Data Maturity Literature Review: Appendices

These are the appendices to the Data Maturity in the Social Sector 2016 report.

Appendix 1 Key Sources on Data Maturity

Accenture, Analytics Maturity Assessment, Netherlands 2015

Anderson C.,”Creating a Data-Driven organisation: practical advice from the trenches“, 2015

Booz, Allan & Hamilton,  “The Field Guide to Data Science“, 2015 (2nd Edition).
(Lit. Review list & Data Science Maturity Model on page 35)

Davenport T., Assessing your analytical and big data capabilities, Wall St Journal, July 2014

Eckerson W., The Data Warehousing Institute, Business Intelligence Maturity Model

Fisher D., “Data Analytics Maturity Model“, 2014

Howard J., Review of the INFORMS analytical model, 2014

Howson C., TScore Overview for BI and Analytics, Gartner 2015

Marsh M., “Review of skills and leadership in the VCS sector” (section on data-informed social change), 2013

Mason H., video and e-mail comms,  2016.

McSweeney A., “Review of Data Management Maturity Models” 2013

Parenteau P., Sallam R., Howson C., Tapadinhas J., Schlegel C., Oestreich T., Magic Quadrant for Business Intelligence and Analytics Platforms, Feb 2016

Polynumeral Blog, the number one question CEOs ask about data 2016

Patil D.J., Mason H., “Data-driven – Creating a Data Culture“, 2015

Sedar J., Data Science maturity model blog, March 2016

Soares S., “The IBM data governance Unified Process“, Sept 2010

Yanosky R., Arroway P., The Analytics Landscape in Higher Education, Educause, Oct 2015

Appendix 2 People we interviewed

  • Jake Porway, Founder and Executive Director at DataKind, New York
  • Duncan Ross, Data and Analytics Director, TES Global (Founder/Chair DataKind UK)
  • Jonathan Sedar, Consulting Data Scientist at Applied AI Ltd
  • Shyann Seet, Independent Data & Analytics Advisor
  • Hilary Mason,  Data Scientist, Fast Forward Labs. (comment via E-mail).

Appendix 3 DataKind’s prototype data maturity model


Appendix 4 A selection of the models and frameworks we found

– Applied AI Data Science Maturity Model

– Gartner Master Data Management Maturity Model

– Gartner Business Intelligence and Analytics Model

– The Data Management Maturity (DMM) (see CMMI institute)

– Steven Mills, Chief Data Scientist, Booz Allen [PDF]

– Educause 2012

– Gapbridge Analytics

– Infofarm Data Science maturity model

– Dan Fisher, Data Analytics Maturity Model, 2014.

– Jay Zaidi, 2015 (AlyData): Data Management Maturity Model (DMM) developed by the Software Engineering Institute at Carnegie Mellon University.

– The Data Warehouse Maturity Model Business Intelligence Maturity Model [PDF]

– Big Data Maturity Model (2012), comes from an IT perspective. Advanced version  has more detailed emphasis on value creation, risk management, compliance, competency, architecture, policy, security, organization, audit.

– Comparative view by A McSweeney. McSweeney A., “Review of Data Management Maturity Models” 2013

Introduction to (Big) Data Science from InfoFarm


Appendix 5 Open Data Maturity Model

The Open Data Institute launched the first edition of its The Open Data Maturity Model in March 2015.

ODI Maturity Model: Guide – Assessing your open data publishing and use by Open Data Institute

They’ve built a ‘Map your pathway’ App which offers to help assess where you’re at, set goals and track progress towards them.  Benefits it promises include: Discover your organisation’s strengths and weaknesses; Identify areas of improvement to optimise progression; receive practical recommendations to help achieve your goal.

Appendix 6 Social Impact Data Maturity Model, University of Chicago

 

For more details see the Social Impact Data Maturity project site (we believe that the Data Maturity Framework resources are available under an open licence).

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