Data Model Scorecard
by Steve Hoberman download a PDF brochure
Description
Aim, wind, and gravity influence an arrow’s trajectory, much the same way as deadlines, skills, and biases influence a Data Model’s trajectory, strongly impacting whether a model will reach its target of appropriately representing a Business solution. The archer’s score can be quickly calculated and we can easily see the success or failure of her work. This is where the analogy ends however, because often we do not measure the strengths and weaknesses of our Data Models, leaving much up to interpretation, perception, and the test of time. After years of reviewing hundreds of Data Models, I have formalized a set of Data Model quality criteria into what I call the Data Model Scorecard™. The Scorecard contains all of the criteria for highlighting strengths and identifying areas for improvement in our designs. This one day course will go into detail on the Scorecard, and provide techniques and tips for improving the quality of your models.Each participant will receive a copy of all presentation material and a copy of the book “Data Modeling Made Simple”, by Steve Hoberman.
What you will learn
- Appreciate the need for an objective measure of data model quality
- Apply the Scorecard to different types of models. This includes subject area, logical and physical models, and both relational and dimensional designs
- Introduce the Scorecard into a development methodology and your company culture
Main Topics
- The Importance of data model quality
- Weaknesses with traditional data model reviews
- Scorecard key characteristics
- Scorecard categories
- Introduce the Scorecard into your organization
- Scorecard challenges