Data/Information architecture: new roles and governance

One of the overarching themes that quickly gets established when reading the Gartner essays on data/information architecture is their collective emphasis on creating new data-centric roles. With as much data being generated and collected by enterprises across different market segments it would behoove the enterprises to take Gartner’s advice seriously. For context, 2020 Seagate’s ‘Rethink Data’ report projected enterprise data collection to increase at a 42.2 percent annual growth rate. The more confounding data point noted in the same report was how 68% Of data available to businesses went unleveraged.

The idea behind the creation of these new data roles is to open streams of data locked inside the enterprise. This data is present within the enterprise but siloed under different business units. In addition to standing up the data roles and creating cross-organizational teams, Gartner also advises implementing a robust governance regime that is agile, flexible, and adaptive.

In my enterprise, the IT leadership has invested in various data-centric policies. Which includes employing a data warehousing lead alongside a dedicated data analytics team. However, unlike Gartner’s suggestion of having a CDO, the team rolls up to a manager who does not focus on data only. Let me know how your enterprise deals with data. Does it have data-centric roles and governance built around the use of data? Share your thoughts below.


On a similar topic, WWE (the wrestling promotion) recently became part of TKO holdings. An unfortunate side effect of these mergers is the large number of jobs that get cut or consolidated. One of the casualties of this merger was WWE’s director of enterprise master data & governance, Amanda Bloom. Ms. Bloom posted a message on her LinkedIn profile. This message covers most of the topics we have read for L03. I wanted to share it here as an interesting side note.

 

 

4 Comments

  1. Hi Ali,

    It was great to read your blog. Like always, this time also you are very through and put a tons of thoughts and study on your blog. This leave very little room for any comment on content.
    The blog effectively communicates its main points regarding the significance of data-centric roles and the need for agile governance. You are adding additional credibility and content by including statistics like the 42.2 percent annual growth rate in data collection from Seagate’s report. By asking questions, you are keeping the readers engaged. I can say this is just a perfect blog, just putting this on few paragraph may have made it bit more readable.

    In your experience, do you have any life examples of how improved data management has benefited other enterprises?

    1. Thank you for the comment. I agree, I have been trying to tighten the writing to reduce the length of my blogs. Axios the news site has a great book out called Smart Brevity which I am trying to emulate but unable to successfully replicate so far.
      In my professional career I have not worked for an enterprise where data management is in an advanced stage. Wherever I have been, they are either starting that journey or still figuring out where to start.
      v/r
      Ali

  2. Hi Ali,
    Great post!
    My organization seems similar each of the various teams in my department have a focus on data and the collection of it. My specific team is the dedicated data services team that then works with the other teams to create storage, ETLs and security around it. We also then have a Centralized Security and Data infrastructure teams that monitor and audit the systems that we build and control. So a very collaborative based effort in the storage and structure of our data.

  3. The Seagate report statistic definitely was some excellent knowledge sharing and sent me down a rabbit hole. The growth of enterprise data has all sorts of pathways, and the handling and manipulating that data demands flexible solutions that keep up with needs of organizations beyond what has been used in the past..
    I find the differing opinions between years, the research from pre-covid rallies around on-prem solutions and hybrid models while post-covid research talks about total cloud solutions and building multi cloud solutions.

    https://www.grandviewresearch.com/industry-analysis/enterprise-data-management-market

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