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By Mohit Sahgal, Vice President of Analytics

 

In a recent survey of some 88 cross-industry Chief Data Officers (CDOs) reconfirmed several pervasive data management challenges. Specifically, “the rapid realization of the importance of data quality (#1 at 93%), governance, (#2 at 89%) and management (#3 at 86%) in achieving, strategic objectives and advantage.” While perhaps not too surprising for many of us in the field, actively working to help organizations remediate these risks, these top three investment priorities highlight the complexities of managing data, and maximizing its utility, for whatever initiatives each organization may have respectively.

One interesting correlation between the first three investment priorities and the second three is that you can’t control (read: curate) data that has yet to be “mastered”. That is, if you don’t have mastery of the data first, then to what are the data quality, governance, and management curations being applied? We’ve explored this point before, in our perspective on “Preferred Practices in Master Data Management and Data Governance Implementation.”

A striking observation was that data lineage (#15 at 71%) was found at the bottom of the list. An unfortunate reality that tracing the origin or official record of the data, transformations, and various “hops” can be super difficult. Yet, with the right automation, and orchestration, technologies, it can be easier, effective and cost-efficient.  Ironically, without knowing data provenance how do you apply the right controls, without which place the organization at risk.

Funding, and senior management’s tolerance for expensive, and often lengthy, data remediation projects is limited. At least one improvement every organization can make is aligning data management initiatives to specific business imperatives. Knowing the materiality, cost, and return of each risk remediation is essential to prioritization; that is, knowing where to start and how to start can often be the difference between wise and wasteful decisions.

And, finally, the article recognizes “data as a strategic asset”. Was it not already? No, actually.  Many companies continue to still treat data as a waste product. For the most part, data remains a senior management annoyance. Yet a disgruntled customer social media posting, or a regulatory fine or two for customer mismanagement, or a CFO questioning whether or not they should attest to the company’s financial results, are instant reminders that “The Data” has always been an organization’s most precious asset. Processes simply break without quality data.  In summary, the article reconfirms for everyone: “good data = good business.”