Wiley, 2013 Tools and Utilities NOTE: You may need to “Save Link As” to download the files. Chapter 3 Sample date dimension spreadsheet Download Correction to Figure 3-13: The first heading in the lower report shown in Figure 3-13 should read “Calendar Week Ending Date,” just like the top report in that figure. Correction to [...]| Kimball Group
Ralph Kimball introduced the data warehouse/business intelligence industry to dimensional modeling in 1996 with his seminal book, The Data Warehouse Toolkit. Since then, the Kimball Group has extended the portfolio of best practices. Drawn from The Data Warehouse Toolkit, Third Edition, the “official” Kimball dimensional modeling techniques are described on the following links and attached [...]| Kimball Group
Data warehousing has never been more valuable and interesting than it is now. Making decisions based on data is so fundamental and obvious that the current generation of business users and data warehouse designers/implementers can’t imagine a world without access to data. I’ll resist the urge to tell stories about what it was like before [...]| Kimball Group
Most of the guidance in the Kimball method for designing, developing, and deploying a DW/BI system is just that: guidance. There are hundreds or thousands of rules in the Kimball Group’s many books, and I confess to having bent many of those rules over the decades, when faced with conflicting goals or unpleasant political realities. [...]| Kimball Group
Time marches on and soon the collective retirement of the Kimball Group will be upon us. At the end of 2015 we will all retire. 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 [...]| Kimball Group
For my final Design Tip, I’m returning to a fundamental theme that’s not rocket science, but too often ignored: business-IT collaboration. If you buy into the proposition that the true measure of DW/BI success is business acceptance of the deliverables to improve their decision-making, then buying into the importance of collaboration should be easy. Achieving [...]| Kimball Group
Dimensional data models have been around for a very long time, almost certainly tracing their lineage back to the original Data Cube project between Dartmouth and General Mills in the late 1960s. The appeal of dimensional modeling stems from the obvious simplicity of the models and the natural way in which both business people and [...]| Kimball Group
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, [...]| Kimball Group
Over the years, we’ve worked with countless exemplary DW/BI project team members: smart, skilled, dedicated, and motivated, coupled with a healthy dose of mutual trust, respect, and camaraderie with their teammates. Teams with members who possess these characteristics tend to fire on all cylinders, with the resulting whole often greater than the sum of the [...]| Kimball Group
Predictive analytics is the name for a broad range of analysis techniques used for making predictions about future behavior. Credit scoring, risk analysis, and promotion selection are among the many applications that have proven to drive revenue and profit. It is worth taking a look at the “predictive analytics” section of Wikipedia to appreciate the [...]| Kimball Group
We characterize the ETL system as a back room activity that users should never see nor touch. Even so, the ETL system design must be driven from user requirements. This Design Tip looks at the design of one bit of ETL plumbing – the fact table surrogate key pipeline – from the perspective of business [...]| Kimball Group
An ever-growing set of data storage technologies offer advantages to the data warehouse architect that look pretty magical. How can you figure out what to do? Should you stick to the tried-and-true relational databases to host your data warehouse? Should you use cubes? Or should you move to the latest and greatest data management solutions [...]| Kimball Group