Global University Review 2017

Why Review What Universities are Teaching ?


In 2016, bad data cost the US economy an estimated $3T, but the data industry has no coherent or consistent response to understand or reduce this damage.

The 2017 Data Manifesto launched in Atlanta, reveals global data skills shortages, poor data literacy in the western world and data leadership inhibitors in business leadership.

The above mentioned issues are well articulated in the Data Manifesto (2017) and supported by credible research available at by Dr Nina Evans  & James Price, and endorsed by revered data luminaries such as Dr Thomas Redman, Kelle O’Neal, John Ladley and Danette McGilvrey.

Sadly, the concepts raised in the Data Manifesto 2017 are not new, and have been championed by experts for decades by others like Jack Olson, Arkady Maydanchik, Larry English, David Loshin, Prof John Talburt (, Dr Richard Wang (MIT), Dr Stuart Madnick (MIT) and many others who have pioneered in this space for cogency, improvement and change.

As a practical global response to several  key issues raised in the Data Manifesto, namely poor data literacy and university curriculum improvement, ClearDQ is undertaking a comprehensive global study of incumbent and planned university curricula on the subject of Data Quality and Data Asset Management disciplines.

The primary object of our study is to predict the global data skills shortfall into the future.

We see data quality and data asset management as a new breed of business problem, not just a technology challenge. In fact, mature data management disciplines transcend the underlying (and churning) data technology platforms, especially in a post-big-data era.

We are of the view that the global data skills and data literacy shortage will not be alleviated until mature, comprehensive teaching on the “commercial valuation” of data quality and data assets is delivered in core business faculties, rather than default technology aligned faculties.

We believe this shift in business focus will drive a universal understanding of data as it’s own “economic asset class”.

Gartner’s Doug Laney has championed this concept in his seminal 2017 work entitled “Infonomics – How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage (ISBN 978-1138090385).

For us at ClearDQ, we seek to provoke a systemic learning revolution, to teach fundamental Data Management and Data Quality disciplines in Business Faculties (as a Core Commercial Business Skill) to support the exploding global culture of technology and data-driven business models.

We are reaching out to 9,362 universities in 204 countries.

We are looking for industry and academic collaborators, as well as funding/sponsorship for this project. We are opento take on board existing learning and insight from previous attempts at this important work.

We are conducting a two(2) stage Global University Review & Collaboration process, namely:


  • Register all universities and faculty units, with contact information for those universities and faculty, who do teach these subjects, and carry a keen interest in future knowledge/teaching breakthroughs in this area, and also report back to all participants on findings from this data collection stage.
  • Closes 31st November 2017.
  • Initial reporting will be provided to all participants on 31st December 2017.
  • Registrations are now open.
  • If interested, please ensure your university is registered.
  • Please proceed to the STAGE 1 the initial University Registration Process HERE.


  • Conduct a second round review to assess the current depth and maturity of what is being taught, assess the alumni throughput, in an attempt to accurately predict the data skills availability shortfall into the future, and also report back to all participants on data collected/findings from this stage.
  • Only participants registered in STAGE 1 will be able to participate in STAGE 2 by invitation only (register in Stage 1 above)
  • Stage 2 will commence 31st January 2018.

Endorsements & Industry Commentary

If you would like to  comment on, endorse,or even  sponsor this process, please email us. Thanks in advance for your thoughtful participation.
Martin Spratt, August 2017

Data Quality for Financial Performance