There are several data warehouse project management metrics worth considering. I'll discuss the top three.
By submitting your email address, you agree to receive emails regarding relevant topic offers from TechTarget and its partners. You can withdraw your consent at any time. Contact TechTarget at 275 Grove Street, Newton, MA.
Business return on investment (ROI)
The best metric to use is business return on investment. Is the business achieving bottom line success (increased sales or decreased expenses) through the use of the data warehouse? This focus will encourage the development team to work backwards to do the right things day in and day out for the ultimate arbiter of success -- the bottom line.
The second best metric is data usage.You want to see the data warehouse used for its intended purposes by the target users. The objective here is increasing numbers of users and complexity of usage. With this focus, user statistics such as logins and query bands are tracked.
Data gathering and availability
The third best data warehouse metric category is data gathering and availability. Under this focus, the data warehouse team becomes an internal data brokerage, serving up data for the organization's consumption. Success is measured in the availability of the data more or less according to a service level agreement. I would encourage you to use these business metrics to gauge your success.
Other, less important data warehouse project management metrics are technical performance indicators like up time, cycle end times, successful loads and clean data levels. Speaking of clean data levels, I have a full white paper about measuring and improving data quality metrics for data warehouses -- email me for more information. In short, you want to eliminate intolerable defects – as defined by the data stewards. These defects come in 10 different categories: referential integrity, uniqueness/deduplication, cardinality, subtype/supertype constructs, value domains/bounds, formatting errors, contingency conditions, calculations, correctness and conformance to "clean" set of values.
Related Q&A from William McKnight
Are business intelligence certifications worth it? Get certification advice from our business intelligence expert, William McKnight.continue reading
Get examples of how data mining is used in vertical industries, such as retail, manufacturing, healthcare, financial and telecommunications.continue reading
Learn the advantages and disadvantages of data mining tools and of implementing data mining technology.continue reading
Have a question for an expert?
Please add a title for your question
Get answers from a TechTarget expert on whatever's puzzling you.