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Showing posts from November, 2013

Read-All-About-It: new weekly Oracle Data Warehousing newspaper

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Thanks to Brendan Tierney for bringing this excellent online automated news service to my attention…. For a long time I have been wondering how to pull together all the articles from my favourite Twitter feeds, Facebook pages and blogs. Well thanks to Brendan I have discovered a service called  Paper.li . This weekend I spent some time setting up feeds from all my favourite sources related to data warehousing, big data. Exadata and other related Oracle technologies. The result is the " #Oracle DW-Big Data Weekly Roundup " which is designed to " keep you up to date on all the weekly sql analytics, data warehousing and big data news from # Oracle ". The newspaper is refreshed every Sunday night so that it is ready for Monday morning to read over breakfast. It is the perfect way to start the working week…. if you want to subscribe to this weekly newspaper then go here:  http://paper.li/OracleBigData/1384259272  and click on the red SUBSCRIBE link in the top

Get some sun and learn about Pattern Matching at BIWA

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This is your chance to get some winter sun and learn about the new 12c SQL pattern matching! I have just received confirmation from BIWA Summit team that my presentation and hands-on lab on SQL pattern matching have been accepted for the 2014 conference (Jan 14-16 2014 at the Oracle Conference Center, Oracle HQ, Redwood Shores). If you are not familiar with BIWA then here is an overview: The Oracle Business Intelligence, Warehousing and Analytics Special Interest Group (BIWA SIG) is the leading worldwide association of persons interested in the successful deployment of Oracle Database-centric business intelligence, data warehousing, analytical products, EPM/Essbase and Big Data related features and options. BIWA now has almost 2000 members worldwide. BIWA is a not-for-profit entity affiliated with the Independent Oracle Users Group (IOUG). BIWA runs all sorts of activities: Webcasts - BIWA holds monthly webcasts presenting BI and DW experts speaking on BI, Data Warehousing and

Using Oracle Exadata to improve crop yields

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It is not often you read about how the agricultural industry uses data warehousing so this article in latest edition of Oracle Magazine, with the related video from OOW 2013, on how Land O'Lakes is using Exadata caught my attention:   The Business of Growing , by Marta Bright  http://www.oracle.com/technetwork/issue-archive/2013/13-nov/o63lol-2034253.html A little background on Land O'Lakes: Land O’Lakes is a US company that has grown far beyond its roots as a small cooperative of dairy farmers with forward-thinking ideas about producing and packaging butter. It is a Fortune 500 company and is now the second-largest cooperative in the United States, with annual sales of more than US$14 billion. Over the years, Land O’Lakes has expanded its operations into a variety of subsidiaries, including WinField Solutions (WinField), which provides farmers with a wide variety of crop seeds and crop protection products. This implementation on our engineered systems highlights one of the k

ADNOC talks about 50x increase in performance

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If you are still wondering about how Exadata can revolutionise your business then I would recommend watching this great video which was recorded at this year's OpenWorld. First a little background...The Abu Dhabi National Oil Company for Distribution (ADNOC) is an integrated energy company that was founded in 1973. ADNOC Distribution markets and distributes petroleum products and services within the United Arab Emirates and internationally. As one of the largest and most innovative government-owned petroleum companies in the Arab Gulf, ADNOC Distribution is renowned and respected for the exceptional quality and reliability of its products and services. Its five corporate divisions include more than 200 filling stations (a number that is growing at 8% annually), more than 150 convenience stores, 10 vehicle inspection stations, as well as wholesale and retail sales of bulk fuel, gas, oil, diesel, and lubricants. ADNOC selected Oracle Exadata Database Machine after extensive resear

Swiss Re increases data warehouse performance and deploys in record time

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Great information on yet another data warehouse deployment on Exadata. A little background on Swiss Re: In 2002, Swiss Re established a data warehouse for its client markets and products to gather reinsurance information across all organizational units into an integrated structure. The data warehouse provided the basis for reporting at the group level with drill-down capability to individual contracts, while facilitating application integration and data exchange by using common data standards. Initially focusing on property and casualty reinsurance information only, it now includes life and health reinsurance, insurance, and nonlife insurance information. Key highlights of the benefits that Swiss Re achieved by using Exadata: Reduced the time to feed the data warehouse and generate data marts by 58% Reduced average runtime by 24% for standard reports comfortably loading two data warehouse refreshes per day with incremental feeds Freed up technical experts by significantly mi

SQL analytical mash-ups deliver real-time WOW! for big data

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One of the overlooked capabilities of SQL as an analysis engine, because we all just take it for granted, is that you can mix and match analytical features to create some amazing mash-ups. As we move into the exciting world of big data these mash-ups can really deliver those "wow, I never knew that" moments. While Java is an incredibly flexible and powerful framework for managing big data there are some significant challenges in using Java and MapReduce to drive your analysis to create these "wow" discoveries. One of these "wow" moments was demonstrated at this year's OpenWorld during Andy Mendelsohn's general keynote session. Here is the scenario - we are looking for fraudulent activities in our big data stream and in this case we identifying potentially fraudulent activities by looking for specific patterns. We using geospatial tagging of each transaction so we can create a real-time fraud-map for our business users. Where we start to move to