Data and Database Management Software
Software develops data warehouse infrastructures.
Press Release Summary:
Data Warehousing Balanced Configuration Unit for AIX® v1.1 facilitates implementation of IBM DB2 Universal Database® DWE, IBM servers, and IBM TotalStorage® storage products for business intelligence solutions by offering modular building block methodology to constructing data warehouses using open components. Modular scaling allows BCU to maintain balance with initial build, and provides predictable and scalable plan for growth as demands change over time.
Original Press Release:
IBM Data Warehousing Balanced Configuration Unit for AIX, V1.1 Accelerates Development of Data Warehouse and Business Intelligence Infrastructures
At a glance
Data Warehousing Balanced Configuration Unit (BCU) is a methodology that provides a prescriptive approach for building successful data warehouse infrastructures. The BCU provides these key benefits, which were validated in several large customer deployments:
Industry-standard components
Ease of installation and implementation
Balanced performance
Scalability
Fault tolerance
High availability
The BCU for AIX® applies the BCU best practices principles to IBM pSeries® running the AIX operating system with DB2 software, and TotalStorage DS4500. The recommended components are individually optimized for high performance, and together are tested end-to-end to help provide optimal, predictable performance and scalability. By providing a prescriptive, prevalidated solution, the BCU for AIX can significantly help achieve:
Reduced implementation times for BI infrastructure, providing faster time to market
Lower total cost of ownership
For ordering, contact:
Your IBM representative, an IBM Business Partner, or IBM Americas Call Centers at 800-IBM-CALL (Reference: YE001).
Overview
The Data Warehousing Balanced Configuration Unit (BCU) revolutionizes the implementation of IBM DB2 Universal Database® Data Warehouse Edition (DWE), IBM servers, and IBM TotalStorage® storage products for business intelligence (BI) solutions by introducing a modular "building-block" methodology to constructing data warehouses using open components.
In the design and testing of data warehouse solutions with DB2®, the concept of balance has always played a key role. Balance ensures that each of the components of the solution is configured in such a way that all components combine across the infrastructure to optimize workload performance. However, without careful planning, this initial design can often become unbalanced when workload or loading requirements change over time.
The BCU provides a holistic and simplified approach to ensure high performance as the solution scales and changes over time. Nodes in the data warehouse are each based on a similar configuration of operating system, server, software, and storage. This modular design is able to achieve optimized performance by taking full advantage of a DB2 massively parallel system across each of the components.
The BCU originated from the IBM BI Best Practices Team, a group that is grounded in years of experience designing and configuring data warehouse solutions. Using their knowledge and expertise, IBM has created a simplified solution design for customers to properly size, build, and grow their data warehouse with more predictability and less risk, while reducing their time to market.
Business needs for the warehouse are mapped to a pool of resources (the nodes), and as needs increase, you simply add additional blocks to scale.
The modular scaling is a significant advantage. Not only does it allow the BCU to maintain balance with the initial build, but as planned (and unplanned) inevitable changes and more demands occur over time in the data warehouse workloads, the BCU provides a predictable and scalable plan for growth. By choosing the BCU, you gain the security of knowing that your existing infrastructure is based on best practices principles, and that you have a prescriptive, scalable approach to grow the data warehouse while maintaining total system balance that is optimized for its size and workload.
Availability date
June 7, 2005
