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Who Owns the Data?

by Svetlana Sicular  |  February 17, 2016  |  2 Comments

The greatest meaning of “big” in “big data” is the role of data in the digital economy. The question who owns the data is big too. With IoT and cloud, data ownership will matter soon even to those who don’t care now.

And there is no universal answer — data ownership is culture-specific. In some cases, nobody wants to own the data, in other cases, everybody wants to grab a piece (“it’s mine!” although the “owner” didn’t even know before you asked that this data existed). With participating external parties, things are even more complicated: for example, one party might learn that it does not have rights for the data it considered its own.  To solve ownership — but not alleviate the problem! — some organizations decide that data belongs to their customers, citizens or third-parties, and the company is only a custodian.

What successful approaches to data ownership have I seen?

The universal first step is establishing an institute of data governance.  I just published a research note on how to do this: EIM 1.0: Setting Up Enterprise Information Management and Governance. You don’t have to call it “data governance.” It could be “data advocacy” or simply a name reflecting the nature of taking care of data. It should resonate with a specific organizational or ecosystem culture.

The next steps would be specific to the culture and the nature of the business: figuring out what data is most vital. This will narrow down data ownership to the decisions that matter (which will save a lot of grief and lots of hours).

The versions of data ownership I have seen:

  • Information governance mechanism resolves it through top-down decision making.
  • Subject matter experts make a step forward to own the data on which they are SMEs (bottom up).
  • Application business owners are offered to own the data, accept it and take it (unexpectedly) seriously, which is fruitful to everyone.
  • Data operators become de-facto data owners (which could be a solution, but could be a greater problem). Transparency in what is being done with data and explicit data access rules make it a solution.
  • When data ownership is hard to resolve on the high level, going more granular, and resolving data elements’ ownership (which is usually more obvious), answers the question.
  • A business executives assumes data ownership. The worst case is when such ownership belongs to an executive who has control, but has no idea about data. E.g. the executive owns the data, but does nothing because executives are busy doing other things. The best case is when this executive is a sponsor of data-related work.

The ownership is just part of taking care of the data. Look at the root of the issue: who can do what with which data without stepping on each other’s toes, avoid troubles with regulations and ensure you put data to work ethically. Data governance often starts with compliance and ownership, but — unavoidably — it ends up finding value in the data, which is big in the digital economy.


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Category: analytics  data-and-analytics-strategies  data-governance  data-paprazzi  technology-and-emerging-trends  the-era-of-data  

Tags: big-data  big-data-adoption  data-governance  data-paprazzi  information-everywhere  

Svetlana Sicular
Research VP
6 years at Gartner
23 years IT industry

Svetlana Sicular is passionate about bringing analytics to domain experts and helping organizations successfully compete by applying their business acumen in analytics and data science. She is convinced that domain expertise and high-value data are the greatest assets that companies should monetize in new analytics applications. Read Full Bio

Thoughts on Who Owns the Data?

  1. Gino Fortunato says:

    Excellent post. There are probably also use cases where owner/custodians have different copies of the same data, each with its own governance solutions. It really does boggle the mind!

    • Svetlana Sicular says:

      Hi Gino! I agree – different copies of the same data is a huge subject from both political and data reconciliation views.

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