Time marches on and soon the collective retirement of the Kimball Group will be upon us. In my final Design Tip, I would like to share the perspective for DW/BI success I’ve gained from my 26 years in the data warehouse/business intelligence industry. While data warehousing has been around now for a long while, there […]

Countless organizations have created mature dimensional data warehouses that are considered tremendous successes within their organizations. These data warehouse environments support key reporting and analysis requirements for the enterprise. Many are capable of supporting self-serve data access and analysis capabilities for disparate business users. Nonetheless, regardless of the success achieved by these dimensional data warehouses, […]

In most cases, metadata is a neglected area of the DW/BI system; however, an increasing number of DW/BI teams have made positive strides in delivering business metadata to their users. This Design Tip looks beyond the business metadata to suggest several opportunities for leveraging ETL process metadata to improve data warehouse operations. The goal is […]

There are three fundamental types of fact tables in the data warehouse presentation area: transaction fact tables, periodic snapshot fact tables, and accumulating snapshot fact tables. Most DW/BI design teams are very familiar with transaction fact tables. They are the most common fact table type and are often the primary workhorse schema for many organizations. […]

Regular readers know we stress the importance of focusing on business requirements when designing dimensional data models to support the data warehouse/business intelligence (DW/BI) environment. As described in Design Tip #157, it is critical to include business partners in the dimensional design process. But including business representatives on the design team obviously increases the size […]

The Kimball Group has always stressed the importance of keeping a keen eye on the business requirements when designing dimensional data models for the data warehouse/business intelligence (DW/BI) environment. Gathering business requirements is typically undertaken just prior to beginning the dimensional data model design process. Design Tip #110 is a reminder of requirements gathering do’s […]

Keeping tight control over the scope of your data warehouse/business intelligence (DW/BI) program is an important ingredient for success. Surprisingly, in some organizations it’s equally important to ensure that the program doesn’t suffer the theft of its scope after an otherwise good plan has been developed. It’s nearly impossible to tackle everything at once in […]

Some organizations have adopted a data warehouse architecture that includes an atomic third normal form (3NF) relational data warehouse. This architecture, often called the hub-and-spoke or Corporate Information Factory (CIF), includes a data acquisition ETL process to gather, clean and integrate data from various sources. Atomic data is loaded into third normal form data structures, […]

Most organizations implementing a new data warehouse/business intelligence (DW/BI) environment are replacing or “sunsetting” a legacy analytic/reporting system. This environment may be an older data warehouse, a single or series of departmental data marts, or a collection of analytic/reporting environments cobbled together using tools such as Access and Excel. Some may be officially sanctioned platforms; […]

The logical dimensional model should be developed jointly by representatives from all interested groups: business users, reporting teams, and the DW/BI project team. It is important that the appropriate individuals are represented on the dimensional data model design team as described in Design Tip #103 in order to achieve an effective design. The best dimensional […]