Two new Oracle OLAP demonstrations have been added to the Oracle OLAP product page on OTN:
Fast Answers to Tough Questions Using Simple SQL :- Oracle OLAP is a world class analytic engine embedded in the Oracle Database. OLAP Cubes and dimensions are easily accessible thru a star-model. Using very simple SQL, Oracle OLAP delivers fast answers to tough, analytic questions. This demonstration shows how to query OLAP cubes using several tools, including: Oracle Business Intelligence Enterprise Edition, Application Express and SQL Developer.
Transparently Improving Query Performance with Oracle OLAP Cube MVs :- Oracle OLAP cubes may also be deployed as materialized views. Summary queries written to base fact tables can transparently leverage the fast query performance delivered by Oracle OLAP - without any changes to the application's query. The Oracle Optimizer automatically rewrites queries to cubes when appropriate. This demonstration shows how Oracle Business Intelligence Enterprise Edition seamlessly benefits from this capability. The demonstration then provides an "under the covers" view of how this improvement is achieved.
Monday, December 29, 2008
Tuesday, December 23, 2008
Oracle OLAP Newsletter - December 2008
The latest Oracle OLAP newsletter, December 2008, has been posted to the OLAP Home Page on OTN and is available by clicking here.
As usual, it contains very useful information about what is happening in the world of Oracle OLAP and includes regular features such as the OLAP skills corner and DBA tips, as well as useful links for those wanting to download the software or get training or assistance.
The featured customer this time is JD Sports in the UK. This is an excellent example of Oracle OLAP being used as part of a wider Data Warehouse solution. It is also a significant endorsement of Oracle's Data Warehouse strategy to bring smart, embedded analytics to the data and highlights the benefits of an embedded OLAP server; JD Sports has been able to leverage other advanced Oracle technologies such as Real Application Clusters (to deliver scalability and availability), whilst additionally benefiting from many of the features taken for granted by Oracle's RDBMS customers (DW integrated security, storage, backup, transaction control, etc) but often not so easily delivered by stand-alone OLAP engines.
This customer feature is also a good example of the scalability of the Oracle OLAP engine itself. Whilst far from being the largest implementation (there are customers managing several Terabytes of data in Oracle OLAP cubes), this example shows how relatively large volumes of DW data can be loaded and aggregated in Oracle OLAP, and how the cube compression and partitioning features first introduced in 10g OLAP have completely changed the game compared to what was previously possible. Taken in isolation, loading 300 million source records is not a major achievement (not for Oracle OLAP anyway), neither is having a 10 dimensional cube, or indeed is aggregating across 28 hierarchical levels. What is more impressive is doing all of these three things combined in a single cube (which is only one cube out of a total of six), and still being able to deliver all of the key benefits you would associate with an well implemented OLAP system - fast query performance and lots of advanced calcs (literally 100's in this case) serving a reasonably sized user community.
All things considered, it is easy to see why Oracle OLAP is a key, strategic component of the Oracle Data Warehouse platform.
Let's hope for some more customer features in the near future.
Greetings of the season to everyone!
BTW - you can have the OLAP newsletter sent directly to your email box each quarter by following the link at the top of the current newsletter (Unsubscribe/Subscribe to this Newsletter)
As usual, it contains very useful information about what is happening in the world of Oracle OLAP and includes regular features such as the OLAP skills corner and DBA tips, as well as useful links for those wanting to download the software or get training or assistance.
The featured customer this time is JD Sports in the UK. This is an excellent example of Oracle OLAP being used as part of a wider Data Warehouse solution. It is also a significant endorsement of Oracle's Data Warehouse strategy to bring smart, embedded analytics to the data and highlights the benefits of an embedded OLAP server; JD Sports has been able to leverage other advanced Oracle technologies such as Real Application Clusters (to deliver scalability and availability), whilst additionally benefiting from many of the features taken for granted by Oracle's RDBMS customers (DW integrated security, storage, backup, transaction control, etc) but often not so easily delivered by stand-alone OLAP engines.
This customer feature is also a good example of the scalability of the Oracle OLAP engine itself. Whilst far from being the largest implementation (there are customers managing several Terabytes of data in Oracle OLAP cubes), this example shows how relatively large volumes of DW data can be loaded and aggregated in Oracle OLAP, and how the cube compression and partitioning features first introduced in 10g OLAP have completely changed the game compared to what was previously possible. Taken in isolation, loading 300 million source records is not a major achievement (not for Oracle OLAP anyway), neither is having a 10 dimensional cube, or indeed is aggregating across 28 hierarchical levels. What is more impressive is doing all of these three things combined in a single cube (which is only one cube out of a total of six), and still being able to deliver all of the key benefits you would associate with an well implemented OLAP system - fast query performance and lots of advanced calcs (literally 100's in this case) serving a reasonably sized user community.
All things considered, it is easy to see why Oracle OLAP is a key, strategic component of the Oracle Data Warehouse platform.
Let's hope for some more customer features in the near future.
Greetings of the season to everyone!
BTW - you can have the OLAP newsletter sent directly to your email box each quarter by following the link at the top of the current newsletter (Unsubscribe/Subscribe to this Newsletter)
Sunday, December 21, 2008
Get hands-on with 11g OLAP
You may have already noticed but over the past couple of weeks some new 11g OLAP training material has been published on the OTN OLAP home page.
Two new tutorials have been added to the popular Oracle By Example (OBE) series.
The first is titled 'Building OLAP 11g Cubes' and covers using Analytic Workspace Manager (AWM) 11g to build and load an OLAP cube.
The second is titled 'Querying OLAP 11g Cubes' and is a guide to querying a cube via SQL, both directly using OLAP Cube Views, and indirectly using Cube Materialized Views.
Supporting both of the tutorials is a new sample schema which gives you the opportunity to get hands-on and experiment in your own environment. Remember, that patch level 11.1.0.7 is required and to always check the recommended release details for your chosen operating system.
Tuesday, December 16, 2008
ComputerWeekly.com : E.on transforms financial insight with Oracle OLAP Option
http://www.computerweekly.com/Articles/2008/12/11/233863/e.on+transforms+financial+insights+with+bare-knuckle.htm
The article above, published last week in ComputerWeekly, follows an earlier customer profile posted on OTN. E.on, one of Europe's leading energy suppliers, has gone live with a financial transformation software project that will give it an accurate view of the profits generated by each customer and provide better forecasting of future demand. E.on has accounts with over eight million customers in the UK. To quote directly from the project leader Lawrence Edwards: "It (accurate forecasting of demand, and, therefore, margin) is a massive problem because of the data volumes and complexity. Others have tried and failed, but we persevered."
It provides excellent proof points for the use of Oracle OLAP to solve business problems that require rapid data loading and analysis of large data volumes. The E.on system is currently operating at about 6Tb and is growing rapidly, with 150Gb of new data added every 14 hours. There is a great quote from Lawrence in the OTN PDF explaining what they have achieved using Oracle OLAP Option:
"The analytical power, centralized administration, and scalability of Oracle OLAP have allowed us to process and present data in a way that was not previously possible. This has provided us with an unprecedented depth of understanding of customers’ energy use and the demand for all our products and offerings"
The article above, published last week in ComputerWeekly, follows an earlier customer profile posted on OTN. E.on, one of Europe's leading energy suppliers, has gone live with a financial transformation software project that will give it an accurate view of the profits generated by each customer and provide better forecasting of future demand. E.on has accounts with over eight million customers in the UK. To quote directly from the project leader Lawrence Edwards: "It (accurate forecasting of demand, and, therefore, margin) is a massive problem because of the data volumes and complexity. Others have tried and failed, but we persevered."
It provides excellent proof points for the use of Oracle OLAP to solve business problems that require rapid data loading and analysis of large data volumes. The E.on system is currently operating at about 6Tb and is growing rapidly, with 150Gb of new data added every 14 hours. There is a great quote from Lawrence in the OTN PDF explaining what they have achieved using Oracle OLAP Option:
"The analytical power, centralized administration, and scalability of Oracle OLAP have allowed us to process and present data in a way that was not previously possible. This has provided us with an unprecedented depth of understanding of customers’ energy use and the demand for all our products and offerings"
New 11g OLAP Cube Materialized Views tutorial posted onto OTN
Another new tutorial has been added to the Oracle OLAP home page on OTN.
This tutorial is titled 'Oracle OLAP 11g: Setting Up Cube Materialized Views for Query Rewrite'
The tutorial describes how to enable cubes as Cube Materialized Views, and how to enable and troubleshoot Query Rewrite using Analytic Workspace Manager 11.1.0.7. It is intended as a quickstart for intermediate developers.
This tutorial is titled 'Oracle OLAP 11g: Setting Up Cube Materialized Views for Query Rewrite'
The tutorial describes how to enable cubes as Cube Materialized Views, and how to enable and troubleshoot Query Rewrite using Analytic Workspace Manager 11.1.0.7. It is intended as a quickstart for intermediate developers.
Monday, December 8, 2008
Oracle Database 11g: OLAP Essentials - First dates announced
Following the announcement last week about the new Oracle OLAP 11g Oracle University Training Course, the dates and locations for the first classes have been announced.
The very first class will be in Bridgewater, New Jersey, US from 20-Jan-2009 through to 22-Jan-2009.
The first class in Europe will be in Reading, UK from 21-Jan-2009 through to 23-Jan-2009.
The code for the course is D70039GC10 and more details on both events can be found on the Oracle University web site
Be sure to register early if you wish to attend as places are sure to be high in demand.
The very first class will be in Bridgewater, New Jersey, US from 20-Jan-2009 through to 22-Jan-2009.
The first class in Europe will be in Reading, UK from 21-Jan-2009 through to 23-Jan-2009.
The code for the course is D70039GC10 and more details on both events can be found on the Oracle University web site
Be sure to register early if you wish to attend as places are sure to be high in demand.
Thursday, December 4, 2008
New! Oracle OLAP 11g Oracle University Training Course
A brand new OLAP 11g training class has been added to the Oracle University schedule.
Here is a brief synopsis:
Oracle OLAP 11g, a fully-integrated component of Oracle Database 11g, provides a full featured multidimensional data model and calculation engine that is easily accessible to any SQL based business intelligence application or tool.
In this course, students learn to progressively build an OLAP data model to support a wide range of business intelligence requirements. Students learn to design OLAP cubes to serve as a summary management resource for existing SQL table queries. Students also learn to leverage the power of Oracle OLAP by adding rich analytic content to your data model.
Students learn to create sophisticated reports of OLAP data by using simple SQL queries. Students also create and execute OLAP queries in SQL Developer, Oracle Application Express (APEX), and in Oracle BI Enterprise Edition. Students learn to implement cube security, including how to authorize access to cube data and methods for scoping user views of data. Finally, students learn to design OLAP cubes for performance and scalability.
Learn To:
* Design and create an Oracle OLAP data model
* Enable query rewrite to OLAP Cube MVs for relational summary management
* Easily create OLAP calculations that enrich the analytic content of your data model
* Query OLAP data using simple SQL
* Implement cube security
* Efficiently design cubes for performance and scalability
More details and scheduling information can be found on the Oracle University Website
Here is a brief synopsis:
Oracle OLAP 11g, a fully-integrated component of Oracle Database 11g, provides a full featured multidimensional data model and calculation engine that is easily accessible to any SQL based business intelligence application or tool.
In this course, students learn to progressively build an OLAP data model to support a wide range of business intelligence requirements. Students learn to design OLAP cubes to serve as a summary management resource for existing SQL table queries. Students also learn to leverage the power of Oracle OLAP by adding rich analytic content to your data model.
Students learn to create sophisticated reports of OLAP data by using simple SQL queries. Students also create and execute OLAP queries in SQL Developer, Oracle Application Express (APEX), and in Oracle BI Enterprise Edition. Students learn to implement cube security, including how to authorize access to cube data and methods for scoping user views of data. Finally, students learn to design OLAP cubes for performance and scalability.
Learn To:
* Design and create an Oracle OLAP data model
* Enable query rewrite to OLAP Cube MVs for relational summary management
* Easily create OLAP calculations that enrich the analytic content of your data model
* Query OLAP data using simple SQL
* Implement cube security
* Efficiently design cubes for performance and scalability
More details and scheduling information can be found on the Oracle University Website
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