ten questions for people who manage large data intensive projects

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Ten Questions for People Who Manage Large Data Intensive Projects Dennis D. McDonald, Ph.D.

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Page 1: Ten Questions for People Who Manage Large Data Intensive Projects

Ten Questions for

People Who Manage

Large Data Intensive

Projects

Dennis D. McDonald, Ph.D.

Page 2: Ten Questions for People Who Manage Large Data Intensive Projects

1

Ten Questions for People Who Manage Large Data

Intensive Projects

By Dennis D. McDonald1

July 29, 2015

Background

I’ve been researching how to manage projects where

the goal is to make large amounts of data open,

accessible, and useful.

With respect to the Federal government that means

tracking implementation of initiatives like the DATA

Act and the Big Data and Open Data activities of

agencies such as NOAA, EPA, and DOT.

One question concerns the skills needed of the people

who manage such projects. While there are generally

accepted sets of project management skills that are

generic to projects of all kinds, such as PMI’s PMBOK,

when it comes to data-intensive projects there may be

certain technical skills and knowledge that are also

needed in order to be effective.

We can’t all be “data scientists” who are expert at analyzing and modeling large quantities of variegated

data to generate insightful and meanigful visualizations. We also need to get to the point of being able

to generate meaningful analytics, starting with an assurance that the data that are being made available

are accurate and of high quality.

Data extraction, standardization, cleaning, and other data prep activities aren’t glamorous. If you’ve

ever managed projects that transform or move individual financial records from one system

environment to another you understand why paying attention to data accuracy and data quality at every

step in the data management lifecycle is critical to generating a trustworthy dataset.

1 Copyright © 2015 by Dennis D. McDonald, Ph.D. Dennis is a management consultant based in Alexandria, Virginia. His experience includes consulting company ownership and management, database publishing and data transformation, managing the integration of large systems, corporate technology strategy, social media adoption, statistical research, open data, and IT cost analysis. Clients have included the U.S. Department of Veterans Affairs, the U.S. Environmental Protection Agency, the National Academy of Engineering, and the National Library of Medicine. He has worked as a project manager, analyst, and researcher for both public and private sector clients throughout the U.S. and in Europe, Egypt, and China. His web site is located at www.ddmcd.com and his email address is [email protected]. On Twitter he is @ddmcd.

Page 3: Ten Questions for People Who Manage Large Data Intensive Projects

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Add to this movement of your data to a cloud based platform that requires learning a new set of tools

for managing data and you begin to appreciate why a disciplined approach to project management and

associated resource and governance requirements might help you to get from point A to point B.

Ten Questions

With that as background I’m conducting interviews with industry and government executives involved

with managing data intensive projects to explore the following questions:

1. What -- if anything -- makes data intensive projects unique?

2. What special challenges -- if any -- do project managers of data intensive projects face?

3. Do “agile” project management techniques work in large complex data projects that involve a

lot of process change?

4. What role should a Project Management Organization (PMO) play in the management of data

intensive projects?

5. How do you manage the wide variation among stakeholders in their understanding of data

management and data analytics?

6. How much and what type of documentation do you need for data intensive projects?

7. How do you create, manage, and share this documentation efficiently?

8. When should data and metadata standardization efforts be project specific?

9. When should data and metadata standardization efforts be enterprise- or industry-wide?

10. Does moving your data to the cloud make your project management job harder or easier?

Please let me know if you would like to discuss these questions with me, off the record if desired. I’ll

synthesize the findings and publish them. My contact information:

Dennis D. McDonald, Ph.D., Alexandria, Virginia USA

Cell phone number 703-402-7382

Email [email protected] or [email protected]

Related reading:

Breakthrough Financial Open Data Legislation To Be Introduced May 20

Can Meat-and-Potatoes “Big Data” Help Detroit?

Challenges of Public-Private Interfaces in Open Data and Big Data Partnerships

Changing Culture of Big Data Management

DATA Act Implementation: Where’s the Plan?

Data Program Governance and the Success of Shared Digital Services

Data Standardization Scores and Changing the DATA Act

Don’t Let Tools Drive Enterprise Data Strategy

Management Needs Data Literacy To Run Open Data Programs

Observations and Questions about Open Data Program Governance

On Defining the "Maturity" of Open Data Programs

Planning for Big Data: Lessons Learned from Large Energy Utility Projects

Progress Implementing the DATA Act (draft)

Recouping “Big Data” Investment in One Year Mandates Serious Project Management