Certify Your Data Assets to Avoid Treating Your Data Engineers Like Catalogs

Too Long; Didn't Read

Say it with me: data engineers are not a data catalog. You would be hard pressed to find “answering multiple Slack messages every week about which tables are good to use for this report,” in their job description, but it happens nonetheless. Data analysts aren’t psychic. Yet, they are often placed in the position of having to intuit if the data being piped is trustworthy. Data certification can help. Here's how it works. Step 1: Build out your data observability capabilities Step 2: Determine your data owners Step 3: Understand what "good" data looks like Step 4: Set clear SLAs for your most important data sets Step 5: Develop your communication and incident management processes Step 6: Determine a mechanism to tag the data as certified Step 7: Train your data team and downstream consumers