The document provides a comprehensive guide for nonprofits on data visualization, emphasizing the importance of cleaning, preparing, and contextualizing data before visualization. It outlines various tools and methods for data cleaning and visualization, including pros and cons of popular software like Excel, Tableau, and GIS options. Additionally, it highlights the significance of exploring data within context to enhance meaningful insights and presents resources for data access and visualization assistance.

1. Nonprofits & Data
Process and Tools: How to Visualize Your Data
340 N 12th St, Suite 402
Philadelphia, PA 19107
215.925.2600
info@azavea.com
www.azavea.com

2. About Us
Tamara Manik-Perlman
Project Manager
tmanik-perlman@azavea.com
215.701.7687
Jeremy Heffner
Product Manager
jheffner@azavea.com
215.701.7712

3. About Azavea
• Founded in 2000
• 32 people
• Based in Philadelphia
– Boston office
– Minneapolis office
• Geospatial + web + mobile
– Software development
– Spatial analysis services

4. Clients & Industries
• Arts & Culture
• Elections & Politics
• Public Health
Carnegie
• Land Conservation Mellon
• Public Safety
• Human Services
• Municipal Services
• Economic Development

5. B Corporation
• 10% Research Program
• Pro Bono Program
• Time-to-Give-Back Program
• Employee-focused Culture
• Projects with Social Value

6. How to Visualize Your Data

7. Agenda
• Cleaning & Preparing Data
• Assembling Data & Building Context
• Exploring, Presenting & Sharing Data Visualizations
• Q&A

8. Cleaning & Preparing Data

9. Data Cleaning: Your Questions
• At what point in the data maintenance process do you
find yourself cleaning data?
• Are there ways that you would like to improve the
workflow?

11. Cleaning & Preparing Data
• Making sense of data starts at the point of collection
– Define what you want to measure / track
• Clearly define schema and fields
– Have a shared meaning for values
– Data validation on entry
– Collect your data
– Examine results
• Are there common mistakes you could prevent?
• Are there different interpretations of fields?
– Close the feedback loop & iterate

12. Cleaning & Preparing Data
• Common data quality issues
– Combined fields
• Address: “340 N 12th St, Suite 402 , Philadelphia, PA 19107”
– Invalid entries
• ZIP code: 1234 (length check, is number)
• Age: 204 (reasonable range check, is number)
– Format variations
• State: PA vs. Pennsylvania (drop down or scrubbing rules)
– Duplicates
• CRM: John Smith with old and new addresses

13. Cleaning & Preparing Data
Not a reasonable option

14. Cleaning & Preparing Data
• Tools to clean tabular data
– Excel (or open source equivalent)
• Pros:
– Broad features
– Widely utilized / common skill
– Formulas / sorting / flexible
• Cons:
– Doesn’t understand record concept
– Mass changes can be tedious

15. Cleaning & Preparing Data
• Tools to clean tabular data
– DataWrangler
• http://vis.stanford.edu/wrangler/
• Pros:
– Focused on transforming data into relational format
– Live previews
• Cons:
– Alpha quality version
– Data size limits / online tool
– Can be difficult to figure out what set of transforms are needed

16. Cleaning & Preparing Data
• Tools to clean tabular data
– Google Refine
• http://code.google.com/p/google-refine/
• Pros:
– Understands record concept
– Formulas / Facets
– Undo capability
– Windows / Mac / Linux
• Cons:
– There is a learning curve
– Unusual type of app
» Download, unzip, run exe file, access through browser

17. Assembling Data & Building Context

18. Context: Your Questions
• What challenges have you faced putting your data in
context?
• Are you struggling to identify what “context” means for
your organization?
• Do you know what data you’d like to use, but have
trouble finding it?

19. Your Data in Context
• Your data is essential!
• But it is more meaningful in context…
– Ratios & rates
• Service level
• Market penetration
– Indicators & trends
• How you compare
– Targeting
• Key demographics Juice Analytics
• Custom summaries

20. Making Sense of the Census
• American FactFinder
• http://factfinder2.census.gov
– Decennial Census
• Every 10 years
• Full population survey
• Just 10 questions
– American Community Survey (ACS)
• Monthly sample
• Aggregated over different time periods (1-, 3- and 5-year)
• Extremely detailed questions
• Subject to sampling error

21. FactFinder Frustrations

22. Helpers: Social Explorer
• http://www.socialexplorer.com/
• Data Dictionary
– Survey
– Dataset
– Table
– Variable
– Formula
– Population

23. Helpers: Social Explorer
• Background
– Key Terms
– Collection Methodology
– Uses & applications

24. Helpers: ACS Alchemist
• https://github.com/azavea/acs-alchemist
• Retrieval of block group-level data
• Custom variable selection
• Delivery in spatial data format ready for mapping
This tool was developed by Azavea in collaboration with Jerry Ratcliffe and Ralph Taylor of Temple
University Center for Security and Crime Science. This project was supported by Award No. 2010-DE-BX-
K004, awarded by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice.

25. Helpers: ACS Alchemist
As easy as 1-2-3
2.Create a document with your selected variables

26. Helpers: ACS Alchemist
As easy as 1-2-3
2.Create a document with your selected variables
3.Pick your geographies

27. Helpers: ACS Alchemist
As easy as 1-2-3
2.Create a document with your selected variables
3.Pick your geographies and geolevels
4.Retrieve your shapefiles

28. Other Sources
• Public data
– Open Data Portals
• Federal, state & local data
– Political Data
• Voter data
• Legislative boundaries
• Commercial data
– Population Projections
– Consumer Data

29. Exploring, Presenting & Sharing Data Visualizations

30. Data Visualization: Your Questions
• Do you currently share data with your constituents?
• Where do you use data visualizations (e.g. annual report,
embedded infographics, live data trackers)?
• Do you currently map your data?

31. Exploring Data
• Visualization tools
– Tableau
• http://www.tableausoftware.com/
• Pros:
– Flexible interface makes data exploration easy
– Fast even on large data sets
• Cons:
– Easy to visualize something that doesn’t make sense to look at
– Price (for desktop tool)

32. Exploring Data
• Visualization tools
– ArcGIS Explorer online
• http://www.arcgis.com/explorer/
• Pros:
– Supports many data formats
– Online digitizing
– Integration with other Esri services
– Presentation view / mobile app
• Cons:
– Can’t export geocoded results
– Geocoding limited to 250 records

33. Exploring Data
• Visualization tools
– GeoCommons (GeoIQ)
• http://geocommons.com/
• Pros:
– Intuitive interface
– Analysis tools
– Geocoding for up to 5,000 records
– Supports KML (Google Maps) import & export
• Cons:
– US-only geocoding

34. Exploring Data
• Desktop GIS: Proprietary
– Esri ArcGIS
• Pros:
– Industry standard
– Many tools
– Extensive training materials
– Customer support
• Cons:
– Windows only
– Potentially expensive *
*

35. Exploring Data
• Desktop GIS: Open Source
– Quantum GIS (QGIS)
– GRASS
– uDig
• Pros:
– Free
– Multi-platform (Windows, Mac OS, Linux)
• Cons:
– Limited functionality (for advanced users)
– Community-based support

36. Q&A

37. Contact Us
Tamara Manik-Perlman
Project Manager
tmanik-perlman@azavea.com
215.701.7687
Jeremy Heffner
Product Manager
jheffner@azavea.com
215.701.7712