Types & Typical Applications of DWH DWH-FarazAhmed Types of data warehouse • Financial • Telecommunication • Insurance • Human Resource • Global • Exploratory DWH-FarazAhmed.

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Transcript Types & Typical Applications of DWH DWH-FarazAhmed Types of data warehouse • Financial • Telecommunication • Insurance • Human Resource • Global • Exploratory DWH-FarazAhmed.

Types &
Typical Applications of
DWH
DWH-FarazAhmed
Types of data warehouse
• Financial
• Telecommunication
• Insurance
• Human Resource
• Global
• Exploratory
DWH-FarazAhmed
Types of data warehouse
Financial
 First data warehouse that an organization
builds. This is appealing because:
 Nerve center, easy to get attention.
 In most organizations, smallest data set.
 Touches all aspects of an organization, with a
common denomination i.e. money.
 Inherent structure of data directly influenced by the
day-to-day activities of financial processing.
Word of caution, will discuss, if and when time permits.
DWH-FarazAhmed
Types of data warehouse
Telecommunication
Dominated by sheer volume of data.
Many ways to accommodate call level detail:
 Only a few months of call level detail,
 Storing lots of call level detail scattered over different
storage media,
 Storing only selective call level detail, etc.
 Unfortunately, for many kinds of processing, working at
an aggregate level is simply not possible.
DWH-FarazAhmed
Types of data warehouse
Insurance
Insurance data warehouses are similar to other
data warehouses BUT with a few exceptions.
Stored data that is very, very old, used for actuarial
processing.
Typical business may change dramatically over
last 40-50 years, but not insurance.
In retailing or telecomm there are a few important
dates, but in the insurance environment there are
many dates of many kinds.
DWH-FarazAhmed
Types of data warehouse
Insurance
Insurance data warehouses are similar to other
data warehouses BUT with a few exceptions.
Long operational business cycles, in years.
Processing time in months. Thus the operating
speed is different.
Transactions are not gathered and processed, but
are in kind of “frozen”.
Thus a very unique approach of design &
implementation.
DWH-FarazAhmed
Typical Applications
Impact on organization’s core business is to
streamline and maximize profitability.
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Fraud detection.
Profitability analysis.
Direct mail/database marketing.
Credit risk prediction.
Customer retention modeling.
Yield management.
Inventory management.
ROI on any one of these applications can justify
HW/SW & consultancy costs in most organizations.
DWH-FarazAhmed
Typical Applications
Fraud detection
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By observing data usage patterns.
People have typical purchase patterns.
Deviation from patterns.
Certain cities notorious for fraud.
Certain items bought by stolen cards.
Similar behavior for stolen phone cards.
DWH-FarazAhmed
Typical Applications
Profitability Analysis
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Banks know if they are profitable or not.
Don’t know which customers are profitable.
Typically more than 50% are NOT profitable.
Don’t know which one?
Balance is not enough, transactional
behavior is the key.
• Restructure products and pricing strategies.
• Life-time profitability models (next 3-5 years).
DWH-FarazAhmed
Typical Applications
Direct mail marketing
• Targeted marketing.
• Offering high bandwidth package NOT to all
users.
• Know from call detail records of web surfing.
• Saves marketing expense, saving pennies.
• Knowing your customers better.
DWH-FarazAhmed
Typical Applications
Credit risk prediction
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Who should get a loan?
Customer segregation i.e. stable vs. rolling.
Qualitative decision making NOT subjective.
Different interest rates for different
customers.
• Do not subsidize bad customer on the basis
of good.
DWH-FarazAhmed
Typical Applications
Yield Management
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Works for fixed inventory businesses.
The price of item suddenly goes to zero.
Item prices vary for varying customers.
Example: Air Lines, Hotels etc.
Price of (say) Air Ticket depends on:
– How much in advance ticket was bought?
– How many vacant seats were present?
– How profitable is the customer?
– Ticket is one-way or return?
DWH-FarazAhmed
Recent Application
Agriculture Systems
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Agri and related data collected for decades.
Metrological data consists of 50+ attributes.
Decision making based on expert judgment.
Lack of integration results in underutilization.
What is required, in which amount and
when?
DWH-FarazAhmed