BI Governance in the world of Self-service Data Preparation and Data Discovery

November 4, 2016 | By | Add a Comment

Self-service BI platforms provide significant benefits, however, they have also contributed to a new trend: the “wild wild west” of proliferating BI silos, inconsistent business definitions, no data lineage, no single version of the truth. “Spreadsheet hell” has been replaced with “Self-Service BI hell”.

As Boris Evelson (Forrester Research) recently commented to me via email: “We increasingly hear from our clients that BI silos are now proliferating.  Basically these platforms are now becoming the new spreadsheets”.

And that introduces risk. In a recent article in The Economist (“Excel errors and science papers”) it was reported:

“…they had accidentally omitted five rows of their spreadsheet when calculating an average. When included, the missing figures weakened the paper’s conclusion substantially.”

OMG.

Self-service is all about speed and agility, allowing business users to follow their own intuition, answer their own questions, rather than having to rely on IT. In the 1990’s, we used to call it the “next question dilemma”: It’s impossible to predict the next question a business user is going to ask, until they’ve seen the answer to their previous question. Collaborative, self-service data discovery needs to be iterative, exploratory.

But can the “need for speed” in business decision-making be reconciled with the need for Governance? According to Howard Dresner, Governance of BI content creation and sharing correlates strongly to success with BI, improving information consistency and accelerating group-based decision making.

In this context, “BI Governance” includes things like BI lineage, impact analysis, facilitating collaboration and content reuse, reducing content duplication. In How Trustworthy is the data?the BI industry in general, we’ve seen what Wayne Eckerson recently referred to as a “pendulum swing” – away from (over) governed BI to un-governed BI. The pendulum is now swinging back, because business users are now starting to ask questions like:

  • How do I trust the decision being made?
  • How trustworthy is the data? How timely is the data?
  • How do I communicate the decision, the thought process behind the decision, the facts supporting the decision?

An added complexity results from the increasing number of additional sources of information available to a business user. I was recently talking to a customer in the Financial Services industry, who was explaining that they receive data such as AML (Anti-Money Laundering) data from external sources, usually in a flat-file format. The users need to merge/blend these data sources with internal data, in order to produce their dashboards and reports, in support of their business decision-making. Due to the time-sensitivity of the data, the users needed more of a self-service approach to the data preparation, but still have some governance in order to retain confidence in the information being communicated.

In another example, a business user at a Government customer used to complain that the BI content they received had no “context”: what am I looking at? What does this number mean? How was it defined? When was it updated? What is it filtered on? It continues to surprise me, after 25 years working in the BI industry, that most BI output still doesn’t contain this kind of basic contextual information.

Hence, perhaps, the number of business meetings which are still dominated by debates about the numbers, who’s “version” of the numbers are correct, instead of actually making productive, collaborating business decisions.

deep_purple_made_in_japanI’m reminded of something I noticed on a Deep Purple record “Made in Japan”, recorded back in 1971. Ian Gillan, the vocalist, can be overheard asking the sound engineer: “Yeah everything up here please. A bit more monitor if you’ve got it.” To which Ritchie Blackmore, the guitarist, adds: “Can I have everything louder than everything else?”

Without effective, governed self-service data preparation and data discovery, the information becomes noise, trust in the information is diminished, and effective collaboration becomes much more difficult. Everything is louder than everything else.

It takes two to speak the truth – one to speak, and another to hear.” – Henry David Thoreau

Filed in: Big Data, General

Patrick Spedding

About the Author (Author Profile)

Patrick Spedding is Senior Director of BI R&D for Rocket Software, and IBM Champion for IBM Collaboration Solutions. He is also a Non-Executive Director on the Board of Eastside Radio in Sydney, Australia. Prior roles include Director of Product Management for IBM Cognos, Director of Field Marketing for Cognos, Founder of Tableau partner See-Change Solutions, and SAS Solution Manager for BI and Strategy Management. Patrick's qualifications include an MBA degree in Marketing (AIU), Diploma in Management (University of Michigan), BSc (Hons) in Mathematics (Loughborough University, UK), Fellow of the Australian Institute of Management (FAIM), and member of the Australian Institute of Company Directors (AICD). Find Patrick on Google+

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