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  • ADNOC talks about 50x increase in performance

    - by KLaker
    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 research because it provided them with a single platform that can run mixed workloads in a single unified machine: "We chose Oracle Exadata Database Machine because it.offered a fully integrated and highly engineered system that was ready to deploy. With our infrastructure running all the same technology, we can operate any type of Oracle Database without restrictions and be prepared for business growth," said Ali Abdul Aziz Al-Ali, IT division manager, ADNOC Distribution. ".....we could consolidate our transaction processing and business intelligence onto one platform. Competing solutions are just not capable of doing that." - Awad Ahmed Ali El-Sidiq, Senior Database Administrator, ADNOC Distribution In this new video Awad Ahmen Ali El Sidddig, Senior DBA at ADNOC, talks about the impact that Exadata has had on his team and the whole business. ADNOC is using our engineered systems to drive and manage all their workloads: from transaction systems to payments system to data warehouse to BI environment. A true Disk-to-Dashboard revolution using Engineered Systems. This engineered approach is delivering 50x improvement in performance with one queries running 100x faster! The IT has even revolutionised some of their data warehouse related processes with the help of Exadata and now jobs that were taking over 4 hours now run in a few minutes.  To watch the video click on the image below which will take you to our Oracle YouTube page: (if the above link does not work, click here: http://www.youtube.com/watch?v=zcRpxc6u5Ic) Now that queries are running 100x faster and jobs are completing in minutes not hours, what is next for the IT team at ADNOC? Like many of our customers ADNOC is now looking to take advantage of big data to help them better align their business operations with customer behaviour and customer insights. To help deliver this next level of insight the IT team is looking at the new features in Oracle Database 12c such as the new in-memory feature to deliver even more performance gains.  The great news is that Awad Ahmen Ali El Sidddig was awarded DBA of the Year - EMEA within our Data Warehouse Global Leaders programme and you can see the badge for this award pop-up at the start of video. Well done to everyone at ADNOC and thanks for spending the time with us at OOW to create this great video.

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  • OpenWorld on your iPad and iPhone

    - by KLaker
    Most of you probably know that each year I publish a data warehouse guide for OpenWorld which contains links to the latest data warehouse videos, a calendar for the most important sessions and labs and a section that provides profiles and relevant links for all the most important data warehouse presenters. For this year’s conference made all this information available in an HTML app that runs on most smartphones and tablets. The pictures below show the HTML app running on iPad and iPhone. This exciting new web app contains information about why you should attend OpenWorld - just in case you have not yet booked your ticket! - as well as the following information: Getting to know 12c - a series of video interviews with George Lumpkin, Vice President of Data Warehouse Product Management Your presenters - full biographies and links to social media sites for all the key data warehouse presenters Must sees sessions - list of all the most important data warehouse presentations at this year’s conference Our customers - profiles our most important data warehouse customers Must attend labs - list of all the most important data warehouse hands-on labs at this year’s conference Links - a list of links to the most important data warehouse sites If you want to run these web apps on your smartphone and/or tablet then follow these links: iPhone - https://876d5e65b7768ca57d1fd1236578c9374b1fca87.googledrive.com/host/0Bz-zGlWahRf4OXNzejBiRFV5ZXc/iPhone-DWoow2014.html iPad - https://876d5e65b7768ca57d1fd1236578c9374b1fca87.googledrive.com/host/0Bz-zGlWahRf4OXNzejBiRFV5ZXc/iPad-DW2014.html Android users: I have tested the app on Android and there appears to be a bug in the way the Chrome browser displays iframes because scrolling does not work . The app does work correctly if you use either the Android version of the Opera browser or the standard Samsung browser. If you have any comments about the app (content you would like to see) then please let me know. Enjoy OpenWorld.

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  • Oracle Data Warehouse and Big Data Magazine MAY Edition for Customers + Partners

    - by KLaker
    Follow us on The latest edition of our monthly data warehouse and big data magazine for Oracle customers and partners is now available. The content for this magazine is taken from the various data warehouse and big data Oracle product management blogs, Oracle press releases, videos posted on Oracle Media Network and Oracle Facebook pages. Click here to view the May Edition Please share this link http://flip.it/fKOUS to our magazine with your customers and partners This magazine is optimized for display on tablets and smartphones using the Flipboard App which is available from the Apple App store and Google Play store

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

    - by KLaker
    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 towards a "wow" moment is to extend this basic use of spatial and pattern matching, as shown in the above dashboard screen, to incorporate spatial analytics within the SQL pattern matching clause. This will allow us to compute the distance between transactions. Apologies for the quality of this screenshot….hopefully below you see where we have extended our SQL pattern matching clause to use location of each transaction and to calculate the distance between each transaction: This allows us to compare the time of the last transaction with the time of the current transaction and see if the distance between the two points is possible given the time frame. Obviously if I buy something in Florida from my favourite bike store (may be a new carbon saddle for my Trek) and then 5 minutes later the system sees my credit card details being used in Arizona there is high probability that this transaction in Arizona is actually fraudulent (I am fast on my Trek but not that fast!) and we can flag this up in real-time on our dashboard: In this post I have used the term "real-time" a couple of times and this is an important point and one of the key reasons why SQL really is the only language to use if you want to analyse  big data. One of the most important questions that comes up in every big data project is: how do we do analysis? Many enlightened customers are now realising that using Java-MapReduce to deliver analysis does not result in "wow" moments. These "wow" moments only come with SQL because it is offers a much richer environment, it is simpler to use and it is faster - which makes it possible to deliver real-time "Wow!". Below is a slide from Andy's session showing the results of a comparison of Java-MapReduce vs. SQL pattern matching to deliver our "wow" moment during our live demo.  You can watch our analytical mash-up "Wow" demo that compares the power of 12c SQL pattern matching + spatial analytics vs. Java-MapReduce  here: You can get more information about SQL Pattern Matching on our SQL Analytics home page on OTN, see here http://www.oracle.com/technetwork/database/bi-datawarehousing/sql-analytics-index-1984365.html.  You can get more information about our spatial analytics here: http://www.oracle.com/technetwork/database-options/spatialandgraph/overview/index.html If you would like to watch the full Database 12c OOW presentation see here: http://medianetwork.oracle.com/video/player/2686974264001

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  • Oracle Magazine: Getting started with SQL Analytics

    - by KLaker
    I am currently working on a series of podcasts covering the broad categories of our SQL analytical functions and features and while I was doing some research I came across of series of four articles in the Oracle Magazine. This series of article is written by Melanie Caffrey who is a senior development manager at Oracle. She is a coauthor of Expert PL/SQL Practices for Oracle Developers and DBAs (Apress, 2011) and Expert Oracle Practices: Oracle Database Administration from the Oak Table (Apress, 2010). The four articles are under the banner "Technology: SQL 101" and parts 9, 10, 11 and 12 cover SQL analytics. Here are the links to the four articles: Jan 2013 Having Sums, Averages, and Other Grouped Data March 2013 A Window into the World of Analytic Functions May 2013 Leading Ranks and Lagging Percentages: Analytic Functions, Continued July 2013 Pivotal Access to Your Data: Analytic Functions, Concluded The articles cover topics such as GROUP BY, SUM, AVG, HAVING, window functions, RANK, FIRST, LAST, LAG, LEAD etc.   The great news is that  you can try out the examples in this series. All you need is access to an Oracle Database instance. All the schemas, data sets and SQL statements that you will need can be downloaded from a link included in the January article.    I hope you find this series of articles useful.

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  • Start your journey into Big Data with the Oracle Academy today!

    - by KLaker
     Big Data has the power to change the way we work, live, and think. The datafication of everything will create unprecedented demand for data scientists, software developers and engineers who can derive value from unstructured data to transform the world. The Oracle Academy Big Data Resource Guide is a collection of articles, videos, and other resources organized to help you gain a deeper understanding of the exciting field of Big Data. To start your journey visit the Oracle Academy website here: https://academy.oracle.com/oa-web-big-data.html. This landing pad will guide through the whole area of big data using the following structure: What is “Big Data” Engineered Systems Integration Database and Data Analytics Advanced Information Supplemental Information This is great resource packed with must-see videos and must-read whitepapers and blog posts by industry leaders.  Enjoy Technorati Tags: Big Data, Data Warehousing, Oracle, Training

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  • Partitioning tutorial - new features in Oracle Database 12c

    - by KLaker
    For data warehousing projects Oracle Partitioning really is a must-have feature because it delivers so many important benefits such as: Dramatically improves query performance and speeds up database maintenance operations Lowers costs by enabling a tiered storage approach that allows data to be stored on the most cost-effective storage for better resource utilisation Combined with Oracle Advanced Compression, it provides an automated approach to information lifecycle management using a simple, efficient, yet powerful way to manage data growth and reduce complexity and costs To help you get the most from partitioning we have released a new tutorial that covers the 12c new features. Topics include how to: Use Interval Reference Partitioning Perform Cascading TRUNCATE and EXCHANGE Operations Move Partitions Online Maintain Multiple Partitions Maintain Global Indexes Asynchronously Use Partial Indexes For more information about this tutorial follow this link to the Oracle Learning Library: http://apex.oracle.com/pls/apex/f?p=44785:24:0::NO:24:P24_CONTENT_ID,P24_PREV_PAGE:8408,2 where you can begin your tutorial right now! For more information about Oracle Partitioning visit our home page on OTN: http://www.oracle.com/technetwork/database/bi-datawarehousing/dbbi-tech-info-part-100980.html

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  • OLL Live webcast - Using SQL for Pattern Matching in Oracle Database

    - by KLaker
    If you are interested in learning about our exciting new 12c SQL pattern matching feature then mark your diaries. On Wednesday, October 30th at 8:00 am (US/Pacific time zone) Supriya Ananth, who is one of our top curriculum developers at Oracle, will be hosting an OLL webcast on our new SQL pattern matching feature. The ability to recognize patterns in a sequence of rows has been a capability that was widely desired, but not possible with SQL until now. Row pattern matching in native SQL improves application and development productivity and query efficiency for row-sequence analysis. With Oracle Database 12c you can use the new MATCH_RECOGNIZE clause to perform pattern matching in SQL to do the following: Logically partition and order the data using the PARTITION BY and ORDER BY clauses Use regular expressions syntax to define patterns of rows to seek using the PATTERN clause. These patterns a powerful and expressive feature, applied to the pattern variables you define. Specify the logical conditions required to map a row to a row pattern variable in the DEFINE clause. Define measures, which are expressions usable in the MEASURES clause of the SQL query. For more information and to register for this exciting webcast please visit the OLL Live website, see here: https://apex.oracle.com/pls/apex/f?p=44785:145:116820049307135::::P145_EVENT_ID,P145_PREV_PAGE:461,143.  Please note - if the above link does not work then go to OLL (https://apex.oracle.com/pls/apex/f?p=44785:1:) and click the OLL Live icon (upper right, beneath the Login link or logout link if you are already logged in). The pattern matching webcast is listed on the calendar of events on 30 October.

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  • OOW content for Pattern Matching....

    - by KLaker
    If you missed my sessions at OpenWorld then don't worry - all the content we used for pattern matching (presentation and hands-on lab) is now available for download. My presentation "SQL: The Best Development Language for Big Data?" is available for download from the OOW Content Catalog, see here: https://oracleus.activeevents.com/2013/connect/sessionDetail.ww?SESSION_ID=9101 For the hands-on lab ("Pattern Matching at the Speed of Thought with Oracle Database 12c") we used the Oracle-By-Example content. The OOW hands-on lab uses Oracle Database 12c Release 1 (12.1) and uses the MATCH_RECOGNIZE clause to perform some basic pattern matching examples in SQL. This lab is broken down into four main steps: Logically partition and order the data that is used in the MATCH_RECOGNIZE clause with its PARTITION BY and ORDER BY clauses. Define patterns of rows to seek using the PATTERN clause of the MATCH_RECOGNIZE clause. These patterns use regular expressions syntax, a powerful and expressive feature, applied to the pattern variables you define. Specify the logical conditions required to map a row to a row pattern variable in the DEFINE clause. Define measures, which are expressions usable in the MEASURES clause of the SQL query. You can download the setup files to build the ticker schema and the student notes from the Oracle Learning Library. The direct link to the example on using pattern matching is here: http://apex.oracle.com/pls/apex/f?p=44785:24:0::NO:24:P24_CONTENT_ID,P24_PREV_PAGE:6781,2.

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  • Swiss Re increases data warehouse performance and deploys in record time

    - by KLaker
    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 minimizing time spent on tuning activities Most importantly this was one of the fastest project deployments in Swiss Re's history. They went from installation to production in just four months! What is truly surprising is the that it only took two weeks between power-on to testing the machine with full data volumes! Business teams at Swiss Re are now able to fully exploit up-to-date analytics across property, casualty, life, health insurance, and reinsurance lines to identify successful products. These points are highlighted in the following quotes from Dr. Stephan Gutzwiller, Head of Data Warehouse Services at Swiss Re:  "We were operating a complete Oracle stack, including servers, storage area network, operating systems, and databases that was well optimized and delivered very good performance over an extended period of time. When a hardware replacement was scheduled for 2012, Oracle Exadata was a natural choice—and the performance increase was impressive. It enabled us to deliver analytics to our internal customers faster, without hiring more IT staff" “The high quality data that is readily available with Oracle Exadata gives us the insight and agility we need to cater to client needs. We also can continue re-engineering to keep up with the increasing demand without having to grow the organization. This combination creates excellent business value.” Our full press release is available here: http://www.oracle.com/us/corporate/customers/customersearch/swiss-re-1-exadata-ss-2050409.html. If you want more information about how Exadata can increase the performance of your data warehouse visit our home page: http://www.oracle.com/us/products/database/exadata-database-machine/overview/index.html

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