Ten Questions for People Who Manage Large Data Intensive Projects
I’ve been researching how to manage projects where the goal is to make large amounts of data open, accessible, and useful.I’ve now developed ten questions that explore the potentially unique project management requirements of such projects.
With respect to the Federal government in the U.S. researching data related project management practicesinvolves 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 issue concerns the skills needed of the people who manage and oversee 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 meaningful 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.
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.
With that as background I’m conducting interviews with industry and government executives involved with managing data intensive projects to explore the following questions:
- What — if anything — makes data intensive projects unique?
- What special challenges — if any — do project managers of data intensive projects face?
- Do “agile” project management techniques work in large complex data projects that involve a lot of process change?
- What role should a Project Management Organization (PMO) play in the management of data intensive projects?
- How do you manage the wide variation among stakeholders in their understanding of data management and data analytics?
- How much and what type of documentation do you need for data intensive projects?
- How do you create, manage, and share this documentation efficiently?
- When should data and metadata standardization efforts be project specific?
- When should data and metadata standardization efforts be enterprise- or industry-wide?
- 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@example.com or firstname.lastname@example.org
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Copyright (c) 2015 by Dennis D. McDonald, Ph.D. Dr. McDonald’s consulting, project management, and research focus on planning and managing data intensive projects. His consulting services include preproposal research and analysis, technical and business proposal development and costing, marketing and sales support including collateral and website content preparation, presentation development, blogging, and “white paper” preparation. His project management services include project and program management, PMO setup and administration, project schedule development, and resource planning. His web site is located atwww.ddmcd.com and his email address is email@example.com. On Twitter he is @ddmcd.