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Lynn Goldstein, Chief Data Officer, NYU on the Need for Data Governance


We discuss the role of Data Governance, establishing Big Data accountability, impact of Data Governance on Data Quality, and assessing the education available for Data Governance.



Lynn GoldsteinLynn A. Goldstein is the Chief Data Officer for the Center for Urban Science + Progress at New York University. Prior to joining NYU, Lynn was the Chief Privacy Officer and Privacy General Counsel for JPMorgan Chase from 2004 to 2013 and was the Chief Privacy Officer for Bank One from 2003 to 2004. From 2001 to 2004, Lynn was General Counsel for Bank One’s credit card company, and from 1983 to 2001, she was Head of Litigation for Bank One, First Chicago NBD and First Chicago. Prior to joining JPMorgan Chase and predecessor entities, Lynn was in private practice and clerked for a federal judge. Lynn is a lawyer and a Certified Information Privacy Professional and a frequent speaker on privacy topics.

Here is my interview with her:

Anmol Rajpurohit: Q1. In your opinion, is the need for data governance underestimated in big data scenarios?

Data GovernanceLynn Goldstein: In my opinion, the need for data governance is not universally underestimated in big data scenarios. It depends on the organization. Organizations that are knowledgeable about information management recognize that as technology allows for the storage and analysis of big data, the same governance disciplines need to be applied to them as traditional approaches to data management. Sometimes those that are less knowledgeable about information management have some catching up to do.

AR: Q2. What kind of data governance actions can an organization take in order to develop Big Data accountability?

LG: In order to put in place a data governance program for big data, an organization needs to be accountable.

AccountabilityAccording to the Information Accountability Foundation, an accountable organization has at least three elements: commitment to accountability (being responsible for personal information under the organization’s control), policies linked to recognizable outside criteria, and performance mechanisms that ensure there is responsible decision-making regarding management of data that is consistent with the organization’s policies.


AR: Q3. An increasing number of Big Data solutions are leveraging Cloud Computing. How does that impact data governance?

LG: I do not think that cloud computing changes anything; fundamentally the same information management and accountability principles apply in the cloud context. Information in the hands of a third party needs to be managed with the same standard of care as it is handled in the hands of the provider of the information.

AR: Q4. How do you think data governance impacts data quality?

Data QualityLG: Data governance improves data quality. Data quality relates to the second element of an accountable organization: policies linked to recognizable outside criteria. One of the basic tenets of information management is accurate data. Thus, an accountable organization will take the appropriate steps to improve data quality.

AR: Q5. In the last few years, a lot of universities have started graduate and undergraduate programs in Data Science. Do you believe that these educational programs are doing a good job in helping students understand the need and benefits of Data Governance?

CUSPLG: I cannot speak to what other programs are doing, but here at New York University’s Center for Urban Science & Progress (CUSP), we have established a Master of Science program in Applied Urban Science and Informatics. The program’s goal is to provide students with the ability to use large-scale data, from a variety of sources, to understand and address real-world challenges in the urban context. The one-year, three-semester program provides core courses in urban science, urban informatics, and information and communication technology in cities, contains a focus on entrepreneurship and innovation, and places students in multidisciplinary environments with city agencies and industry partners to work on projects that address actual, current problems. Before students gain access to any real data, they take CUSP’s Introduction to Data Governance course, which covers the fundamentals of data governance, the concepts of privacy and confidentiality, security and unauthorized access, through a scenario-based format.

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