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Chief Data and Analytics Officer Research Publication List

by Jitendra Subramanyam  |  July 1, 2019  |  Submit a Comment

Here is a list of our publications to date – it is kept current as we release more publications.

[Last updated: July 1st, 2020]

The Team

Jitendra Subramanyam  https://www.linkedin.com/in/jsubramanyam/

Ben Hertzberg https://www.linkedin.com/in/benjaminhertzberg/

Farhod Yuldashev https://www.linkedin.com/in/fyuldash/

Ethan Green https://www.linkedin.com/in/ethanfgreen/

Ariel Silbert https://www.linkedin.com/in/ariel-silbert-289a50104/

Shelly Thackston https://www.linkedin.com/in/shellythackston/

Our research terrain covers:

Business Value of Data & Analytics

Data & Analytics Strategy and Planning

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Data & Analytics Quality and Ethics

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  • Case Study: Ethical AI with an External Board (Axon) NEW!
    Are concerns about potential ethical issues blocking you from implementing AI? Learn from Axon how to set up an external ethics board to keep your work ethically sound!
  • How to Investigate the Operating Characteristics of Any Quantitative Model 
    Any quant model, even deterministic ones, can behave unpredictably. Learn how to systematically investigate the operating characteristics of your business-critical quant models here.
  • Case Study: Data Ethics Decision-Making System (Highmark Health) 
    Most D&A leaders believe complying with rules ensures ethical use of D&A. It doesn’t. Ethical use of D&A demands reflection on use cases, which enables decisions on their appropriateness. Find out how Highmark Health established a system to do so here.
  • Zen and the Art of Data Quality Improvement 
    Does low quality data prevent value creation in your organization? Reexamine your data quality improvement practices. This research profiles a Zen approach to data quality improvement adopted by several progressive D&A leaders who have created value with imperfect data.
  • Data Governance Playbook  
    This toolkit collects client templates to aid D&A leaders in developing a data governance model. It includes templates for governance processes, stewardship roles, and information health metrics.
  • Rationales for the Idealist Imperative in Business 
    Are you perplexed by the hype around business ethics? Click here to learn why ethics are crucial for branding and financial performance today. Find concrete recommendations D&A leaders can take to ensure their organizations’ data practices are ethical.
  • Human Controls for AI Dangers (SignatureValue Bank*)
    Rather than guarding against AI-based attacks, D&A leaders should collaborate with security leaders to guard against the threats internal AI applications cause. Find out how SignatureValue Bank did so here.
  • On Demand Problem Solving Teams (McDonald’s)
    Are you frustrated with onerous data governance practices at your organization? Learn how McDonald’s uses rapid response “sand dune teams” to efficiently make data governance decisions.
  • Exclusion-Based Data Sharing Rights (FirstHarbor*)
    Do data sharing requests at your organization get bogged down because dozens of stakeholders have to approve them? Find out how FirstHarbor quickly determines which stakeholders should be excluded from reviewing data sharing requests.
  • Business-Need Driven Data Governance Objectives (FirstHarbor*)
    Does your data governance enable value creation or constrain it? Find out how FirstHarbor narrows the scope of data governance, meeting business needs in data collection, use, and sharing while ensuring compliance and productivity.
  • Value-Add Data Minimization (Northrop Grumman)
    More data is not always better, because data comes with risk. Find out how Northrop Grumman selects data for minimization and sells business partners on value-adding alternatives.
  • Ignition Guide to Building a Data and Analytics Governance Program
    Don’t assume that traditional data governance will meet the demands of big data and digitization! Use this guide to establish a governance program that aligns with business priorities and divides strategic and tactical responsibilities.
  • Data Quality Score (TE Connectivity)
    Does your organization struggle to get buy-in for data quality improvements from your business users? Find out how TE Connectivity used an enterprise-public data quality score to hold business users accountable for data quality.
  • Dangerous Data: Can’t Live Without It, Can’t Live With It
    Many D&A leaders think data is good and more data is better. But some data can pose serious legal, ethical, and brand risks to organizations. Find out why here.
  • “Show Don’t Tell” Data Quality Improvement (Citizens Bank)
    Business users often struggle to see the relevance of data quality to their work. Citizens Bank creates business demand for increased data quality by contrasting the insights and reports that could be generated from higher quality data to the current state.
  • Data & Analytics Operational, Data Quality, and Data Management Metrics
    How do Data and Analytics leaders measure success? Find out here: our collection of real-world metrics spanning operations, business value, data quality, and data management maturity.

Data & Analytics Talent

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Jitendra Subramanyam
VP, Team Manager I
2 years at Gartner
16 years IT Industry

Jitendra Subramanyam leads a research team that is focused on how Chief Data Officers manage the Data and Analytics function in their organizations. Jitendra teaches a course on machine learning at Harvard Extension School. The course is a practical introduction meant to help business executives understand key concepts and techniques in data science and immediately apply them to business problems.Read Full Bio




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