SQL for Data Warehousing and Analytics

Our SPARC and OLAP development teams have published some fantastic performance figures on their blog: https://blogs.oracle.com/BestPerf/entry/20130326_sparc_t5_8_olap Using Oracle's SPARC T5-8 server the teams delivered world record query performance with near real-time analytic capability using the Oracle OLAP Perf Version 3 workload running Oracle Database 11g Release 2 on Oracle Solaris 11. The workload uses a set of realistic BI queries that run against an OLAP cube based on a 4 billion row fact table of sales data. The 4 billion rows are partitioned by month spanning 10 years. The combination of the Oracle Database with the Oracle OLAP option running on a SPARC T5-8 server supports live data updates occurring concurrently with minimally impacted user query executions. This is a great evolution of the development work we have been doing with our in-database OLAP features. The details about "real-time" analytics reminded me of the work with did with BNP Paribas to de...

http://www.oracle.com/technetwork/developer-tools/datamodeler/overview/index.html Attention all data modellers - we are pleased to announce the release of SQL Developer Data Modeler 3.3. This release includes a new search, reports can be generated from search results, extended Excel import and export capabilities and more control and flexibility in generating your DDL.  Here are a few links to get you started: For downloads see here:  http://www.oracle.com/technetwork/developer-tools/datamodeler/downloads/index.html For information about new features see here:  http://www.oracle.com/technetwork/developer-tools/datamodeler/datamodeler-33-newfeatures-1869156.html The release notes are available here:  http://www.oracle.com/technetwork/developer-tools/datamodeler/data-modeler-releasenotes33-1869517.html The documentation can be found here:  http://www.oracle.com/pls/topic/lookup?ctx=E29463_01&id=homepage For data warehouse data modellers there are some very important new feat...

According to an article by Forrester analyst Mike Gualtieri, predictive analytics is a red hot topic!  There are many examples across a broad range of industries where predictive analytics is driving better decisions: President Obama's campaign team used sophisticated uplift modeling to target and influence swing voters. Telecom firms that use predictive analytics to help prevent customer churn.  Police departments that use it to reduce crime. The list goes on and on and on. Let us quickly look at two of these uses cases because we have Oracle customers who have already implemented these types of solutions: 1) How telcos are using predictive analytics to reduce churn a) Telecom Italia Lab - Churn is a critical problem in the telecommunications industry because losing customers is a drain on resources. Finding new customers to replace the ones that have defected to a competitor is an expensive process. Consequently companies go to great lengths to reduce the c...

Stumbled across this article on the motoring page of the Guardian newspaper. Cars will soon be so linked into wireless networks they will be like giant rolling smartphones. Ford has already started to integrate web services such as Spotify into their dashboard systems and this looks like the first step to introducing a real-time data collection service to your car. This new vision of in-car big data goes far beyond the current engine management monitoring that garages use when you take your car in for servicing. A few examples of this brave new world: - Low on fuel? Soon a petrol station app may know before you do. - Tyres need rotating? Your car may wirelessly alert your dealership when it's time. - Ready for a lunch break? Your car can make a reasonable guess based on the hour. Are these realistic? Well, according to the article "… more than 60% of vehicles worldwide will be connected directly to the internet by 2017, up from 11% last year, predicts ABI Research. In No...

The latest Data Warehouse Magic Quadrant is out and we (Oracle) has been positioned in the leaders quadrant. How do you get into the leaders quadrant? This is how Gartner defines a leader: vendors in the Leaders quadrant, “demonstrate the greatest support for data warehouses of all sizes, with large numbers of concurrent users and management of mixed data warehousing workloads. These vendors lead in data warehousing by consistently demonstrating customer satisfaction and strong support, as well as longevity in the data warehouse DBMS market, with strong hardware alliances.  Here is a great quote from my boss, Cetin Ozbutun, vice president, Data Warehousing and Big Data Technologies: “We believe Oracle's position in Gartner's Magic Quadrant for Data Warehouse Database Management Systems recognizes the outstanding performance of the Oracle Exadata Database Machine, as well as Oracle’s delivery of innovative, integrated solutions for big data with the Big Data Appliance and ...

If you want to get hands-on time with Oracle's big data technology stack then we are rolling out, in collaboration with OTN, a new complementary one-day hands-on workshop - yes it really is FREE! The date will is Wednesday, February 20, 2013 at Oracle's HQ in Redwood Shores, California . The workshop will be based around the MoviePlex demonstration application that was first shown at last year's OpenWorld and you will get hands-on time with the source code and we will show you how to develop some of the key features of this application. What is Oracle MoviePlex? The Oracle MoviePlex is a fictional on-line movie streaming company and like many other on-line stores, they needed a cost effective approach to tackle their “big data” challenges. They recently implemented Oracle’s Big Data Platform to better manage their business, identify key opportunities and enhance customer satisfaction. The key challenge for Oracle Movieplex is how to manage and process massive vo...

Many of our customers spent 2012 kick-starting big data projects. Based on the number of analyst reports, news articles and general chatter on the web I think it is fair to say that 2012 was the Year of Big Data. To help our customers plan and coordinate their big data projects we developed a very simple high level five step workflow for big data (Stream-Acquire-Organize-Analyze-Decide) as shown here: Many of the projects that our customers stated in 2012 have at least completed the first three steps (with some having completed stages 4 and 5 and now looping back to stage 1 to kick-start the next round of data enrichment and knowledge discovery ): 1) STREAM - all the relevant data streams have been identified and the APIs coded to collect the data on a regular basis 2) ACQUIRE - these data streams are increasing landing on our Big Data Appliance and that is great news! 3) ORGANIZE - many project teams have completed the first round of light-touch transformations and made thei...