.. it has always been that an important first step in Data Analytics was developing or acquiring the key data to be analyzed. Having the right subject matter data for the right geography and time frame are essential prerequisites. The Internet and pervasive expanding needs and solutions for data integration has made Data Analytics easier and more accessible — and often more technically challenging. The Data Analytics Lab, reviewed here, offers a foundational and support framework to address the continually evolving Data Analytics needs. See more about the Data Analytics Lab in the related Web section.
Data Analytics involves more than the ability to perform statistical analyses on data, though this is an important element. Data Analytics encompasses a spectrum of data and the ability to develop, access, integrate and effectively use those data. The platform of data on which we operate is constantly in change. New and different types of data emerge. Older data become obsolete. Required subject matter are often not available at the required geographic granularity. Often the biggest challenge is in linking data for analysis.
Role of Geographic Information Systems (GIS)
GIS software is one on many Data Analytics tools. It is an important tool for many reasons. One main reason is the enabling ability to flexibly visually examine subject matter for different types of geography simultaneously. The following view shows patterns of economic prosperity in the Atlanta region (metro shown with bold boundary). The thematic pattern is median household income by block group. Higher income areas are shown in blue/green and lower income areas are shown in orange/red. Counties are shown with black boundaries.
The next view is a zoom-in to the pointer location in the map shown above. This view has a higher transparency setting enabling a see-though effect to view highways and related ground infrastructure. Block groups appear with black boundaries. The pointer is at the county boundary, a slightly bolder boundary.
Data Analytics Labs (DAL) help participants develop a capacity to create map views like those shown above and perform geospatial analyses. This is more than learning how to operate GIS software; more than how to acquire shapefiles and build a GIS project. It is about selecting and acquiring the right subject matter data and then integrating those data with geometry (shapefiles, etc.) and assembling the composite files for analysis. DAL learning enables participants to develop informative and relevant maps view — and the right types of different geographies (including vintages) to use.
Data Analytics Labs are set up within universities, government agencies and not-for-profit organizations to address these needs. Contact us to discuss how a Lab can be developed within your organization.
A Data Analytics Lab provides tools/resources for hands-on data analytics applications. In a university setting, the Lab can be open to MBA, MPA, MHA and other graduate students plus multi-disciplinary faculty/researchers. Also in the university setting, some parts of a Lab can fit into existing classes and mesh with other existing programs. There is no physical lab; it is a virtual lab. The resources and vision are initially focused on Census-type geographic-demographic-economic data, expanded to selected Federal statistical data, and how these and primary data are knitted together for analysis and decision-making.
There are no fees to participants. Tools and data are made available by ProximityOne — http://proximityone.com.
Data Analytics Lab Resources & Components
• CV XE GIS software
– GIS shapefiles and applications compatible with ESRI ArcGIS software
• API data access/integration software
• Modeler software
– cause & effect modeling; estimation & forecasting; impact analysis
• Related software
2. Data Resources
• state & national scope ready to use GIS projects
• augmented TIGER/DMD geography
• U.S. national scope 5-year demographic-economic estimates & projections
– small area demographic-economic estimates/projections to 2020
• U.S. national scope county/up 2060 demographic projections
– population projections to 2060 (single year of age x gender x race/origin)
• ProximityOne Data Services (PDS)
– multi-sourced Federal , Census and other data resources
3. U.S. by state/metro/county macro models (uses software and data above)
• enable users to explore alternative model specifications/assumptions
• produce alternative outcomes; perform impact analyses
4. Data Analytics Lab Sessions
• variations on weekly Web-based sessions
5. Certificate in Data Analytics Modules
• structured usage of Data Analytics Certificate program sessions/resources
6. Intern Participation: Data Analytics Tools Development and Applications
• model specification & use; software development & use; data resource development & use
Forthcoming sections will review examples of Data Analytics Labs, how and where they are operating and experiences of participants.
About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data.