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Problem Statement:
ATT is a large telecommunications company and they have really good data about phone calls globally.
They would like to build new business services around the nice data assets that they have, similar to a data broker. One beautifully rich data set they have is Call Detail Records (CDRs). They would like to build a data broker service around this internal data. (google: call detail records).
There are privacy restrictions around data that they can sell, but they can derive new data fields from their rich proprietary data. If averaged at a large enough geographical region (zip9, zip5, zip3?) these derived fields can be sold. Also, they can sell new fields at the customer/address/phone number level that are derived from CDR fields if the new fields are of a different nature than the CDRs. This would allow them to sell a segment label/description.
They see a company called Claritas and others that make a lot of money selling highly descriptive consumer segments (google: Claritas PRIZM segments).
An ATT executive wants to build such a data broker business, selling such demographic-like segments built using the CDRs. Let’s start with the U.S. only. Design a process to build PRIZM-like segments using CDR records.
Requirement:
Here are three examples (see attached files) of pretty good submissions for homeworks. It’s best if you begin by stating what the business problem is, in your own words, so it’s clear to the reader that you understand the problem. Then describe the proposed solution approach. If appropriate, you can also describe any assumptions you made, particularly about data that is needed. You might describe several solution paths depending on what data might be available. Describe the input and out put of the framework you designed.
The goal is for the reader to read it, easily understand it, and believe it will work well to solve the problem. It’s not enough to have a great idea – you also need to communicate it well.
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