Open Data Program Managers Need Both Analytical and Structural Data Skills

By Dennis D. McDonald, Ph.D., Balefire Global, dmcdonald@balefireglobal.com


Introduction


In Management Needs Data Literacy to Run Open Data Programs I addressed the question of how much “data literacy” open data program managers need. I outlined a series of topics corresponding to different parts of the data management lifecycle the program managers need to be familiar with. While certainly I don't believe it is necessary for all program managers to be “data scientists” to manage open data programs effectively, I do think that there are certain data related skills that managers do need. One of the most important is the ability to think about data both from analytical as well as structural perspectives.



The analytical perspective


Analytically, managers need to understand that useful data are not just random collections of numbers but represent patterns and trends that can be used to tell stories about the objects or events with which the numbers are associated. The range of tools we have available now for analyzing and visualizing data are truly impressive including systems that are capable of processing and recognizing patterns and trends in huge volumes of data. Sometimes this is referred to as “big data” analytics, especially when we’re discussing the volumes of data that can be produced by organizations such as government agencies and public utilities.


What is also impressive to me, though, is the other end of the spectrum. As a BaleFire consultant involved with the implementation of open data portals using tools such as those provided by companies such as Socrata I am truly impressed with the visualization and analytical power available to those interested in discovering and exploring trends and patterns in everyday data such as crime statistics, municipal operational expenditures, and restaurant inspections.


Despite the simplicity and ease of use of such systems, though, open data managers need to be sensitive to the opportunities such tools provide and should be able to perform basic analyses on their own. One of the most important skills the open data manager can possess will be the ability to think in terms of the stories the data can “tell” and plan accordingly.


The structural perspective


From a structural perspective managers need to understand that, despite the availability of easy-to-use file management, navigational, and visualization tools, data need to be viewed as building blocks that need cleaning, quality control, and standards. Sophisticated processing tools can be relied on to do some cleaning and standardization at the time of data intake for making a file available on a web portal. Sustaining consistent data quality over time requires constant monitoring and some changes to current processes if the data are to be updated in a timely fashion. This "extra layer" of management requires resources, someone to oversee it, and -- perhaps most importantly -- someone to defend it over time.


Summary


Effectively performing both these roles requires both an understanding of analytical potential and an appreciation of what it takes to keep the data flowing!

Further reading

Planning for Big Data: Lessons Learned from Large Energy Utility Projects
Learning from the World Bank’s “Big Data” Exploration Weekend
Can Meat-and-Potatoes “Big Data” Help Detroit?
Recouping “Big Data” Investment in One Year Mandates Serious Project Management
Data Cleanup, Big Data, Standards, and Program Transparency