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Online analytical processing functions are very powerful. Using them, you can write a simple solution to a complex problem. Additionally, they might lead to improved performance.  

Short Abstract:

This user session is all about experience with a great tool for the DBA, whose database must be online all the time. Using it, one can achieve database version's architecture limits relief or improve performance instead of using regular tools.

 

Abstract:

I heard about admin_move_table() procedure several years ago at an Idug presentation, announcing DB2 9.7 for LUW. I first seemed to me a sidekick of some enthusiast, working in an IBM lab afternoon after everybody else left. Some time later i understood clearly that I was wrong, it resolved to be a crucial tool that has helped me and my fellow DBAs to achieve a list of  goals, dealing with advances in physical data layout, performance and most of all, availability. It is a great tool that provides exceptional usability, it is a Swiss army knife for every LUW administrator.

In this session, i will explain my experience with the procedure, starting with the basics, then topics of use, strengths and shortcomings and some hints. I will provide my view on its evolution from user procedure to more and more system integrated tool.

Short abstract:

We are in the area with data of growing size and complexity. Therefore one of the key imperatives today is to use this data  and get useful information out of it. The session will be focused on how by using predictive analytics, companies can improve the business outcome and how you as the user can apply advanced algorithms and techniques to solve a variety of business problems.

 

Abstract:

We are in the area with data of growing size and complexity. Therefore one of the key imperatives today is to use this data  and get useful information out of it. The session will be focused on how by using predictive analytics, companies can improve the business outcome and how you as the user can apply advanced algorithms and techniques to solve a variety of business problems. Predictive analytics enables you to access a variety of data sources such as data warehouses, databases, Hadoop distributions or flat files and by using analytical techniques identify patterns and deploy predictive models into operational systems. Systems and people can than use these patterns and models to derive insights that enable them to consistently make the right decision at the point of impact.

Predictive analytics can be used in several different industries and various areas such as customer churn detection, profitability calculation, fraud detection, next best action analyses, anomaly detection, cross-sell/up-sell and many others.