1 year, 9 months ago

DataOps – Organizing the Data Value Chain

Link: http://feedproxy.google.com/~r/Soapbox/~3/QB-xSYh1o0E/dataops-organizing-data-value-chain.html

At #TalendConnect today frequent mention of #DataOps, although according to a post I found on the Talend blog from earlier this year, Talend prefers the term collaborative data management.

Data Preparation … should be envisioned as a game-changing technology for information management due to its ability to enable potentially anyone to participate. Armed with innovative technologies, enterprises can organize their data value chain in a new collaborative way. Talend

I’ve always insisted that the data value chain should end not with delivering insight (so-called actionable intelligence) but with delivering business outcomes (actioned intelligence), and I was pleased to hear some of today’s speakers making the same point. However, there are still voices within the industry that have a narrower view of DataOps, and I note with concern that the DataOps Manifesto identifies the goal of DataOps in terms of the early and continuous delivery of valuable analytic insights.

Although there will always be a place for analytic reports and dashboards, I always expected that these would gradually make way for analytic insights being rendered as services and integrated into operational business systems and processes, to create closed-loop business intelligence. There are many good examples of this today, especially in the manufacturing world. There are also systems that deliver insights directly to customers or end-users, perhaps in the form of recommendations. But a lot of the discussion of the data-driven enterprise still seems to be based on a dashboard mindset.

And who actually does the DataOps? A presentation from Virtusa showed a three-step DataOps process – pipeline, innovation and value – which suggests a trimodal approach. So the Town Planners would do the pipeline (building generic and highly customizable data preparation frameworks), Pioneers would do the innovation (experimental proof of concept), and the Settlers would roll out the value. I shall be interested to see some practical implementations of this approach.

Meanwhile, simplistic notions of democratization (or citizen integration) often divides people into two camps – experts and citizens – and this polarization is encouraged by Gartner’s promotion of Bimodal IT. But this leads people to believe that you can have either trust or speed/agility but not both. And as Jonathan Gill of Talend emphasized in his keynote today, digital leaders don’t recognize this dichotomy.

Jean-Michel Franco, 3 Key Takeaways from the 2019 Gartner Market Guide for Data Preparation (Talend, 26 April 2019)

Wikipedia: DataOps

Related posts: Service-Oriented Business Intelligence (September 2005), SPARK 2 Innovation or Trust (March 2006), Analytics for Adults (January 2013), From Networked BI to Collaborative BI (April 2016), Beyond Bimodal (May 2016), Towards the Data-Driven Business (August 2019), Beyond Trimodal – Citizens and Tourists (November 2019)