Keith  Laker

Keith Laker

Senior Principal Product Manager, Data Warehousing


Oracle Partitioning - Did You Think It Couldn’t Get Any Better?

Oracle Partitioning is one of the most proven and successful functionalities of Oracle Database, managing hundreds of terabytes or even petabytes of data. After more than two decades of development, the newest generation of Oracle Database introduces yet again numerous and significant enhancements. Oracle Partitioning further aligns with any business requirement, making it even better and more effective for any kind of environment—from pure online transaction processing (OLTP) to data warehousing and big data environments. Attend this session to learn the latest and greatest about Oracle Partitioning.

SQL Pattern Matching Deep Dive

This session will explore the new Database 12c SQL Pattern Matching feature. This is a very powerful feature, which can used to solve a wide variety of business and technical problems. 
Using a live demo we will look at how to solve typical pattern matching business problems that can be solved very efficiently using MATCH_RECOGNIZE. To help you understand the basic mechanics of the MATCH_RECOGNIZE clause the demo will look at the new MATCH_RECOGNIZE related keywords in the explain plan such as DETERMINISTIC, FINITE and AUTO. 
We will explore the key concepts of deterministic vs. non-deterministic state machines, greedy vs. reluctant quantifiers and how to use the built-in debugging measures. Finally, we will review typical issues such as back-tracking. At the end of this session you should be able to: 
- Recognize the new key words in the explain plan 
- have a basic understanding of state machines 
- Understand differences between greedy and reluctant quantifiers 
- Learn how to void back-tracking scenarios

An Introduction to Approximate Query Processing in Database 12c

Business intelligence applications extensively use aggregate functions such as distinct counts to provide answers to common business questions. For some specific types of queries, such as when the data set is extremely large, providing exact answers can be resource intensive: for example, counting the number of unique customers sessions on a website. 
Approximate query processing is mainly used in data discovery type applications to return quick answers to explorative queries. Users typically want to locate interesting data points within large amounts of data and then drill to uncover further levels of detail. For these explorative-type queries, quick responses are more important than exact values. 
This session will use Oracle Database 12c to explore these new features with the help of live demonstrations. It will explain how approximate query processing works along with the most important new keywords. At the end of this session you should be able to:
- Understand how approximate processing works 
- Understand the significance of error rates and confidence levels 
- Recognize key benefits of using approximate query processing


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