Sunday, January 29th, 2012

Urban Data the Easy Way

Some of you are familiar with my urban data platform Telestrian. I built Telestrian because I love to do posts based on analysis of basic census and economic data, but found it ridiculously painful to do because 1) all the free tools for this data suck and 2) all the tools that look like they are good are so expensive and/or hard to use I can’t buy them. So I decided to roll my own, and it is has literally cut the amount of time I spent doing data analysis by 95%. It saves me staggering amounts of time.

Now that I’ve got some experience with the platform and know what it takes to support, I’m re-launching for 2012 with a massive price cut of 88%. Telestrian is now only $49/year (not per month, per year). And you can try it for free for 30 days, no credit card required, no obligation.

They say the first rule of sales is that you have to ask for the business. Well, I’m asking for yours. If you work for an organization where you use Census and economic type data, please give Telestrian a try and buy it today. The cost is de minimis for any organization. And if you want to kit out your whole office or department, I can give you even better pricing. Just ask.

To whet your appetite, I’ll share a little of what the system can do. For more about the type of pain Telestrian was designed to take away, read my white paper. You can also see a list of features and functions.

World’s Easiest Thematic Maps

I love to do thematic maps of data. These are difficult to create without graphic design tools or complex and expensive GIS software. But for any data element in the system, Telestrian lets you create thematic maps for states and MSAs, plus national and state county maps. Map not just the raw data, but also things like percent changes, location quotients, etc. – it’s all built in. This is by far the easiest platform I’ve ever seen for creating basic thematic maps.

Here’s a map of the percentage change in population for US counties between 2000 and 2010 that I made in about 30 seconds.

This is the map that landed me on the front page of Yahoo since I was able to crank out Census analysis with compelling graphics faster than any media outlet in the country.

BTW: This isn’t Flash. It’s a picture file you can right click and save off for your presentation or whatever. And you can make it as big or small as you want with no resolution loss. (SVG is also available for graphic designers to use).

You can also make maps out of your own data by uploading a comma delimited file. (I give you the templates). This lets you map anything pretty easily even if Telestrian doesn’t include the data. For example, it doesn’t have election results, but I downloaded the 2008 presidential election info and uploaded the data to put together this results map:

Place to Place Migration

Telestrian also has place to place migration data from the IRS. You’d have to pay them $500 just to send you the raw files on CD, BTW – in the form of over 3,000 Excel spreadsheets. Telestrian processes this and make it easily queryable. It also takes the county-county data and calculates what is arguably more interesting, MSA-MSA and MSA-state migration. Plus instead of just the in and out migration the IRS gives you, gross and net migration are also available, intra-MSA migration, etc. Overall, there are more than 100 easy to use pieces of data out of this.

Here’s a quick map I did to show you what it can do. This is 2000-2010 migration for Indianapolis metro. Those metros with which Indy has net in-migration are in blue. Those with which it has net out-migration are in red.

Doing analysis like this would almost be mission impossible without this tool. It’s so painful that I only know a handful of even Ph.D. researchers doing metro-metro migration analysis. You rarely see it in regional talent studies, for example, even though a metro area’s talent networks are absolutely crucial in putting together a talent strategy. (If any research or other organizations are interested in getting the raw data behind this in a usable form, I’m happy to sell it to you. Just email me).

Data Mining

Go to your average free data site, and you’ll rapidly discover that you can look up facts or get a grid of numbers, but not much more than that. Want to know what cities grew their GDP the most last year? It’s way harder than it should be. But Telestrian has parameterized queries built in so you can answer basic questions, like, for example, the one I just asked:

Note that I only included metros over one million in this search. Setting a population threshold is one of the built-in parameters you can use. Again, this only takes like 30 seconds to make once you master the tool.

Give Telestrian a Try

This is just a taste of what it provides. There’s other life-savers, like the fact that the Census 2000 data has been re-baselined to current MSA definitions, so you can compare with current day data. And there are many other types of data as well.

Again, Telestrian is free to try for 30 days, so please give it a shot. Even if you did a trial in the past, just re-register and you’ll be re-enabled for another trial.

At just $49/year, it’s practically free to any organization with a budget. Buying a subscription today is a great way to support the work I do here at the Urbanophile. But more importantly, there’s huge value there that I’m confident is more than worth the price.

Now back to my regularly scheduled blog programming.

10 Comments
Topics: Demographic Analysis, Economic Development

10 Responses to “Urban Data the Easy Way”

  1. Evan says:

    Nice to see Indianapolis is drawing in people from places like NYC/LA/SF etc.

  2. Christopher says:

    I so wish something like this was available to Canadians. Is it easy enough to import data from other sources?

  3. Christopher, right now you can’t import foreign data. I decided to focus on US domestic data only. Part of the challenge is that data between countries is not always comparable on an apples to apples basis.

  4. Elliott says:

    Are counties and MSAs the smallest level geography available? How about cities? Census tracts?

  5. Elliott, I include city-level data where the data sets support it. My focus in building the tool was the metro area level, which is where I do most of my analysis, but for any data set I take city, county, state, and national data too where it is available (plus MD, CSA, EA, NECTA). I do not do census tract, zip code or more granular data.

  6. CityBeautiful21 says:

    Consider a product that works with more granular data. Something better than the Census American FactObscurer website might find a wide, wide audience at this price point.

  7. CityBeautiful21, I don’t often work with data at that level, so don’t know what the problems are. So I’d be taking a stab in the dark as to the use case to try to build something. I agree Fact Finder is garbage. Part of the reason why is that there’s no use case in the tool. If I get more of a feel for the best ways to use that data, and the appropriate use cases, I may expand to include it. The functionality in the system isn’t necessarily specific to any type of data entity.

  8. Charley says:

    Great to see you’re relaunching this! I didn’t catch when reading through the features before that you can upload data into the mapping functionality. Something like that is incredible even if you didn’t have the data to back it up.

    If you ever start moving into international data let me know, I have a few tips on how you could deal with the comparison issues you mention.

  9. Chris Barnett says:

    Aaron, major US cities get HUD money for housing and community development. Depending on the allocation process, either the city staff or nonprofit development entities have a need to extract certain specific data by Census Tract: household income, homeownership rate, single head of household rate, poverty rate, senior population, and disabled persons.

    Even more important, such organizations must often aggregate data over a smaller-than-city geography that aligns to Census Tracts or Block Groups.

    There’s one use-case that fits a $49/year subscription.

  10. Chris Barnett says:

    Meant to add that the data often needs to be compared with City or County or Metro mean or median.

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