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a series of departmental databases containing customer, product, and related data.
While the billing and sales views were often overlapping in these applications, it
was not easy to map one to the other.
The past 10 years have seen a rapid rise in MDM for customer and product
data across the enterprise. Analytics applications were the irst consumers of
master data to create mappings across multiple hierarchies as well as fragmented
customer and product identiiers. MDM then graduated to transactional appli-
cations with much of the focus on business solutions, speciically customer
relationship management (CRM) and billing systems. We can now use Big Data
to build a comprehensive view of customer, network, and external data as demon-
strated in the following case study.
Jim and Mary Smith have two children, Corey and Karen. The family has
four phones, one for each family member. Corey and Karen are in high school
and have basic phones for calls and text. Jim has an iPhone, which he uses
primarily for ofice calls and emails. Mary has an iPhone and a WiFi-only iPad.
She uses her iPad for investment research and participates in inancial blogs.
When Jim received a brand-new iPhone from his employer as part of an
upgrade program, he decided to give his older iPhone to Karen. Karen decided
to sell her basic phone to a friend. Since they were in the last six months of their
contract, the Smith family decided to keep the friend's phone on their plan until
the end of the period. Karen's friend paid her for basic phone and messaging
service.
The CSP providing phone service to the Smiths had done extensive house-
hold analysis to develop a customer hierarchy of their residence that tagged
phones to users and connected all the users to the family account. After the
changes mentioned above, the CSP's analytics applications would likely display
abnormal calling patterns for the users compared with historical norms. In
addition, Jim's old iPhone would show a number of web transactions that tracked
to Jim's user ID but exhibited web browsing behaviors that were characteristic of
a teenager. Karen's phone is now “hanging-out” in a new geohash.
Network data provides the best view of customer usage and trouble infor-
mation. If this data is harnessed and offered as a strategic asset to others in the
organization, it can provide a far more comprehensive understanding of the
customer. In many cases, it may not even be important to connect the phone
exchanges to the PII. The location and usage patterns may provide valuable
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