Data Visualization in a Mashed-Up World

I've been invited to participate in a DMRadio round table about visualization and mashup. If you're interested, please visit this site to register.

US Job Losses

There's plenty of political posturing about the current recession and whether the American Recovery and Reinvestment Act (Obama's stimulus bill) helped. I never rely on conjecture, so I went in search of facts. These were easy enough to find from the Bureau of Labor Statistics. Then, instead of staring at raw numbers of unemployment values, I substracted consecutive values to see the differential of the Job Losses (in other words, the rate of change or velocity) from month to month. Out of curiosity, I also gathered the numbers for men and women. I plotted these on a chart, added an annotation for when the stimulus bill was passed, and then added trend lines (using least-squares) to smooth out the jaggedness. Here's the resulting graph, which you can click on to see the code for:

Wal-Mart Stores Over Time

Here's the latest visualization I created, showing the growth of Wal-Mart over the years. What's really interesting is the local focus for the first 20 years.

NYC District Data Analysis

The City of New York is running a contest to develop the best data visualization application using public data from various NYC departments. This is to help promote http://www.nyc.gov/data

The easiest way to participate is to build a dashboard using Visualize Free, and then submit it on http://www.nycbigapps.com/. The deadline is tomorrow.

Here's my entry: http://visualizefree.com/public.jsp?id=sYixthhp

And the listing: http://www.nycbigapps.com/application-gallery/analysis-of-district-data-on-an-interactive-map

Black Friday 2009 Offer Browser

Using Visualize Free I created an interactive flash tool to slice and dice all the best shopping deals for this year's post-Thanksgiving buying craze.

The Black Friday dashboard allows you to filter by store, brand, category, price, discount, doorbuster, and more. It currently has over 7000 special deals, and I'm going to be adding more.

Free Visualization

I think it's about time for another shameless plug. However, this time it's for a free service that InetSoft provides.

We just launched a website (http://visualizefree.com) that will allow you to use our software for free, without downloading anything. Better still, you can upload your own data and create your own dashboard!

Once you create your dashboard, you can easily send your friends a link, or embed it in your own web page. Take a look at the simple example I put together for the unemployment rate (if the small iframe below is too cramped, open a new window by clicking this link).

Move the ends of the slider to adjust the time period displayed. For a real kick, click the pencil icon in the upper right corner of the chart to change what fields it displays.

Forrester: Mighty Mashups

James Kobielus, an analyst at Forrester Research, recently published Mighty Mashups: Do-It-Yourself Business Intelligence For The New Economy.

Jim does a pretty good job covering the inefficiencies and bottlenecks that mashup can address, and he touches the same points as Business Case for Data Mashup. Jim then goes on to list the "principal data mashup functions", including source-virtualization, publishing, and collaboration. At this point, I'm onboard and agree with everything he's saying.

Then, as Forrester is wont to do, they make sure to emphasize governance and the role that IT plays in securing the component data sources in a mashup environment. I'm still with him, and this got me thinking again about the relationship between IT and self-service.

Next, Jim lays out the Maturity Model, and I'm impressed. His characterization of the 4 levels of BI mashup make a lot of sense, and I'm thinking that this paper is building up to a ringing endorsement of InetSoft as being the only vendor who enables the whole spectrum.

Okay, let's calm down and take a step back. Kobielus explains that BI mashup isn't a panacea, and it may not fit your organization if your employees' personalities don't mesh with the self-service culture. I buy that, because I've seen it firsthand.

Then, strangely, Jim says, "Evaluate BI solutions for their integration of in-memory OLAP engines, semantic virtualization, EII, and other core mashup features." And there's a table with 4 columns: in-memory BI client; data virtualization/EII; interactive browser-based visualization; and automated source discovery. Where is this coming from?

I'm happy that InetSoft was one of only 6 vendors chosen to occupy this table (13 were interviewed), but the first and last criteria aren't on the same level as the middle two. In-memory data processing is nice (we also leverage this technique), and I'm sure that if automated source discovery works it can save a little upfront setup time, but I don't understand why these are given equal weight with the two halves of BI mashup (data mashup, and presentation mashup). What happened to governance and collaboration? I think these would be more appropriate as high level criteria.

Jim ends the paper on a high note by detailing a few best practices for organizations considering adding self-service capabilities: enforce governance; make a culture-shift; consider different roles; and enable collaboration.

Overall, it's a good paper, and validates many of the things that I've been saying for a while. I'm going to dismiss the minor digression, and focus on the overall lesson: BI mashup means providing maximal self-service, which is the fastest way to see bottom-line benefits from business intelligence.