Category Archives: Site Analysis

Block Group Demographic Data Analytics

.. use tools described here to access block group data from ACS 2016 (or ACS2017 in December 2018) using a no cost, menu driven tool accessing the data via API. Select from any of the summary statistic data. Save results as an Excel file or shapefile. Add the shapefile to a GIS project and create unlimited thematic pattern views. Add your own data. Join us in a Data Analytics Web session where use of the tool with the ACS 2017 data is reviewed.

See related Web section for more details.
– examine neighborhoods, market areas and sales territories.
– assess demographics of health service areas.
– create maps for visual/geospatial analysis of locations & demographics.

Illustration of Block Group Thematic Pattern Map – make for any area

– click graphic to view larger view
– pointer (top right) shows location of Amazon HQ2

Topics in this how-to guide (links open new sections/pages)
• 01 Objective Thematic Pattern Map View
• 02 Install the CV XE GIS software
• 03 Access/Download the Block Group Demographic-Economic Data
• 04 Download the State by Block Group Shapefile
• 05 Merge Extracted Data (from 03) into Shapefile (04)
• 06 Add Shapefile to the GIS Project; Set Intervals
• 07 Viewing Profile for Selected Block Group
• 08 BG Demographics Spreadsheet
• 09 Block Group Demographics GIS Project
• 10 Why Block Group Demographics are Important

Data Analytics Web Sessions
Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

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. Contact Warren. Join Warren on LinkedIn.

Location-Based Demographics Update

.. tools you can use to examine characteristics of addresses/locations .. many of us are interested in knowing attributes of addresses or locations. Often knowing address latitude-longitude is important so that the addresses can be viewed on a map .. see below.  Some might need to know what census block, or other geography, in which an address is located .. or what school district is an address located in.  Others need to know demographic-economic attributes of the neighborhood or area where an address is located.  These types of attributes can be obtained for addresses using the Location-Based Demographic (LBD) tools.  The LBD tool has just been made a part of the CV XE GIS software.  The LBD tool is available in all versions of CV XE GIS, including the no fee User Group version. See more about using the LBD tools to look-up and analyze address/location attributes.

Viewing Geocoded Addresses on a Map – automatically
The following view shows addresses geocoded using the LBD tool. Markers show addresses of 27 Trader Joe’s locations in the Los Angeles area. LBD automatically creates a shapefile that is added to your GIS project. The markers are labeled with population ages 18 and over in the corresponding census tract. Marker color/styles reflect different levels of median household income. A separate census tract layer shows patterns of economic prosperity.

Click graphic for larger view. Expand browser window. A mini profile is displayed showing demographic-economic attributes for the marker at pointer.

View the locations without the tract thematic pattern layer:

Make similar views for your addresses.

Get Started Using the LBD Tool
1 – join the User Group .. click here to join (no fee).
2 – run the installer to install on a Windows machine .. requires your userid.
3 – with CV XE GIS running, click Tools>Find Address/LBD
    enter an address .. a form appears showing characteristics of the address.
4 – see more about using the tools on the LDB page.

GeoStatistical Data Analytics Learning Sessions
We are developing a series of “GeoStatistical Data Analytics” (GSDA) Learning Sessions/modules. One of these is focused on using the LBD tools and methods in the broader context of data analytics. We plan to develop the GSDA models for self-guided use by analysts/practitioners as well as in the classroom setting with teacher/student materials. Upcoming blog posts will describe the program in more detail.

Data Analytics Web Sessions
Join me in a Data Analytics Web Session, every Tuesday, where we review access to and use of data, tools and methods relating to GeoStatistical Data Analytics Learning. We review current topical issues and data — and how you can access/use tools/data to meet your needs/interests.

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. Contact Warren. Join Warren on LinkedIn.

ZIP Codes with Highest & Lowest Economic Prosperity

.. the latest data for ZIP Code Areas show that eleven had a median household income of $250,000 or more during the period 2011-15. More than 20 ZIP code areas had a median housing value of $2,000,000 or more. Contrast these ZIP code areas with higher economic prosperity with the more than 150 ZIP codes that had a median housing value of less than $30,000.  Use the interactive table in this related Web section to see which ZIPs meet these and other criteria.

ZIP Codes with MHI $100,000 or More; Dallas, TX Metro
Analyzing economic prosperity patterns using combined types of small area geography … the following graphic shows ZIP code areas a red markers with the median household income or $100,000 or more in context of median household income by census tract thematic pattern. Click graphic for larger view with more detail. Expand browser window for best quality view. Use CV XE GIS software and associated GIS project to develop variations of this view for your areas of interest. .

– view developed with CV XE GIS software.

This section reviews measures of economic prosperity for all ZIP code areas. These data were released in December 2016. This section updates with new data December 2017. See the list of all ZIP ccdes showing population, housing and economic characteristics in the interactive table shown below. Use the interactive table to view, rank, compare and query ZIP code attributes.

Examining demographic-economic characteristics by ZIP code is important for several reasons. We are familiar with our own ZIP codes as a geographic location. We tend to be interested in our area compared to other areas. ZIP codes provide an easy way to do that. Also, many secondary data resources are tabulated by ZIP code area; some important data are only available by ZIP code. See more about ZIP Code areas.

Resources & Methods to Examine Small Area Demographics
• See related ZIP Code Demographic-Economic Interactive Tables
  .. extended subject matter
• See related Census Tract Code Demographic-Economic Interactive Tables
• Examine ZIP Code Urban/Rural Characteristics
• Examine ZIP Code Business Establishment patterns
• Examine ZIP Code Housing Price Index patterns
• Join us in the weekly Data Analytics Lab Sessions
  .. reviewing applications using these and related data.

ZIP Code Areas with $MHI $100,000 or More
The following graphic shows ZIP code areas as red markers having median household income or $100,000 or more. Click graphic for larger view with more detail. Expand browser window for best quality view. Use CV XE GIS software and associated GIS project to develop variations of this view; integrate other data; select alternative ACS 2015 subject matter.

– view developed with CV XE GIS software. Click graphic for larger view.

ZIP Code Areas with $MHV Less than $30,000
The following graphic shows ZIP code areas as orange markers having median housing value of less than $30,000. Click graphic for larger view with more detail. Expand browser window for best quality view. Use CV XE GIS software and associated GIS project to develop variations of this view; integrate other data; select alternative ACS 2015 subject matter.

– view developed with CV XE GIS software. Click graphic for larger view.

ZIP Code Areas: Population & Economic Prosperity
  — Interactive Table –
Use the interactive table to view, rank, compare, query ZIP codes based on a selection of demographic-economic measures. The following graphic illustrates how the table can be used to examine patterns of the three digit ZIP code area (San Diego) by 5-digit ZIP code. Table operations are used to select ZIP codes in the 921 3-digit area (containing 39 5-digit ZIP codes). These 39 ZIP code are then ranked in descending order on median household income. See results in the table shown below. ZIP code 92145 has the highest $MHI in this group with $228.036.

– click graphic for larger view.

Try it yourself. Use the table to examine a set of ZIP codes on your selected criteria in for a state/area of interest.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

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. Contact Warren. Join Warren on LinkedIn.

Housing Price Index by 5-Digit ZIP Code

.. tools to examine housing prices by 5-digit ZIP code and how they are changing .. of the 17,931 5-digit ZIP codes tabulated, 8,074 experienced a decrease in housing value during the period 2010 to 2015. At the same time, 8,672 ZIP code areas experienced an increase in housing value. Housing prices increased for most ZIP codes from 2014 to 2014.  Find out more about housing prices and trends for ZIP codes of interest using tools described here. These data are based on experimental estimates of the Housing Price Index (HPI) by 5-digit ZIP code based in part on home sales price data from Fannie Mae- and Freddie Mac-acquired mortgages. See more about these data.

• Use the interactive table to view, rank, compare the HPI for all 5-digit ZIP code areas tabulated.
• Use GIS tools described here to develop thematic pattern maps; add your own data & geography, select different HPI measures or criteria; zoom to different geographic extents, label and modify colors as desired.

Gaining Insights in Housing Prices, Conditions & Markets
  .. Characteristics, Patterns & Trends
  .. join in .. one hour web session — overview & connectivity details

Patterns of Housing Value Change by ZIP Code: 2010-15
The following graphic shows patterns of housing value appreciation by ZIP Code: 2010-15 for the Houston metro (bold brown boundary). The color patterns/intervals are shown in the inset legend. Data are not available, using the criteria applied (2000 base year), for areas not colored In the larger view (click graphic), ZIP codes are labeled with HPI percent change from 2010 to 2015. Click graphic for larger view. Expand browser to full window for best quality view. Use the GIS tools described here to develop thematic pattern maps for a range of data and criteria.

.. view developed using the CV XE GIS software.
.. click map for larger view and details.

Additional views:
Atlanta area
New York City area
Washington, DC area
Los Angeles area

Examining Recent Trends; Current Estimates & Projections
The interactive table presents annual HPI data 2010 through 2015. A much larger set of these ZIP codes show a negative change between 2010 and 2015 compared to the one year change 2014-2015; The data generally show more ZIP codes experiencing housing value appreciation 2014-2015 compared to the longer period 2010 to 2015. These trends underscore the importance of having more recent data for use in analysis, planning and decision-making. The next update based on transaction data will be May 2017 or later.

ProximityOne uses the HPI transaction data with other data to develop HPI current estimates (2016) and annual projections to 2021 with quarterly updates as a part of the Regional Demographic-Economic Modeling System (RDEMS). Experimental county-up (metro, state, U.S.) and sub-county estimates and projections are planned for the fall 2016 quarterly update. The model based estimates and projections include the number of units by type and value that are added to the housing stock used to compute a variation of the HPI.

Housing Price Index by 5-Digit ZIP Code: 2010-2015
  — Interactive Table
Use the interactive table to examine the Housing Price Index (HPI) by 5-digit ZIP code. The following graphic illustrates use of the table to show the 10 ZIP codes experiencing the largest percentage increase in the HPI from 2014 to 2015. Click graphic for larger view. Examine cities or ZIP code ranges of interest using tools below the table.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

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. Contact Warren. Join Warren on LinkedIn.

Tip of the Day — Census Tract Data Analytics

.. tip of the day .. a continuing weekly or more frequent tip on developing, integrating, accessing and using geographic, demographic, economic and statistical data. Join in .. tip of the day posts are added to the Data Analytics Blog on an irregular basis, normally weekly. Follow the blog to receive updates as they occur.

This section is focused on tools and methods to access and use census tract demographic-economic measures. Median household income ($MHI), median housing value ($MHV) and other selected items are used to illustrate operations and options.

This section illustrates use of census tract data from the 2014 American Community Survey (ACS1014) 5-year estimates. These are the most comprehensive demographic-economic data from the Census Bureau at the census tract level. These “5-year estimates” are centric to mid-2012. See more about 2010-2021 annual estimates and projections.

Methods described here apply to many other geographies; see related tip sections. See related section on ZIP code applications.

Five data access and use options are reviewed. Each method illustrates how $$MHI, $MHV and other data can be analyzed/used in different contexts.

Option 1 – View the data as a thematic pattern map.
Option 2 – View, compare, rank query data in interactive tables.
Option 3 – Access data using API Tools; create datasets.
Option 4 – View $MHI in structured profile in context of related data.
Option 5 – Site analysis – view circular area profile from a location.

Related sections:
Census tracts main section
Evolution of Census Tracts: 1970-2010
Demographic-Economic Estimates & Projections
Census tract and ZIP code equivalencing
Using census tracts versus ZIP code areas
Single year of age demographics

Option 1. View the data as a thematic pattern map; use the GIS tools:
Patterns of Economic Prosperity ($MHI) by Census Tract … the following graphic shows $MHI for a portion of the Los Angeles metro. Accommodating different demographic-economic thresholds/patterns, different legend color/data intervals are used. The pattern layer is set to 80% transparency enabling a view of earth features. Click graphic for larger view, more detail and legend color/data intervals; expand browser window for best quality view.

– View developed using CV XE GIS and related GIS project.

See details about each option in the related Web page.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

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. Contact Warren. Join Warren on LinkedIn.

Developing & Using Map Graphics

.. steps to develop map graphics & visual analysis of market/study areas .. map graphics are an important part of most demographic-economic analyses and essential for many applications. Not only are are maps needed to show geographic boundaries and the relative location of geography within a broader area, they can come alive by showing patterns. A thematic pattern map of median household income by block group is a good example; higher and lower areas of economic prosperity by neighborhood can be immediately determined. Map graphics can improve our ability to communicate complex information. Convey information faster. Make more compelling presentations. Collaborate more effectively through the use of map graphics.  See related Web section for more details.

The focus of this section is on creating and using KML files to prepare map graphics for use in developing Market-Study Area Comparative Analysis Reports. These files and map graphics also have broader uses. Steps are reviewed to develop the KML circular area map graphics files, convert them to shapefile structure and integrate both files into mapping and GIS applications and put them into operational use. 

KML (Keyhole Markup Language) files are XML structured files useful for visualizing geographic objects (like circles) using Internet-based browsers, notably Google Earth. Why develop/use KML files? They are easy to create with precision, there is little to no learning curve, they can be used in many venues and they are free to develop. KML files can be used side-by-side with shapefiles. Shapefiles, structured very much unlike KML files, are the dominant vector-based file structure used in GIS applications involved in both viewing and geospatial analysis. 

Developing Circular KML Files & Map Graphics
An “objective view” of this section is shown in the following graphic. The graphic shows a study site location (red marker), 1-mile & 3-mile radius circles. The site location is a Starbucks located at 302 Nichols Road, Kansas City, MO 64112. The view shows a circular KML-based graphics in context of patterns of median household income by block group. Develop similar views for any area, any site circular configuration, using steps reviewed in this section.

– view developed using CV XE GIS

Creating the KML Circular Graphics File
Proceed through the next steps to develop a KML file used to create the graphic below on left — a Starbucks located at 302 Nichols Road, Kansas City, MO 64112. Graphic on the right is a Starbucks location in Paris, used to illustrate this process works globally. Both graphics include study area center point and 1-mile and 3-mile radius circles.

302 Nichols Road, Kansas City, MO 64112
23 Avenue de Wagram, 75001 Paris, France

Start the create KML file application
• Key in address 302 Nichols Road, Kansas City, MO 64112 to Google Maps
.. see the latitude-longitude (39.041548,-94.592965) in the URL bar.
• Open this web page to create the circles & save results as KML file.
• Refresh this page if making a new KML file.
• Set the colors and lines to medium, blank and clear.
• Enter coordinates — key in lat 39.041548 and lon -94.592965
.. these for for this example
.. enter the values for your location of interest
Add center point
• In the Radius Distance, key in 0.05 miles
• Click Draw Radius blue button (at right of longitude).
Add site 1 circle
• In the Radius Distance, key in 1.00 miles (use preferred radius for inner circle).
• Click Draw Radius blue button (at right of longitude).
Add site 2 circle
• In the Radius Distance, key in 3.00 miles (use preferred radius for inner circle).
• Click Draw Radius blue button (at right of longitude).
View study area geography
• Optionally navigate up to the map view and make the view similar to the graphic at the top of this page 
.. this step is not required but might be useful to verify the study area appearance.
Save KML file
• Navigate down the page to “Google Earth KML Output”. Click the blue button Generate KML.
• Click “Download KML file Here.” Save the file to a folder and make a note of the file path and name
.. save the file as c:\sitereport\302nichols.kml (this file and filename are used below).
Done
• The three part KML file has been created and saved to the local computer. 
• Finished using this browser application.

This same process may be used again to create similarly structured KML files of any radius about any point for any location in the world. 

Loading a KML file into Google Maps
Optionally create the objective map graphic using the following steps. Or, the KML file may be used with the CV XE GIS software (see below) enabling yet further analytical possibilities. 

 Click this link to start the Google MyMaps application.
• When the new page opens click create new map button
• Next click import button
• Enter the file path/name as created above (c:\sitereport\302nichols.kml), or any KML file.
• Edit the MyMaps rendering to achieve preferred view.
• Use preferred screen capture tool to save that part of the map view as a graphic for the study report.

Using the KML File with an Existing GIS Project and converting the KML file to shapefile structure

1. Add the KML file to an Existing CV XE GIS Project
• Start the CV XE GIS software and open the project file c:\cvxe\1\cvxe_us2.gis (distributed with installer).
.. uncheck Locations and $MHI x BG layers in legend panel.
• Click the AddLayer button (second button from left on toolbar)
• Select the KML file that was created above (c:\sitereport\302nichols.kml) .. circles appear in the map window.
• Use LayerEditor to adjust settings for KML layer (transparent, bold outline)
• Navigate to zoom-in view and smaller map window.
• Use Toolbar button Save to Image (button 7 from left) to save the map window view to a .jpg file.

Navigate to this view:

2. Converting a KML File to a Shapefile
This step requires the CV XE GIS Basic or higher level version. After the KML layer appears in the above sequence, proceed as follows:

• Click File>ExportShapefile.
• Select the KML layer name.
• Set Coordinate System edit box value to NAD83.
• Click OK button.
• On the Export Layer/FileSave dialog, select an output file path and name.
• The shapefile is generated and may be reused with any GIS project.

3. Editing attributes of the study area shapefile and project file
There are three shapes in the shapefile (center point, circle 1, circle 2). 
Modify the appearance of these shapes/objects by using the Select tool (mouse in Select mode).
• In legend panel click on circles layer; name turns blue indicating this is the active layer.
• In the map window, click in the circle; the profile/editor appears (pop-up)
• Initially all three shapes have the name “Polygon”.
.. change the object names successively to Point1 (the small circle), Circle1 and Circle2.
• The shapefile attributes have been permanently changed.
• When each shape/object has been renamed, use the LayerEditor to modify the appearance of each shape.
.. the changes modify the project file and not the shapefile.
.. optional save the project (overwriting the former version) or save the project with a new name.

Renaming a shape to “Point1”
Click for larger view

Using LayerEditor to set attributes of the study area layer
Click for larger view

View of final study area layer in context of broader project
Click for larger view

View as above with $MHI x BG checked on/visible
Click for larger view
 

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

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. Contact Warren. Join Warren on LinkedIn.

Crime Data Analytics

Goto ProximityOne .. examining crime incidence and socioeconomic patterns and analyzing small-area and location-based data.

.. what are the crime patterns in neighborhoods or areas of interest? It is challenging to get useful answers to this type of question. Crime incidence data by location/address are often difficult or not possible to obtain. Even where the location-based crime data are available, the data must be geocoded, e.g., assigned a census block code to each address. Separately demographic-economic must be organized to examine contextually with the crime data.

Integrating Crimes by Location & Patterns of Economic Prosperity
– View developed using CV XE GIS and related GIS project.

Crime Data Analytics. Use the Crime Incidence and Socioeconomic Patterns GIS project and associated datasets to explore relationships between crime and small area demographic-economic characteristics. Follow the steps described below to study patterns and relationships in Kansas City and/or use this framework to develop similar data analytics for other areas.

Framework for a case study. 409 of Missouri’s 4,506 block groups are within the jurisdiction of the Kansas City police department (KCPD) and had one or more crimes in 2014 (latest fully reported year). There were approximately 10,400 crimes recorded by the KCPD in 2014, in the city area spanning four counties. In this section tools and data are used to examine crime patterns in Kansas City, MO. Crime data are included as markers/locations in a GIS project. Crime data are also aggregated to the census block level and examined as summary data (aggregate crimes by census block). Crime data are related to American Community Survey (ACS) 2014 5-year demographic-economic data at the block group geographic level.

To perform these types of analyses, it is important to start with location-based crime data that have been attributed with type of offense (offense code). Ideally, each crime incidence data record includes minimally the offense code and address of the crime. Such location-based crime incidence data have been acquired from the KCPD. These data are used to develop a shapefile that can be included in a GIS project.

Patterns of Crime Incidence in Kansas City, MO
The following graphic shows patterns of crime incidence by census block for the “Plaza Area” within Kansas city. This view shows all types of crimes aggregated to the census block level. Crimes committed where a handgun was involved are shown as black/red circular markers. Click the graphic for a larger view that shows legend and more detail.
– View developed using CV XE GIS and related GIS project.

Related views (click link to view graphic in new window):
Use the GIS project to develop variations of these views. Optionally add your own data.
Lay of the land: Kansas City city (cross hatched) in context of metro
All crimes as markers in Kansas City in 2014

Patterns of Economic Prosperity & Crime Incidence
The following graphic shows patterns of economic prosperity (median household income $MHI) by block group for the same general area as above. This view illustrates how two types of crimes (burglary blue triangle markers and homicide (red/black square markers) can be examined in context. Click the graphic for a larger view that shows legend and more detail.

– View developed using CV XE GIS and related GIS project.

Related views (click link to view graphic in new window):
Use the GIS project to develop variations of these views.
View similar to above, without $MHI layer

Data used to analyze patterns of economic prosperity/$MHI are based on the American Community Survey (ACS) 2014 5-year estimates at the block group geographic level. The same scope of subject matter is available for higher level geography. The GIS project/datasets includes many types of demographic-economic subject matter that can be used to display/analyze different socioeconomic patterns.

Using Block Group Geography/Data
Census Block Groups sit in a “mid-range” geography between census blocks and census tracts. All cover the U.S. wall-to-wall and nest together, census blocks being the lowest common denominator for each. Block Groups (BGs) are the smallest geographic area for which annually updated ACS 5-year estimates data are tabulated.

Advantages of using BG geodemographics include the maximum degree of geographic drill-down (using ACS data) … enabling the most micro-perspective of demographics for a neighborhood or part of study area. A disadvantages of using BG estimates is that typically the smaller area estimates have a relatively higher error of estimate.

Crime Incidence and Socioeconomic Patterns GIS Project/Datasets
1. Install the ProximityOne CV XE GIS
… omit this step if CV XE GIS software already installed.
… run the CV XE GIS installer
… take all defaults during installation
2. Download the CISP GIS Project fileset
… requires ProximityOne User Group ID (join now)
… unzip CISP GIS project files to local folder c:\crime
3. Open the kcmo_crimes_2014.gis project
… after completing the above steps, click File>Open>Dialog
… open the file named C:\crime\kcmo_crimes_2014.gis
4. Done .. the start-up view shows the crime patterns.

Weekly Data Analytics Lab Sessions
Join me in a Data Analytics Lab session to discuss more details about accessing location-based data and block group demographics and integrating those data into analytical applications.  Learn more about integrating these data with other geography, your data and use of data analytics that apply to your situation.

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. Contact Warren. Join Warren on LinkedIn.