Design Tip #180 The Future Is Bright

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 cropped-cropped-filo01_cartoonized_42.jpgand 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 1980. By Ralph Kimball  © Kimball Group. All rights reserved.

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Design Tip #179 Key Tenets of the Kimball Method


cropped-cropped-filo01_cartoonized_42.jpgMost 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.
 By Joy Mundy – © Kimball Group. All rights reserved.

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Design Tip #168 What’s in a Name?

It seems like a small thing, but names are important. Good names for tables and columns are particularly important for ad hoc users of the DW/BI system who need to find the objects they’re looking for. Object names should be oriented to the business users, not the technical staff.  By Joy Mundy  July 21, 2014 © Kimball Group. All rights reserved.

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Design Tip #167 Complementary Fact Table Types

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. Many teams have also incorporated periodic snapshot fact tables in their presentation areas. Fewer organizations leverage the accumulating snapshot fact table. Design teams often don’t appreciate how an accumulating snapshot fact table can complement transaction and/or periodic snapshot fact tables. June 17, 2014 – © Kimball Group. All rights reserved. Bob Becker

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13 Tips for Basics of DW and Dimensional Modeling

Imagine you’re working for a company that has accumulated a tremendous amount of transaction data. The business users want to perform all sorts of analysis, monitoring and analytics on the data. Some OLTP developers might reply with, “Just create views or stored procedures to query all the data the way the users want.” Many companies initially take that approach – however, just like certain technologies and system hardware configurations don’t scale well, certain methodologies don’t scale well either. Fortunately, this is where data warehousing and dimensional modeling can help. In this article, I’ll provide some basic information for developers on the basics of data warehousing and dimensional modeling – information that might help you if you want to provide even more value for your company. By Kevin S. Goff, a Microsoft SQL Server MVP

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Design Tip #164 Have You Built Your Audit Dimension Yet?

One of the most effective tools for managing data quality and data governance, as well as giving business users confidence in the data warehouse results, is the audit dimension. March 3, 2014 © Kimball Group. All rights reserved.

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Design Tip #157 Involve Business Representatives in Dimensional Modeling

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 environment.  Bob Becker on June 28, 2013.

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