by the server, e.g. act on first item in the returned list of pending tasks/actions. This may lead to concurrency issues if the virtual users simulated in a load test scenario are not synchronized in some way.As the load test cases should be carried out in a comparable and straight forward manner simply cancel a transaction in case a collision occurs is clearly not an option. In case you increase the number of virtual users this approach would lead to a high number of requests for the early steps in your transaction (e.g. login, retrieve list of action points, assign an action point to the virtual user) but later steps would be rarely visited successfully or at all, depending on the application logic.A way to tackle this problem is to enqueue the virtual users in a Shared Data Service queue. Only the first virtual user in this queue will be allowed to carry out the critical steps (retrieve list of action points, assign an action point to the virtual user) in your transaction at any one time.Once a virtual user has passed the critical path it will dequeue himself from the head of the queue and continue with his actions. This does theoretically allow virtual users to run in parallel all steps of the transaction which are not part of the critical path.In practice it has been seen this is rarely the case, though it does not allow adding more than N users to perform a transaction without causing delays due to virtual users waiting in the queue. N being the time of the total transaction divided by the sum of the time of all critical steps in this transaction.While this problem can be circumvented by allowing multiple queues to act on individual segments of the list of actions, e.g. per country filter, ends with 0..9 filter, etc.This would require additional handling of these additional queues of slots for the virtual users at the head of the queue in order to maintain the mutually exclusive access to the first element in the list returned by the server at any one time of the load test. Such an improved handling of multiple queues and/or multiple slots is above the subject of this paper.Shared Data Services Pre-RequisitesStart WebLogic Server to host Shared Data ServicesYou will have to make sure that your WebLogic server is installed and started. Shared Data Services may not work if you installed only the minimal installation package for OpenScript. If however you installed the default package including OLT and OTM, you may follow the instructions below to start and verify WebLogic installation.To start the WebLogic Server deployed underneath of Oracle Load Testing and/or Oracle Test Manager you can go to your Start menu, Oracle Application Testing Suite and select the Restart Oracle Application Testing Suite Application Service entry from the Tools submenu.To verify the service has been started you can run the Microsoft Management Console for Services by Selecting Run from the Start Menu and entering services.msc. Look for the entry that reads Oracle Application Testing Suite Application Service, once it has changed it status from Starting to Started you can proceed to verify the login. Please note that this may take several minutes, I would say up to 10 minutes depending on the strength of your CPU horse-power.Verify WebLogic Server user credentialsYou will have to make sure that your WebLogic Server is installed and started. Next open the Oracle WebLogic Server Adminstration Console on http://localhost:8088/console.It may take a while until the application is deployed and started. It may display the following until the Administration Console has been deployed on the fly.Afterwards you can login using the username oats and the password that you selected during install time for your Application Testing Suite administrative purposes.This will bring up the Home page of you WebLogic Server. You have actually verified that you are able to login with these credentials already. However if you want to check the details, navigate to Security Realms, myrealm, Users and Groups tab.Here you could add users to your WebLogic Server which could be used in the later steps. Details on the Groups required for such a custom user to work are exceeding this quick overview and have to be selected with the WebLogic Server Adminstration Guide in mind.Shared Data Services pre-requisites for Load testingOpenScript Preferences have to be set to enable Encryption and provide a default Shared Data Service Connection for Playback.These are pre-requisites you want to use for load testing with Shared Data Services.Please note that the usage of the Connection Parameters (individual directive in the script) for Shared Data Services did not playback reliably in the current version 9.20.0370 of Oracle Load Testing (OLT) and encryption of credentials still seemed to be mandatory as well.General Encryption settingsSelect OpenScript Preferences from the View menu and navigate to the General, Encryption entry in the tree on the left. Select the Encrypt script data option from the list and enter the same password that you used for securing your WebLogic Server Administration Console.Enable global shared data access credentialsSelect OpenScript Preferences from the View menu and navigate to the Playback, Shared Data entry in the tree on the left. Enable the global shared data access credentials and enter the Address, User name and Password determined for your WebLogic Server to host Shared Data Services.Please note, that you may want to replace the localhost in Address with the hosts realname in case you plan to run load tests with Loadtest Agents running on remote systems.Queued Processing of TransactionsEnable Shared Data Services Module in Script PropertiesThe Shared Data Services Module has to be enabled for each Script that wants to employ the Shared Data Service Queue functionality in OpenScript. It can be enabled under the Script menu selecting Script Properties. On the Script Properties Dialog select the Modules section and check Shared Data to enable Shared Data Service Module for your script. Checking the Shared Data Services option will effectively add a line to your script code that adds the sharedData ScriptService to your script class of IteratingVUserScript.@ScriptService oracle.oats.scripting.modules.sharedData.api.SharedDataService sharedData;Record your scriptRecord your script as usual and then add the following things for Queue handling in the Initialize code block, before the first step and after the last step of your critical path and in the Finalize code block.The java code to be added at individual locations is explained in the following sections in full detail.Create a Shared Data Queue in InitializeTo create a Shared Data Queue go to the Java view of your script and enter the following statements to the initialize() code block.info("Create queueA with life time of 120 minutes");sharedData.createQueue("queueA", 120);This will create an instantiation of the Shared Data Queue object named queueA which is maintained for upto 120 minutes.If you want to use the code for multiple scripts, make sure to use a different queue name for each one here and in the subsequent steps. You may even consider to use a dynamic queueName based on filters of your result list being concurrently accessed.Prepare a unique id for each IterationIn order to keep track of individual virtual users in our queue we need to create a unique identifier from the virtual user id and the used username right after retrieving the next record from our databank file.getDatabank("Usernames").getNextDatabankRecord();getVariables().set("usernameValue1","VU_{{@vuid}}_{{@iterationnum}}_{{db.Usernames.Username}}_{{@timestamp}}_{{@random(10000)}}");String usernameValue = getVariables().get("usernameValue1");info("Now running virtual user " + usernameValue);As you can see from the above code block, we have set the OpenScript variable usernameValue1 to VU_{{@vuid}}_{{@iterationnum}}_{{db.Usernames.Username}}_{{@timestamp}}_{{@random(10000)}} which is a concatenation of the virtual user id and the iterationnumber for general uniqueness; as well as the username from our databank, the timestamp and a random number for making it further unique and ease spotting of errors.Not all of these fields are actually required to make it really unique, but adding the queue name may also be considered to help troubleshoot multiple queues.The value is then retrieved with the getVariables.get() method call and assigned to the usernameValue String used throughout the script.Please note that moving the getDatabank("Usernames").getNextDatabankRecord(); call to the initialize block was later considered to remove concurrency of multiple virtual users running with the same userid and therefor accessing the same "My Inbox" in step 6. This will effectively give each virtual user a userid from the databank file. Make sure you have enough userids to remove this second hurdle.Enqueue and attend Queue before Critical PathTo maintain the right order of virtual users being allowed into the critical path of the transaction the following pseudo step has to be added in front of the first critical step. In the case of this example this is right in front of the step where we retrieve the list of actions from which we select the first to be assigned to us.beginStep("[0] Waiting in the Queue", 0);{info("Enqueued virtual user " + usernameValue + " at the end of queueA");sharedData.offerLast("queueA", usernameValue);info("Wait until the user is the first in queueA");String queueValue1 = null;do {// we wait for at least 0.7 seconds before we check the head of the// queue. This is the time it takes one user to move through the// critical path, i.e. pass steps [5] Enter country and [6] Assign// to meThread.sleep(700);queueValue1 = (String) sharedData.peekFirst("queueA");info("The first user in queueA is currently: '" + queueValue1 + "' " + queueValue1.getClass() + " length " + queueValue1.length() );info("The current user is '"+ usernameValue + "' " + usernameValue.getClass() + " length " + usernameValue.length() + ": indexOf " + usernameValue.indexOf(queueValue1) + " equals " + usernameValue.equals(queueValue1) );} while ( queueValue1.indexOf(usernameValue) < 0 );info("Now the user is the first in queueA");}endStep();This will enqueue the username to the tail of our Queue. It will will wait for at least 700 milliseconds, the time it takes for one user to exit the critical path and then compare the head of our queue with it's username. This last step will be repeated while the two are not equal (indexOf less than zero). If they are equal the indexOf will yield a value of zero or larger and we will perform the critical steps.Dequeue after Critical PathAfter the virtual user has left the critical path and complete its last step the following code block needs to dequeue the virtual user. In the case of our example this is right after the action has been actually assigned to the virtual user. This will allow the next virtual user to retrieve the list of actions still available and in turn let him make his selection/assignment.info("Get and remove the current user from the head of queueA");String pollValue1 = (String) sharedData.pollFirst("queueA");The current user is removed from the head of the queue. The next one will now be able to match his username against the head of the queue.Clear and Destroy Queue for FinishWhen the script has completed, it should clear and destroy the queue. This code block can be put in the finish block of your script and/or in a separate script in order to clear and remove the queue in case you have spotted an error or want to reset the queue for some reason.info("Clear queueA");sharedData.clearQueue("queueA");info("Destroy queueA");sharedData.destroyQueue("queueA");The users waiting in queueA are cleared and the queue is destroyed. If you have scripts still executing they will be caught in a loop.I found it better to maintain a separate Reset Queue script which contained only the following code in the initialize() block. I use to call this script to make sure the queue is cleared in between multiple Loadtest runs. This script could also even be added as the first in a larger scenario, which would execute it only once at very start of the Loadtest and make sure the queues do not contain any stale entries.info("Create queueA with life time of 120 minutes");sharedData.createQueue("queueA", 120);info("Clear queueA");sharedData.clearQueue("queueA");This will create a Shared Data Queue instance of queueA and clear all entries from this queue.Monitoring QueueWhile creating the scripts it was useful to monitor the contents, i.e. the current first user in the Queue. The following code block will make sure the Shared Data Queue is accessible in the initialize() block.info("Create queueA with life time of 120 minutes");sharedData.createQueue("queueA", 120);In the run() block the following code will continuously monitor the first element of the Queue and write an informational message with the current username Value to the Result window.info("Monitor the first users in queueA");String queueValue1 = null;do {queueValue1 = (String) sharedData.peekFirst("queueA");if (queueValue1 != null)info("The first user in queueA is currently: '" + queueValue1 + "' " + queueValue1.getClass() + " length " + queueValue1.length() );} while ( true );This script can be run from OpenScript parallel to a loadtest performed by the Oracle Load Test.However it is not recommend to run this in a production loadtest as the performance impact is unknown. Accessing the Queue's head with the peekFirst() method has been reported with about 2 seconds response time by both OpenScript and OTL. It is advised to log a Service Request to see if this could be lowered in future releases of Application Testing Suite, as the pollFirst() and even offerLast() writing to the tail of the Queue usually returned after an average 0.1 seconds.Debugging QueueWhile debugging the scripts the following was useful to remove single entries from its head, i.e. the current first user in the Queue. The following code block will make sure the Shared Data Queue is accessible in the initialize() block.info("Create queueA with life time of 120 minutes");sharedData.createQueue("queueA", 120);In the run() block the following code will remove the first element of the Queue and write an informational message with the current username Value to the Result window.info("Get and remove the current user from the head of queueA");String pollValue1 = (String) sharedData.pollFirst("queueA");info("The first user in queueA was currently: '" + pollValue1 + "' " + pollValue1.getClass() + " length " + pollValue1.length() );ReferencesOracle Functional Testing OpenScript User's Guide Version 9.20 [E15488-05]Chapter 17 Using the Shared Data Modulehttp://download.oracle.com/otn/nt/apptesting/oats-docs-9.21.0030.zipOracle Fusion Middleware Oracle WebLogic Server Administration Console Online Help 11g Release 1 (10.3.4) [E13952-04]Administration Console Online Help - Manage users and groupshttp://download.oracle.com/docs/cd/E17904_01/apirefs.1111/e13952/taskhelp/security/ManageUsersAndGroups.htm

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  • New version of SQL Server Data Tools is now available

    - by jamiet
    If you don’t follow the SQL Server Data Tools (SSDT) blog then you may not know that two days ago an updated version of SSDT was released (and by SSDT I mean the database projects, not the SSIS/SSRS/SSAS stuff) along with a new version of the SSDT Power Tools. This release incorporates a an updated version of the SQL Server Data Tier Application Framework (aka DAC Framework, aka DacFX) which you can read about on Adam Mahood’s blog post SQL Server Data-Tier Application Framework (September 2012) Available. DacFX is essentially all the gubbins that you need to extract and publish .dacpacs and according to Adam’s post it incorporates a new feature that I think is very interesting indeed: Extract DACPAC with data – Creates a database snapshot file (.dacpac) from a live SQL Server or Windows Azure SQL Database that contains data from user tables in addition to the database schema. These packages can be published to a new or existing SQL Server or Windows Azure SQL Database using the SqlPackage.exe Publish action. Data contained in package replaces the existing data in the target database. In short, .dacpacs can now include data as well as schema. I’m very excited about this because one of my long-standing complaints about SSDT (and its many forebears) is that whilst it has great support for declarative development of schema it does not provide anything similar for data – if you want to deploy data from your SSDT projects then you have to write Post-Deployment MERGE scripts. This new feature for .dacpacs does not change that situation yet however it is a very important pre-requisite so I am hoping that a feature to provide declaration of data (in addition to declaration of schema which we have today) is going to light up in SSDT in the not too distant future. Read more about the latest SSDT, Power Tools & DacFX releases at: Now available: SQL Server Data Tools - September 2012 update! by Janet Yeilding New SSDT Power Tools! Now for both Visual Studio 2010 and Visual Studio 2012 by Sarah McDevitt SQL Server Data-Tier Application Framework (September 2012) Available by Adam Mahood @Jamiet

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  • The Ins and Outs of Effective Smart Grid Data Management

    - by caroline.yu
    Oracle Utilities and Accenture recently sponsored a one-hour Web cast entitled, "The Ins and Outs of Effective Smart Grid Data Management." Oracle and Accenture created this Web cast to help utilities better understand the types of data collected over smart grid networks and the issues associated with mapping out a coherent information management strategy. The Web cast also addressed important points that utilities must consider with the imminent flood of data that both present and next-generation smart grid components will generate. The three speakers, including Oracle Utilities' Brad Williams, focused on the key factors associated with taking the millions of data points captured in real time and implementing the strategies, frameworks and technologies that enable utilities to process, store, analyze, visualize, integrate, transport and transform data into the information required to deliver targeted business benefits. The Web cast replay is available here. The Web cast slides are available here.

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  • How Oracle Data Integration Customers Differentiate Their Business in Competitive Markets

    - by Irem Radzik
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 With data being a central force in driving innovation and competing effectively, data integration has become a key IT approach to remove silos and ensure working with consistent and trusted data. Especially with the release of 12c version, Oracle Data Integrator and Oracle GoldenGate offer easy-to-use and high-performance solutions that help companies with their critical data initiatives, including big data analytics, moving to cloud architectures, modernizing and connecting transactional systems and more. In a recent press release we announced the great momentum and analyst recognition Oracle Data Integration products have achieved in the data integration and replication market. In this press release we described some of the key new features of Oracle Data Integrator 12c and Oracle GoldenGate 12c. In addition, a few from our 4500+ customers explained how Oracle’s data integration platform helped them achieve their business goals. In this blog post I would like to go over what these customers shared about their experience. Land O’Lakes is one of America’s premier member-owned cooperatives, and offers an extensive line of agricultural supplies, as well as production and business services. Rich Bellefeuille, manager, ETL & data warehouse for Land O’Lakes told us how GoldenGate helped them modernize their critical ERP system without impacting service and how they are moving to new projects with Oracle Data Integrator 12c: “With Oracle GoldenGate 11g, we've been able to migrate our enterprise-wide implementation of Oracle’s JD Edwards EnterpriseOne, ERP system, to a new database and application server platform with minimal downtime to our business. Using Oracle GoldenGate 11g we reduced database migration time from nearly 30 hours to less than 30 minutes. Given our quick success, we are considering expansion of our Oracle GoldenGate 12c footprint. We are also in the midst of deploying a solution leveraging Oracle Data Integrator 12c to manage our pricing data to handle orders more effectively and provide a better relationship with our clients. We feel we are gaining higher productivity and flexibility with Oracle's data integration products." ICON, a global provider of outsourced development services to the pharmaceutical, biotechnology and medical device industries, highlighted the competitive advantage that a solid data integration foundation brings. Diarmaid O’Reilly, enterprise data warehouse manager, ICON plc said “Oracle Data Integrator enables us to align clinical trials intelligence with the information needs of our sponsors. It helps differentiate ICON’s services in an increasingly competitive drug-development industry."  You can find more info on ICON's implementation here. A popular use case for Oracle GoldenGate’s real-time data integration is offloading operational reporting from critical transaction processing systems. SolarWorld, one of the world’s largest solar-technology producers and the largest U.S. solar panel manufacturer, implemented Oracle GoldenGate for real-time data integration of manufacturing data for fast analysis. Russ Toyama, U.S. senior database administrator for SolarWorld told us real-time data helps their operations and GoldenGate’s solution supports high performance of their manufacturing systems: “We use Oracle GoldenGate for real-time data integration into our decision support system, which performs real-time analysis for manufacturing operations to continuously improve product quality, yield and efficiency. With reliable and low-impact data movement capabilities, Oracle GoldenGate also helps ensure that our critical manufacturing systems are stable and operate with high performance."  You can watch the full interview with SolarWorld's Russ Toyama here. Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* 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-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Starwood Hotels and Resorts is one of the many customers that found out how well Oracle Data Integration products work with Oracle Exadata. Gordon Light, senior director of information technology for StarWood Hotels, says they had notable performance gain in loading Oracle Exadata reporting environment: “We leverage Oracle GoldenGate to replicate data from our central reservations systems and other OLTP databases – significantly decreasing the overall ETL duration. Moving forward, we plan to use Oracle GoldenGate to help the company achieve near-real-time reporting.”You can listen about Starwood Hotels' implementation here. Many companies combine the power of Oracle GoldenGate with Oracle Data Integrator to have a single, integrated data integration platform for variety of use cases across the enterprise. Ufone is another good example of that. The leading mobile communications service provider of Pakistan has improved customer service using timely customer data in its data warehouse. Atif Aslam, head of management information systems for Ufone says: “Oracle Data Integrator and Oracle GoldenGate help us integrate information from various systems and provide up-to-date and real-time CRM data updates hourly, rather than daily. The applications have simplified data warehouse operations and allowed business users to make faster and better informed decisions to protect revenue in the fast-moving Pakistani telecommunications market.” You can read more about Ufone's use case here. In our Oracle Data Integration 12c launch webcast back in November we also heard from BT’s CTO Surren Parthab about their use of GoldenGate for moving to private cloud architecture. Surren also shared his perspectives on Oracle Data Integrator 12c and Oracle GoldenGate 12c releases. You can watch the video here. These are only a few examples of leading companies that have made data integration and real-time data access a key part of their data governance and IT modernization initiatives. They have seen real improvements in how their businesses operate and differentiate in today’s competitive markets. You can read about other customer examples in our Ebook: The Path to the Future and access resources including white papers, data sheets, podcasts and more via our Oracle Data Integration resource kit. /* 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-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}

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  • SQL SERVER – Standard Reports from SQL Server Management Studio – SQL in Sixty Seconds #016 – Video

    - by pinaldave
    SQL Server management Studio 2012 is wonderful tool and has many different features. Many times, an average user does not use them as they are not aware about these features. Today, we will learn one such feature. SSMS comes with many inbuilt performance and activity reports, but we do not use it to the full potential. Connect to SQL Server Node >> Right Click on it >> Go to Reports >> Click on Standard Reports >> Pick Any Report. Please note that some of the reports can be IO intensive and not suggested to run during business hours! More on Standard Reports: SQL SERVER – Out of the Box – Activity and Performance Reports from SSSMS SQL SERVER – Generate Report for Index Physical Statistics – SSMS SQL SERVER – Configure Management Data Collection in Quick Steps I encourage you to submit your ideas for SQL in Sixty Seconds. We will try to accommodate as many as we can. If we like your idea we promise to share with you educational material. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Database, Pinal Dave, PostADay, SQL, SQL Authority, SQL in Sixty Seconds, SQL Query, SQL Scripts, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL, Technology, Video

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