Data Strategy for Building Data Warehouses

​by ​Gwen Garrison, PhD

As we head into ASAE's Annual Meeting in early August, the insights we've shared this month become even more valuable. This event presents a unique opportunity to put our networking strategies into action, forge new connections, and strengthen existing relationships. Whether you're an experienced professional or just starting out, the principles of effective networking—preparation, authenticity, respect, and continuous learning—are essential to making the most of this gathering.

As a data strategist, I am asked what are the strategic considerations when considering a data warehouse? A simple internet search will yield various pieces of advice. From my experience and continued review of available options, here are my four strategic tips:

Start with a goal in mind. Ask yourself, what questions or key performance indicators (KPIs)does it help me answer? What business activities matter to you, where tracked and connected data from various systems can provide a continuous narrative to tell the organizational story over time? This can be a trend line of how many members you have and then connected to membership campaign drives or the introduction, adoption, and use of new association products.
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1. Build a team to support, maintain, and use the data. A DW can become a fancy tech decoration if there isn't a team that supports, maintains, and uses the data to support decision making at all levels--from the unit to the board. This team, for most associations, will include internal business and technical operations experts connected to reputable and skilled vendors but also needs dedicated analysts who can conduct research, build dashboards, and create succinct organizational data stories.
2. Be selective on what data should be kept and maintained. As with most technology data warehouses (DW) can be cloud based and support robust security requirements. But it shouldn't be the place where you 'stuff' all your organizational data. Consider a DW like a safety deposit box where you keep your most important and valuable papers and items of worth. This, of course, will be your data but it is the most important data you have, not everything.
3. Develop and maintain data governance efforts that support data warehousing. These routines are not so different from data governance policy and procedure efforts that support direct business data operations such as master data and integration. But when it comes to data warehousing, documenting your data eco-system, applying classification schemas, and describing transformations that support useful research and organizational data stories are key to gain the benefits of the warehouse data.
   
   

Finally, as you consider your journey in digital transformation of your own technology, serious and strategic consideration of data warehousing will bring benefits to business objectives from direct research to business intelligence.