10 Winter Housekeeping Tasks for Data Modelers

It’s that time of year after the winter holidays that my mind turns to decluttering and organizing my house. It only seems natural to extend that attitude to my workplace. Here are ten tasks for data modelers to start the New Year off with a clean modeling workspace.

  1. Clean up history. – Whether you store your data models in project folders or repositories, you probably have accumulated many versions of data models. These unneeded models clutter your model libraries and degrade the retrieval time of  models from the repository. Mark and keep needed versions and delete the unneeded versions.
  2. Say good-bye to the dead models. – I tend to model scenarios in the early phases of projects. I often create subsets of models to demonstrate a point. I may model some what-ifs when bringing models together. Now is a good time to walk through model libraries and get rid of these unneeded models before they multiply even more.
  3. Validate domains and naming standards. – Domains and naming conventions generally stand the test of time. However, time and technology changes can introduce needed changes. January is a good time to look at your standards and evaluate how well they work with your existing or emerging data technologies. It is OK to make an adjustment when needed.
  4. Do some quality assurance. – In the typical year, multiple data modelers working on multiple projects create and update multiple data models. This tests even the most disciplined staff in maintaining standards. Make it a practice to walk through some data models checking them for compliance. This is the perfect chance to find shortcomings or errors in your standard modeling and quality assurance practices.
  5. Try some new modeling features. — There is a good chance that your data modeling software released a new version this past year. Make it a point to try out one of the new and improved features in your toolset. Software vendors are constantly improving their products to give their customers more productivity.
  6. Setup modeling templates or themes. – Consistency in data modeling makes modelers’ work easier and the models more easily readable to our clients. Many data modeling toolsets support the creation of templates and themes that provide this consistency. Colors, fonts, appearance, display and other options are set once and reused.
  7. Upgrade your modeling software. — Workload keeps us from upgrading to the newest release. I am cautious and wait 3-6 months after a major release for the bugs to fall out. Now is a good time to get serious about moving forward to a newer release. Enjoy new features and keep yourself ahead of the software obsolescence cycle.
  8. Read your manuals to keep current. – Never get too comfortable with your software. It is bound to change. Menus, drop-downs, features, defaults and much more change with each release.  Don’t just upgrade your software. Read the release notes, help files, software tips, technique guides, etc. to make sure you understand how to best use your tool.
  9. Sync your models to the database. – This is a very important process to keep your models accurate and relevant to you and your client base. If you have been lax in syncing throughout the year, there is no better time than to do it than now. Nothing makes your model more unusable than discrepancies that lead to distrust by developers and project team members.
  10. Plan your training for the year. – Once you have put your modeling house in order, it’s a good time to plan training for the upcoming year. Lay out the workshops, brown bags, and classes you will offer your clients and fellow modelers. Take special care in setting up a training plan for yourself that keeps your skills up-to-date and your work responsive.
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