With so many efforts focused on restoring systems, applications and workloads, it is easy to miss an important piece: the data that makes business processes possible. A fully restored system is as good as offline if you don’t have the data required to work.
Let’s face it: in the past, technology drove business capabilities. Today, data does. Weirdly, the technology is the easy part. The hard part is trying to figure out what to do with the data, our most valuable asset. We can replace ‘stuff’. Data, once stolen, corrupted or locked, not so much.
Literature and practice in this space is not well defined. If you are looking for a standard or framework on the data lifecycle, it may be hard to come by. Instead, let’s use a mixture of a few models out there to guide us through the conversation.
Data Creation/Tagging
Keep this old saying in mind with data: garbage in, garbage out. Sounds easy, but one would be amazed at how much garbage is out there, creating downstream impacts that are difficult to untangle. Systems of record can be an incredible trouble point if not governed and managed well.
Pro tip: don’t be ‘penny-wise, pound-foolish’ on this initial first step. Spend the extra effort to get ‘clean’ data into your systems and you will have an overall more secure and resilient system. And tag it well. It makes your life easier. Also, the tech resources used to process and normalize the data will love what could be an easier workload.
Data Collection/Acquisition
Very closely rel ..
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