What Is a Data Strategy?
Imagine this familiar situation: as an analyst in your company, you've been tasked with the daunting task of assimilating all of your organization's data to collect unique and comprehensive insights. But this is easier said than done. Business development has much of their data siloed into a proprietary CRM solution, finance keeps theirs hidden away in spreadsheets, and application developers have SDK and IoT data streaming in to separate on-prem databases with no fault-tolerance built in. On top of that, compliance and security issues were never even considered. There seems to be no rhyme or reason to how everything works, it's impossible to get a unified view from all of the enterprise data. And "data science" is mostly done around the organization by way of sampling data from different pools and then making a "seat of the pants" guesstimate from arbitrarily sampled data, which is neither productive nor reliable. What a mess!
You need to have a strategy for your data. How will you do this? What data will you collect? Which data will you store — and where? Who is the audience for your data? Who consumes your analyzed data? What kind of access controls and permissions do you want to have on your data?