Db2

Introduction

Implementing industry models can help accelerate projects and reduce risk in a wide variety of industry sectors when enterprises develop and implement business intelligence applications.

The IBM Industry Models solutions cover a range of industries that include banking, healthcare, retail, and telecommunications. The IBM Industry Models solutions provide you with an extensive and extensible data model for your industry sector. Use the logical data model as provided by IBM to build a physical model that is customized for your reporting requirements, and then deploy and populate a best practice IBM DB2® 10.5 with BLU Acceleration database.

This paper introduces the logical data model concepts and then focuses on what you must do to transform a non-vendor-specific logical data model into a best-practice production IBM DB2 10.5 with BLU Acceleration schema.

Specifically, this paper uses the IBM Industry Models Banking Data Warehouse model pertaining to Involved Party and Social Media entities. It guides you through the recommended process for transforming the logical data model for dimensional warehousing into a physical database design for production use in your environment.

The key steps described are:

• Create a subset of the data model from the supplied logical data model.
• Prepare the physical data model for deployment as an IBM DB2 10.5 with BLU Acceleration schema.
• Generate the DDL to deploy the schema to DB2.

Using the recommendations in this paper can help you transform an IBM Industry Model Banking Data Warehouse dimensional warehouse solution into a database that is ready for production use.

IBM DB2 10.5 with BLU Acceleration Summary

BLU Acceleration is a new collection of technologies for analytic queries that are introduced in DB2 for Linux, UNIX, and Windows Version 10.5 (DB2 10.5). At its heart, BLU Acceleration is about providing faster answers to more questions and analyzing more data at a lower cost. DB2 with BLU Acceleration, also known as DB2 BLU, is about providing order-of-magnitude benefits in performance, storage savings, and time to value.

These goals are accomplished by using multiple complementary technologies, including the following technologies:

• Column-organized tables mean that I/O is performed only on those columns and values that satisfy a particular query.
• Actionable compression on the column data preserves order so that the data can be used without decompression, resulting in huge storage and CPU savings and a significantly higher density of useful data held in memory.
• Parallel vector processing, with multi-core parallelism and single instruction, multiple data (SIMD) parallelism, provides improved performance and better utilization of available CPU resources.
• Data skipping avoids the unnecessary processing of irrelevant data, thereby further reducing the I/O that is required to complete a query.

These and other technologies combine to provide an in-memory, CPU-optimized, and I/O-optimized solution that is greater than the sum of its parts.

BLU Acceleration is fully integrated into DB2 10.5, so that much of how you leverage DB2 in your analytics environment today still applies when you adopt BLU Acceleration. The simplicity of BLU Acceleration changes how you implement and manage a BLU-accelerated environment. Gone are the days of having to define secondary indexes or aggregates, or having to make SQL or schema changes to achieve adequate performance.

Download the full report for more on Deploying the IBM Banking Data Warehouse to IBM DB2 10.5 with BLU Acceleration.
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