FAQ

First, make sure you’ve exhausted the possibilities we’ve listed elsewhere in this resource.

Don’t despair! Your service region like has subregions that are recognizable to you, like counties, cities, or even zip codes. More good news – these geographic identifiers are likely already in your case management system (CMS). In excel, or possibly even directly in your CMS, you can calculate frequencies of particular variables for these identifiers.

Even without maps, it is still useful spatial information to know, for example, the top 10 cities for intakes, or the top 10 zip codes for foreclosure assistance. Based just on a frequency table, a spatial pattern might suggest itself to you for further investigation.

For maps of your CMS data, there are several online services that will translate your addresses into “pin maps”. Some services are free, some are not, and naturally the range of options varies. A good place to start is the Geoservices Portal of Texas A&M University. Not only do they provide free services, they provide a list of others (and their prices) who do the same.

Most of the external demographic data we used originated from the US Census Bureau. American FactFinder is one of the primary interfaces you will use once you are at the Census webpage. Their Guided Search is a good place to start. It asks basic questions to narrow down your search, and at the end will produce presentation-ready tables, maps, or data for download.

For mapping, our boundary files also came from the Census, via their Tiger Products page.

One option is to seek out training directly from ESRI, the company that produces ArcGIS. They have a variety of in-person and web based options available.

Another option would be to seek out a university course in Geographic Information Systems. We have compiled a list of academic departments and Universities (sorted by state) likely to have a curriculum in GIS.

A wide range of academic departments are now likely to house at least some geographic expertise. Our list of academic departments and Universities (sorted by state) is a good starting point.

The internet is full of Excel tutorials. A simple search on YouTube will turn up thousands of options.

Chandoo.org is a site I’ve found to be particularly helpful. It is a vast site dedicated MS Excel. It has a section on Excel Basics, and also 10 tutorial videos for Excel beginners. If you’re beyond that level, there is a section on Advanced Skills too.

Once you have your organization’s data in Excel, we think the most useful tools are (in no particular order):

• Basic calculations, so that you can create totals, averages, highs, lows, and trends;
• Charts and graphs, so that you can visualize the specific data and trends that you are interested in;
• Filtering, which allows you to select particular subsets of data, like a legal problem, or a calendar year, or a client demographic;
• Pivot tables, allowing you to create summary tables of larger data sets.

We obtained all of our Census data through the American FactFinder.

While data from the American Community Survey might be the most popular data product accessed through American FactFinder, there are actually a wide variety of data available through this one location.

They are listed here: What We Provide – Learn about the data available in American FactFinder.

Although there is a brief overview of the different ways of accessing data through American Factfinder (It is located here: Using Factfinder – Getting started with American FactFinder) we think a better route is to start with the American FactFinder Virtual Tour, located here, and then to get an overview of FactFinder by reading through its help site, here: FactFinder Help, Table of Contents.

We think a good entry point to American FactFinder is through its Community Facts portal, where all you need to start is the name (state, county, city, or town) or zip code of the place you are interest in.

Many of our analyses compare an eligible population to that population served by an organization. For example, if we are interested in eligible minority households, we can find population information through American FactFinder on households in poverty by race/ethnicity. Then, we might query our internal data to find out how many minority households were served. We might compare these numbers across time, or within a single geography (such as a neighborhood). But the data aren’t always perfect.

For example, you might not be able to find exactly the external data you are looking for. Perhaps the census reports different income ranges (clouding eligibly questions) or has different race/ethnicity categories than your internal data. Conflicts like these are common.

So, what to do? First, remember that it would be unwise to use a single data analysis or data comparison to solely inform an important decision, even if the data were perfect! Rather, it is better to see these analyses as part of a complex picture. The better the data, the larger the part those data might play in that complex picture. But there will certainly be situations where one will discover useful information from imperfect data, and find nothing useful from near-perfect data.

It isn’t necessary to avoid using data when they aren’t exactly what you are looking for. It is necessary, however, to scale your conclusions (and enthusiasm) proportionally to your confidence in the input data – and that could apply both to internal and external input data. Keep in mind the context of these data analyses being but one component of a broader effort aimed at better understanding different dimensions of your organization.