Corporate Data Analysis
Our tools were designed to analyze customers (accounts) and the transactions that are associated with them. The reason that we can analyze long form census data so effectively is because of the similarities between account data and household data.
- Both have high level records (accounts or households)
- Both have potentially many low level records (transactions or people) associated with each high level record
- Both the high and low level records have many data items
- Both account and census data tend to have large volumes
Our tools have been used for years in the telephone industry, and we are looking for other areas to use them. Census data serves three purposes:
- It allows users to become accustomed to our capability without making a significant commitment
- It conclusively demonstrates that our tools are not "Telephone Analysis Tools" - Our tools are multilevel data analytical tools, and should work equally well with banking, retail, credit card, telephone, and census data
- It allows us to serve a different market
Think about the questions you have about your own data, and see how we would solve it in the census data. Instead of thinking race, gender, and profession, think about your own product/service attributes. Talk to us about questions you have on your own data, and we'll put together a census example to show how we would handle it, and how quickly it can be done.
Imagine going to your CIO and telling them that you want a 5 dimensional tabulation of your account and transaction data, and you want it done by tomorrow. They'll tell you it can't be done. Then ask us. With our tools, it's an everyday event.
If you want a genuine comparison of our tools vs. a typical IT shop approach, have us do a multidimensional tabulation with user defined dimensions and simulations. Then call the IT shop at the census bureau, and ask them for a time and cost for the same tabulation.
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