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With the introduction of Db2 V11.5, we have now finished with delivering new functionality on Db2 V11.1. Over the past few years we have some very significant feature paks, adding a wealth of new high value capabilities to Db2. In this session we will go through the key new capabilities associated with each feature pak. This will include key BLU enhancements, pureScale enhancements, NoSQL enhancements, security enhancements and more. Many of these new capabilities form the base for new capabilities in Db2 V11.5. This session will help raise awareness of the many enhancements so clients can get as much value out of Db2 V11.1.

Db2 uses a cost-based query optimizer that is vitally dependent on appropriate statistics to generate efficient execution plans. However, it is often not obvious when to use which of the many options for the RUNSTATS command to collect the "right" kind of statistics. This session presents a set of practical examples to explain how different types of statistics affect query optimization. We also discuss RUNSTATS measurements to illustrate the overhead of collecting more advanced statistics. As a result you will be able to determine when it is worthwhile to use more advanced concepts such as distribution statistics, column group statistics, or statistical views. Provide the right steroids to the optimizer to boost performance!

In 2019 we released a significant new release of Db2 and delivered a great deal of new capabilities including new logging options, enhancements to our columnar support, enhancements to pureScale, leveraging machine learning within our optimizer and much more. In addition to a significant number of engine enhancements, we have also introduced many other capabilities including enhancements to Q-Replication based solutions, Natural Language Query and more. In this session we'll take a look at the key enhancements which were delivered with V11.5 and also a peak ahead to our first feature pak on top of V11.5. We will also include a couple of demos of some of the great new capabilities.

Watson Machine Learning for z/OS evolves as fast as data science and there are new features every few months. This presentation will review all the new functionalities as well as dicussing about the life cycle of a machine learning model on z/OS. 

Continuous delivery and function levels are key enhancements of Db2 for z/OS. This session demonstrates the rationale behind these keywords and their consequences in customer environments. In addition, this presentastion outlines the latest Db2 12 for z/OS enhancements. The focus is how users can exploit and adapt these new features and functions. Also it will be outlined what consequences and tradeoffs the users have to consider. In addition, some important functionalities not tied to a specific function level are illustrated.

Just like Newton explained the attraction between objects by the Law of Gravity, we see a metaphor in data and applications. As datasets grow, they become harder to move and are likely to attract applications rather than moving data to the applications. As we all know, data on IBM Z both is significant in size as well as in freshness. We might ask ourselves why do we need to ETL, morph, and manipulate data off the platform to another place? And although this paradigm already exists for many years, we see that IBM has recently put together a significant amount of technologies that makes it worth while to re-evaluate Enterprise Data strategy. In this session you'll learn how data on Z might fit in such Enterprise Data Strategy while complying to a hybrid multi-cloud approach