Rise of the Citizen Information Steward

April 6, 2018

Rise of the Citizen Information Steward

By Scott Cappiello

I recently attended the Gartner Data & Analytics Summit, which is always an interesting opportunity to follow latest trends in our space. During the conference, I attended a talk by Gartner analyst Guido De Simoni entitled “How to Create an Impactful Data Quality Program.” I thought it would be a good opportunity to learn how enterprises are currently thinking about initiating and organizing their data quality initiatives.

What struck me during the talk was the use of the term “citizen information steward” which I had not heard before. Of course Gartner has popularized the term “citizen data scientist” — which is roughly someone whose day job is not statistics and analytics, but nonetheless employs data science techniques in the course of performing their job within a business function of an organization (my definition, not theirs). So a “citizen” information steward is a riff on this concept, reflecting the need to have individuals in the business own the responsibility of monitoring, measuring data quality, etc. Perhaps most importantly, citizen information stewards are in the best position to solve data quality problems that are new and emerging.

In the talk, De Simoni further presented a model where there is some form of centralized coordination of such citizen information stewards, reporting to a Chief Data Officer or some other governance structure. But the essential point in my mind was that impactful data quality programs require that mix of business knowledge and information skills.

The concept of citizen information stewards also reflects the reality, which Gartner corroborates, that Data Quality is ultimately a business problem, not an IT problem. The knowledge and perspective required to successfully execute data quality initiatives lies in the heads of individuals in the business units themselves. These are the people we need to support with enabling technology.

And we clearly see this dynamic playing out in the Paxata customer base. Several customers use self-service data preparation to collect data from third-parties, performing data quality assessments before incorporating these data feeds into analytics. Because of the variety of sources and the fact that the data originate in an external organization, the resulting data quality also varies widely. Data quality rules are volatile and thus are difficult to encode by a centralized IT team — subject matter experts in the business are required to tweak and maintain the data quality assessments.

We have other customers who use Paxata to assist with application migrations. These customers need to assess data quality before moving data from the legacy to new application environment. Again, the ability to conduct these assessments and remediate any data quality issues is in the hands of business analyst experts.

Now I know that these “PaxPros” also hold the title of “citizen information stewards”!

 

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