Get your data warehouse into better shape! Use this matrix to find common errors and fixes for them.
12 items found
An evaluation of relational database systems determines the most suitable engine for a data warehouse. This report is an example of a comparative analysis of data warehouse database tools.
How do you select the best data extraction/transformation toolset for your data warehouse? Evaluate features, functionality, vendor reputation... the works. Follow the example set by this robust tool evaluation.
Even though you've built the perfect data warehouse, it's better to be safe than sorry if something goes wrong during its operation and you need to restore the original data files. Take the time to document your backup and recovery procedures, as in this example.
This example will help you put in place logical as well as physical database design standards for building data warehouses using Business Objects.
What is the best way to get data from the legacy system(s) into the new system? Design your conversion routines to organize the process.
What data should you keep in a Data Warehouse and why? This form helps you identify the needed data and its associated characteristics in relation to your business requirements.
A handy spreadsheet for recording Data Warehouse QA issues, from data transformation to report generation problems.
Here's a template, with attached examples, for testing your Data Warehouse canned queries (analytical reports).
Need help selecting a Data Warehouse toolset? You must consider many factors regarding vendor service and reputation, tool functionality and tool quality against your technical and business requirements when selecting Data Warehouse construction and implementation tools. Let this matrix guide your selection.