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• What's Happening in Business Analytics at OpenWorld 2012?

  - by jmorourke

  Oracle OpenWorld 2012 is rapidly approaching on September 30th when we take over the city of San Francisco for five days.  The Business Analytics this year is our strongest ever with over 150 EPM, BI, Analytics and Data Warehousing sessions delivered by Oracle, our customers and partners.  We’ll also have Hands-On Labs, 20 demo pods dedicated to Business Analytics products, and over 30 partners exhibiting their solutions.  So what’s hot in the Business Analytics program at OpenWorld?  Here are some of the “can’t miss” sessions at this year’s conference: The EPM and BI general sessions, led by SVP of Product Development Balaji Yelamanchili will highlight what’s new provide a view into Oracle’s EPM, BI and Analytics strategies.  Both sessions are scheduled on Monday, October 1st. Thursday Keynote:  See More, Act Faster:  Oracle Business Analytics, led by Oracle President Mark Hurd, will provide a view into Oracle’s strategy for Business Analytics, especially engineered systems designed to provide extreme performance for the most rigorous analytic tasks. Superfast Business Intelligence with Oracle Exalytics.  Hear about various business intelligence scenarios in which Oracle Exalytics provides exemplary value—from operational reporting and prepackaged applications to analytics on unstructured data. Turn Insights into Real-Time Actions with Oracle Business Intelligence Mobile.  Learn how Oracle Business Intelligence Mobile enables organizations to deliver relevant information and turn insight into real-time action, no matter where employees are located. Empowering the Business User: Introduction to Oracle Endeca Information Discovery.  Find out how you can find fast answers to the new questions that confront your business every day, while avoiding the confusion and inconsistencies brought about by spreadsheets and desktop tools. Big Data:  The Big Story.  Learn how to harness big data, your existing data, and predictive analytics to make better decisions in an environment of rapid shifts in behavior and instant feedback.  Learn about the technologies that constitute a big data architecture, how to leverage and implement advanced analytics for real-time decisions, and the tools needed to know the unknown. Planning at the Speed of Business with Oracle Exalytics.  Learn how Oracle Hyperion Planning leverages the power of Oracle Exalytics to do planning faster, with more detail and more users than ever. For more details on these and other Business Analytics sessions at OpenWorld, download the Focus On Business Analytics program guide at:  http://www.oracle.com/openworld/focus-on/index.html We look forward to seeing you in San Francisco!

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• how did Google Analytics kill my site?

  - by user1813359

  Yesterday I created a google analytics profile for one of my sites and included the JS block in the layout template. What happened next was very strange. Within about 2 minutes, the site had become unreachable. I had been checking the AWStats page for the site when I thought to set up GA. After that had been done, I clicked on the link for 404 stats, which opens in a new tab. It churned for a long while and then showed a nearly blank page, similar to that when Firefox chokes on a badly-formatted XML page, except there was no error msg. But i was logged into the server and could see that that page has a 401 Transitional DTD. Strange! I tried viewing source but it just churned endlessly. I then tried "inspect element" and was able to see an error msg having to do with some internal Firefox lib. Unfortunately, i neglected to copy that. :-( All further attempts to load anything on the site would time out. Firebug's Net panel showed no request being made. Chrome would time out. So, I deleted the GA profile, removed the JS block, and cleared the server cache. No joy. I then removed all google cookies and disabled JS. Still nothing. No luck in any other browser. And now my client couldn't access the site. Terrific. I was able use wget while logged into another server. The retrieved page was fine, and did not contain the GA JS block. However, the two servers are on the same network. (Perhaps a clue.) The server itself was fine. Ping, traceroute looked great. I could SSH in. I tailed the access log and tried a browser request. Nothing. But i forgot to quit and a minute or so later I saw a request from someone else being logged. Later, I could see that requests had been served all day to some people. Now, 24 hours later, the site works once again, but is still unreachable by the client (who is in another city). So, does anyone have some insight into what's going on? Does this have something to do with google's CDN? I don't know very much about how GA works but what I'm seeing reminds me of DNS propagation issues. And why the initial XML error? And why the heck was the site just plain unreachable? What did google do to my site?! Sorry for the length but I wanted to cover everything.

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• Google Analytics Request URI to Event advanced filter

  - by confidentjohn

  I have a query string attached to a Request URI. Whilst I can see this data within the pages report and it works, I was thinking about setting up an advanced filter to convert the request URI to an Event, with the hope this would clean up my pages report and sit this query with related events in my data. I can see in advanced filters that this is possible, but seems limited to specifying a single event area, so Cat, action or Label, not all 3. Does any one know how I could set up an advanced filter to find any URIs that contain a specific query string, say example below. www.example.com?querystring=123 and convert this into an event, where I can set the Cat, action and label.

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• Are there any open-source / free site analytics solutions that are intranet deployable?

  - by Richard Nichols

  There are plenty of statistics/analytics providers for Internet deployed software (e.g. Google Analytics), but I'm looking for an analytics tool to integrate into a LAN/intranet based web application. I'm aware of AWStats, but I'd prefer something with a design similar to Google Analytics, where a Javascript callback can be embedded into the app and call back to an analytics server. This doesn't require any sort of extra application server configuration and access to run. I'm thinking there's nothing available that isn't proprietary / pay-for, but I'd love to be told I'm wrong!

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• How do I prove to a client/advertiser that my site's analytics numbers are what I say they are?

  - by Bryson

  I have been asked to provide recommendations on "Verified Analytics" for the next iteration of my company's site. Verified to mean that when we sell ad space, it's based on a number of page-views, and the people who buy that space want a way to verify that the numbers we give them are the actual numbers we're delivering. I have turned to The Google and the only services I can find for this sort of thing revolve around Google Analytics and the sale of a domain name. I export my analytics numbers to a PDF, have Google email the PDF to my auctioneer, and they look for signs of tampering. If no signs of tampering are found they put a little "Verified" badge on the domain auction. (Here) Other than this, and something similar on another domain sales site, I haven't found anything like what I've been asked to find. Currently we are using Google Analytics, however I've been also asked to recommend a replacement for that based on the ability to be verified. I'd rather just stick with Google Analytics since we also use Google for advertising.

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• Reassessment: What's a good analytics package to use for tracking user behavior in a native iOS app?

  - by BeachRunnerJoe

  Hello. I've been poking around google and SO for answers on this, but it doesn't seem to be very well discussed, so I thought I revisit the question. Is anyone using any analytics packages (like Google Analytics or Mixpanel) to track user behavior in their native iOS apps? The three I've come across are Flurry, Mixpanel, and Google Analytics. It sounds like Apple is still peeved at Flurry, so I don't want to mess with that. Mixpanel looks simple and easy to use, but I'd first like to hear from someone who has used it. Same goes with Google Analytics for the iPhone. I've just finished building an iPhone game and I'd like to begin tweaking it based on how the users are playing it. Does anyone have any recommendations or experience with any of these analytics packages? Thanks so much!

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• Google Analytics recording event based on <a> title attribute

  - by rlsaj

  I am declaring: var title = (typeof(el.attr('title')) != 'undefined' ) ? el.attr('title') :""; and then have the following: else if (title.match(/^"Matching Content"\:/i)) { elEv.category = "Matching Content Click"; elEv.action = "click-Matching-Content"; elEv.label = href.replace(/^https?\:\/\//i, ''); elEv.non_i = true; elEv.loc = href; } However, using Google Analytics debugger this is not being recorded. Any suggestions? The complete function is: if (typeof jQuery != 'undefined') { jQuery(document).ready(function gLinkTracking($) { var filetypes = /\.(avi|csv|dat|dmg|doc.*|exe|flv|gif|jpg|mov|mp3|mp4|msi|pdf|png|ppt.*|rar|swf|txt|wav|wma|wmv|xls.*|zip)$/i; var baseHref = ''; if (jQuery('base').attr('href') != undefined) baseHref = jQuery('base').attr('href'); jQuery('a').on('click', function (event) { var el = jQuery(this); var track = true; var href = (typeof(el.attr('href')) != 'undefined' ) ? el.attr('href') :""; var title = (typeof(el.attr('title')) != 'undefined' ) ? el.attr('title') :""; var isThisDomain = href.match(document.domain.split('.').reverse()[1] + '.' + document.domain.split('.').reverse()[0]); if (!href.match(/^javascript:/i)) { var elEv = []; elEv.value=0, elEv.non_i=false; if (href.match(/^mailto\:/i)) { elEv.category = "Email link"; elEv.action = "click-email"; elEv.label = href.replace(/^mailto\:/i, ''); elEv.loc = href; } else if (title.match(/^"Matching Content"\:/i)) { elEv.category = "Matching Content Click"; elEv.action = "click-Matching-Content"; elEv.label = href.replace(/^https?\:\/\//i, ''); elEv.non_i = true; elEv.loc = href; } else if (href.match(filetypes)) { var extension = (/[.]/.exec(href)) ? /[^.]+$/.exec(href) : undefined; elEv.category = "File Downloaded"; elEv.action = "click-" + extension[0]; elEv.label = href.replace(/ /g,"-"); elEv.loc = baseHref + href; } else if (href.match(/^https?\:/i) && !isThisDomain) { elEv.category = "External link"; elEv.action = "click-external"; elEv.label = href.replace(/^https?\:\/\//i, ''); elEv.non_i = true; elEv.loc = href; } else if (href.match(/^tel\:/i)) { elEv.category = "Telephone link"; elEv.action = "click-telephone"; elEv.label = href.replace(/^tel\:/i, ''); elEv.loc = href; } else track = false; if (track) { _gaq.push(['_trackEvent', elEv.category.toLowerCase(), elEv.action.toLowerCase(), elEv.label.toLowerCase(), elEv.value, elEv.non_i]); if ( el.attr('target') == undefined || el.attr('target').toLowerCase() != '_blank') { setTimeout(function() { location.href = elEv.loc; }, 400); return false; } } } }); }); }

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• Willy Rotstein on Supply Chain Planning

  - by sarah.taylor(at)oracle.com

  Each time a merchandiser, buyer or planner in Retail makes a business decision around assortment, inventory, pricing and promotions there is an opportunity to improve both Profitability and Customer Service. Improving decision making, however, has always been a tricky business for retailers.  I have worked in this space for more than 15 years. I began my career as an academic, at Imperial College London, and then broadened this interest with Retailers, aiming to optimize their merchandising and supply chain decisions. Planning the business and optimizing profit is a complex process. The complexity arises from the variety of people involved, the large number of decisions to take across all business processes, the uncertainty intrinsic to the retail environment as well as the volume of data available for analysis.  Things are not getting any easier either. The advent of multi-channel, social media and mobile is taking these complexities to a new level and presenting additional opportunities for those willing to exploit them. I guess it is due to the complexities of the decision making process that, over the last couple of years working with Oracle Retail, I have witnessed a clear trend around the deployment of planning systems. Retailers are aiming to simplify their decision making processes. They want to use one joined up planning platform across the business and enhance it with "actionable" data mining and optimization techniques. At Oracle Retail, we have a vibrant community of international retailers who regularly come together to discuss the big issues in retail planning. It is a combination of fashion, grocery and speciality retailers, all sharing their best practice vision for planning and optimizing merchandise decisions. As part of the Retail Exchange program, at the recent National Retail Federation event in New York, I jointly hosted a Planning dinner with Peter Fitzgerald from Google UK, Retail Division. Those retailers from our international planning community who were in New York for the annual NRF event were able to attend. The group comprised some of Europe's great International Retail brands.  All sectors were represented by organisations like Mango, LVMH, Ahold, Morrisons, Shop Direct and River Island. They confirmed the current importance of engaging with Planning and Optimization issues. In particular the impact of the internet was a key topic. We had a great debate about new retail initiatives.  Peter highlighted how mobility is changing retail - in particular with the new "local availability search" initiative. We also had an exciting discussion around the opportunities to improve merchandising using the new data that is becoming available from search, social media and ecommerce sites. It will be our focus to continue to help retailers translate this data into better results while keeping their business operations simple. New developments in "actionable" analytics and computing capacity make this a very exciting area today. Watch this space for my contributions on these topics which will be made available through this blog. Oracle Retail has a strong Planning community. if you are a category manager, a planner, a buyer, a merchandiser, a retail supplier or any retail executive with a keen interest in planning then you would be very welcome to join Oracle Retail's Planning Community. As part of our community you will be able to join our in-person and virtual events, download topical white papers and best practice information specifically tailored to your area of interest.  If anyone would like to register their interest in joining our community of retailers discussing planning then please contact me at [email protected]   Willy Rotstein, Oracle Retail

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• Setting up a Google Analytics Campaign

  - by Ashfame

  I will be doing a bunch of things to give one of my projects (main app) a big initial push for which I will be building a few small Facebook apps which will help in promoting the main apps. Traffic from these apps need to be tracked individually. My main app will be posting on the walls when the user needs to be notified. Traffic from these posts need to be tracked. Traffic from emails sent by the main app need to be tracked, like different types of email. I need to track all of these & possibly a couple of more but I need to be sure that I build my campaign URLs correctly as I won't get another chance to fix it. Correct me where I am wrong: Campaign Name: Launch Campaign Medium: Email Campaign Source: Type1 or Type2 (I can break it down for different types of email, right?) For apps: Campaign Name: Launch Campaign Medium: Apps Campaign Source: App1 or App2 (I can break it down here for different apps, right?) What if I want to track two different links within a single email or a single app? Any way of tracking them individually too but still keeping to track them as one because tracking them as one makes more sense for me. Campaign Term & Campaign content is irrelevant in my case, or I can/should use them for something? And I will also be tracking traffic of different apps. Should I do more? Let me know if my scenario wasn't clear enough & I need to explain more.

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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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• 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 Management – data 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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• Master Data Services Employees Sample Model

  - by Davide Mauri

  I’ve been playing with Master Data Services quite a lot in those last days and I’m also monitoring the web for all available resources on it. Today I’ve found this freshly released sample available on MSDN Code Gallery: SQL Server Master Data Services Employee Sample Model http://code.msdn.microsoft.com/SSMDSEmployeeSample This sample shows how Recursive Hierarchies can be modeled in order to represent a typical organizational chart scenario where a self-relationship exists on the Employee entity. Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

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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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• 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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• Google Analytics is not tracking all of our pages

  - by luis

  Our website is insynchq.com. In the All Pages report under Content - Site Content we can only see data for some our pages, like /, /getstarted, and /download. Others, like /gmail, /about, and /mobile are not shown, even if we are sure that there have been visits to them. We use a template for our pages so the scripts that are loaded for / (for example) should also be loaded for /gmail, so it doesn't seem to be a problem with the installation of the tracking code. Can anyone help? Thanks.

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• NRF Week - Disney Store Tour

  - by sarah.taylor(at)oracle.com

  Disney has created a real buzz at this year's NRF event. Yesterday morning we began the Oracle Retail Exchange program with a visit to the flagship Disney store in Times Square. Additionally Oracle made a key announcement with Disney  on Oracle Retail's Point of Sale implementation in 330 stores worldwide. Today   Disney's Steve Finney gave a super session on The Magic of Disney at the NRF Big Show. We also saw Disney making an exclusive news announcement about their plans for Global store openings at the Oracle trade show stand - with a little help from Mickey and Minnie Mouse. Disney Stores have been entirely reinvented since the company in 2008 took ownership after previously franchising the retail arm of the business. They have subsequently been a strong Oracle partner and technology has played a key role in their re imagination of the store environment. The new Imagination stores have a 20% higher footfall and margins are up 25%. The Disney brand is synonymous with magical and memorable experiences for children of all ages. The company is achieving a unique retail experience that delights children and shareholders alike! Technology is a key pillar in helping to deliver on both a strong operating model and a unique customer experience - the best thirty minutes in a child's day is their aim. Steve Finney this morning said their technology has to be as reliable as a theme park ride. Store experiences are much more enjoyable when there are short waiting times and children can interact with their favourite characters through magic mirrors, mobile point of sale, touch screens and custom animations that are digitally transmitted to stores globally. The Oracle Retail Point of Sale with iPad touch screens reduces check out times, stores customer data, ensures that promotions are delivered accurately and reduces losses. This means higher levels of guest conversion, increased availability and convenience for customers who want to check availability at other locations. Disney is a pioneer. At NRF's 100th show, we had the privilege of learning from a retailer using technology as a creative force to drive their business forward.

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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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• Google Analytics API - Tying Behavior to Specific Dates

  - by DavidS

  I am using the API to understand the performance of Adwords ad campaigns. I need to know how to attribute metrics back to the date dimension. For instance, for a given date, if I have 20 clicks, 18 visits, and 3 goal completions, does it mean that: 1) All of these actions happened on the day in question and are otherwise independent (meaning that the 3 goals could have been for people that clicked any time in the past 30 days, not who clicked on that day) 2) The on-site actions are a subset of the click activity on that day (i.e. on that day, 20 people clicked, 18 registered a real visit, and 3 completed a goal) If it is scenario 2, does that mean there is a need to refresh old rows every day? Thanks!

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• How do you exclude yourself from Google Analytics on your website using cookies?

  - by Keoki Zee

  I'm trying to set up an exclusion filter with a browser cookie, so that my own visits to my don't show up in my Google Analytics. I tried 3 different methods and none of them have worked so far. I would like help understanding what I am doing wrong and how I can fix this. Method 1 First, I tried following Google's instructions, http://www.google.com/support/analytics/bin/answer.py?hl=en&answer=55481, for excluding traffic by Cookie Content: Create a new page on your domain, containing the following code: <body onLoad="javascript:pageTracker._setVar('test_value');"> Method 2 Next, when that didn't work, I googled around and found this Google thread, http://www.google.com/support/forum/p/Google%20Analytics/thread?tid=4741f1499823fcd5&hl=en, where the most popular answer says to use a slightly different code: SHS Analytics wrote: <body onLoad="javascript:_gaq.push(['_setVar','test_value']);"> Thank you! This has now set a __utmv cookie containing "test_value", whereas the original: pageTracker._setVar('test_value') (which Google is still recommending) did not manage to do that for me (in Mac Safari 5 and Firefox 3.6.8). So I tried this code, but it didn't work for me. Method 3 Finally, I searched StackOverflow and came across this thread, http://stackoverflow.com/questions/3495270/exclude-my-traffic-from-google-analytics-using-cookie-with-subdomain, which suggests that the following code might work: <script type="text/javascript"> var _gaq = _gaq || []; _gaq.push(['_setVar', 'exclude_me']); _gaq.push(['_setAccount', 'UA-xxxxxxxx-x']); _gaq.push(['_trackPageview']); // etc... </script> This script appeared in the head element in the example, instead of in the onload event of the body like in the previous 2 examples. So I tried this too, but still had no luck with trying to exclude myself from Google Analytics. Re-iterate question So, I tried all 3 methods above with no success. Am I doing something wrong? How can I exclude myself from my Google Analytics using an exclusion cookie for my browser?

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• How do you exclude yourself from Google Analytics on your website using cookies?

  - by Cold Hawaiian

  I'm trying to set up an exclusion filter with a browser cookie, so that my own visits to my don't show up in my Google Analytics. I tried 3 different methods and none of them have worked so far. I would like help understanding what I am doing wrong and how I can fix this. Method 1 First, I tried following Google's instructions, http://www.google.com/support/analytics/bin/answer.py?hl=en&answer=55481, for excluding traffic by Cookie Content: Create a new page on your domain, containing the following code: <body onLoad="javascript:pageTracker._setVar('test_value');"> Method 2 Next, when that didn't work, I googled around and found this Google thread, http://www.google.com/support/forum/p/Google%20Analytics/thread?tid=4741f1499823fcd5&hl=en, where the most popular answer says to use a slightly different code: SHS Analytics wrote: <body onLoad="javascript:_gaq.push(['_setVar','test_value']);"> Thank you! This has now set a __utmv cookie containing "test_value", whereas the original: pageTracker._setVar('test_value') (which Google is still recommending) did not manage to do that for me (in Mac Safari 5 and Firefox 3.6.8). So I tried this code, but it didn't work for me. Method 3 Finally, I searched StackOverflow and came across this thread, http://stackoverflow.com/questions/3495270/exclude-my-traffic-from-google-analytics-using-cookie-with-subdomain, which suggests that the following code might work: <script type="text/javascript"> var _gaq = _gaq || []; _gaq.push(['_setVar', 'exclude_me']); _gaq.push(['_setAccount', 'UA-xxxxxxxx-x']); _gaq.push(['_trackPageview']); // etc... </script> This script appeared in the head element in the example, instead of in the onload event of the body like in the previous 2 examples. So I tried this too, but still had no luck with trying to exclude myself from Google Analytics. Re-iterate question So, I tried all 3 methods above with no success. Am I doing something wrong? How can I exclude myself from my Google Analytics using an exclusion cookie for my browser? Update I've been testing this for several days now, and I've confirmed that the 2nd method of excluding yourself from tracking does indeed work. The problem was that the filter settings weren't properly applied to my profile, which has been corrected. See the accepted answer below.

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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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• Why CFOs Should Care About Big Data

  - by jmorourke

  The topic of “big data” clearly has reached a tipping point in 2012.  With plenty of coverage over the past few years in the IT press, we are now starting to see the topic of “big data” covered in mainstream business press, including a cover story in the October 2012 issue of the Harvard Business Review.  To help customers understand the challenges of managing “big data” as well as the opportunities that can be created by leveraging “big data”, Oracle has recently run and published the results of a customer survey, as well as white papers and articles on this topic.  Most recently, we commissioned a white paper titled “Mastering Big Data: CFO Strategies to Transform Insight into Opportunity”. The premise here is that “big data” is not just a topic that CIOs should pay attention to, but one that CFOs should understand and take advantage of as well.  Clearly, whoever masters the art and science of big data will be positioned for competitive advantage in their industries or markets.  That’s why smart CFOs are taking control of big data and business analytics projects, not just to uncover new ways to drive growth in a slowing global economy, but also to be a catalyst for change in the enterprise.  With an increasing number of CFOs now responsible for overseeing IT investments and providing strategic insight to the board, CFOs will be increasingly called upon to take a leadership role in assessing the value of “big data” initiatives, building on their traditional skills in reporting and helping managers analyze data to support decision making. Here’s a link to the white paper referenced above, which is posted on the Oracle C-Central/CFO web site, as well as some other resources that can help CFOs master the topic of “big data”: White Paper “Mastering Big Data:  CFO Strategies to Transform Insight into Opportunity CFO Market Watch article:  “Does Big Data Affect the CFO?” Oracle Survey Report:  “From Overload to Impact – An Industry Scorecard on Big Data Industry Challenges” Upcoming Big Data Webcast with Andrew McAfee Here’s a general link to Oracle C-Central/CFO in case you want to start there: www.oracle.com/c-central/cfo Feel free to contact me if you have any questions or need additional information:  [email protected]

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• Ideal data structure/techniques for storing generic scheduler data in C#

  - by GraemeMiller

  I am trying to implement a generic scheduler object in C# 4 which will output a table in HTML. Basic aim is to show some object along with various attributes, and whether it was doing something in a given time period. The scheduler will output a table displaying the headers: Detail Field 1 ....N| Date1.........N I want to initialise the table with a start date and an end date to create the date range (ideally could also do other time periods e.g. hours but that isn't vital). I then want to provide a generic object which will have associated events. Where an object has events within the period I want a table cell to be marked E.g. Name Height Weight 1/1/2011 2/1/2011 3/1/20011...... 31/1/2011 Ben 5.11 75 X X X Bill 5.7 83 X X So I created scheduler with Start Date=1/1/2011 and end date 31/1/2011 I'd like to give it my person object (already sorted) and tell it which fields I want displayed (Name, Height, Weight) Each person has events which have a start date and end date. Some events will start and end outwith but they should still be shown on the relevant date etc. Ideally I'd like to have been able to provide it with say a class booking object as well. So I'm trying to keep it generic. I have seen Javasript implementations etc of similar. What would a good data structure be for this? Any thoughts on techniques I could use to make it generic. I am not great with generics so any tips appreciated.

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