K
Kathleen Martin
Guest
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Data governance has had more than its fair share of spins through the hype cycle. It burst on the scene in the late 90s with metadata management as a seemingly silver bullet for making data actionable and trustworthy.
A decade and a half later, the industry was littered with failed, C-suite driven initiatives to try and manually catalog every data asset. So many data teams drowned it was unfathomable any would ever dare again set sail on such a hubristic odyssey.
And yet, many data teams are convinced that today the tides have turned!
Data governance remains vital, perhaps even more so as data volume levels rise and disruptive tidal waves of data regulation such as GDPR wash across the industry.
Driven by these outside forces, data teams have started to convince themselves that maybe, just maybe, machine learning automation can tame the storm and make cataloging data assets possible this time around.
Unfortunately, many of these new data governance initiatives are destined to sink by focusing on technology to the detriment of culture and process.
The reality is for teams to improve their data governance posture they need to not only have visibility into their data, but also treat it like a product, be domain-first, and establish data quality as a prerequisite.
Treat Data Governance Like a Product — Don’t Treat a Product Like its Data Governance
Data governance is a big challenge, and so it’s tempting to try and tackle it with a big solution.
Typically, data governance initiatives will start with a data leader decreeing the seemingly agreeable objective, “We will catalog all the things and assign owners for all of our data assets end-to-end so it is accessible, meaningful, compliant, and reliable.”
The first problem with this initiative is how it originated. Just as successful companies are customer focused, data teams must focus on their data consumers and internal customers, too.
I guarantee no one in the marketing department asked you for a data catalog. They asked for useful reports and more reliable dashboards.
No one in the compliance department asked for a data catalog either. They asked for visibility into the location of regulated and personally identifiable information and who has access.
Continue reading: https://www.datanami.com/2022/05/24/the-rise-and-fall-of-data-governance-again/
Data governance has had more than its fair share of spins through the hype cycle. It burst on the scene in the late 90s with metadata management as a seemingly silver bullet for making data actionable and trustworthy.
A decade and a half later, the industry was littered with failed, C-suite driven initiatives to try and manually catalog every data asset. So many data teams drowned it was unfathomable any would ever dare again set sail on such a hubristic odyssey.
And yet, many data teams are convinced that today the tides have turned!
Data governance remains vital, perhaps even more so as data volume levels rise and disruptive tidal waves of data regulation such as GDPR wash across the industry.
Driven by these outside forces, data teams have started to convince themselves that maybe, just maybe, machine learning automation can tame the storm and make cataloging data assets possible this time around.
Unfortunately, many of these new data governance initiatives are destined to sink by focusing on technology to the detriment of culture and process.
The reality is for teams to improve their data governance posture they need to not only have visibility into their data, but also treat it like a product, be domain-first, and establish data quality as a prerequisite.
Treat Data Governance Like a Product — Don’t Treat a Product Like its Data Governance
Data governance is a big challenge, and so it’s tempting to try and tackle it with a big solution.
Typically, data governance initiatives will start with a data leader decreeing the seemingly agreeable objective, “We will catalog all the things and assign owners for all of our data assets end-to-end so it is accessible, meaningful, compliant, and reliable.”
The first problem with this initiative is how it originated. Just as successful companies are customer focused, data teams must focus on their data consumers and internal customers, too.
I guarantee no one in the marketing department asked you for a data catalog. They asked for useful reports and more reliable dashboards.
No one in the compliance department asked for a data catalog either. They asked for visibility into the location of regulated and personally identifiable information and who has access.
Continue reading: https://www.datanami.com/2022/05/24/the-rise-and-fall-of-data-governance-again/
