Data Warehouse 8

7/29/2019 Data Warehouse 8

1/25

Data Base and Data

Warehouse

The difference between operational

CRM and Analytical CRM


2/25

Which of the customers have been steadily

increasing their purchases from Slim Well

(making world a slimmer place) during last

two years?

Which one showed a decrease in the

purchase pattern?

Is this because these customers are gettingthinner over time, and therefore, do not need

our products any more**

** This makes us ponder further


3/25

Operational CRM Database.. Current data which isjust useful for current queries. (one month old or a fewmonths old.)

Example A bank would have its branch accountingsystem, which the teller at the branch uses to performone transaction such as withdrawing or depositingmoney, crediting interest or deducting bank charges,etc.,

Or a telephone company, which uses billing softwareto keep track of the details of every call made.

Or any organisation which has implemented an ERPsystem, which might be used for transactions such as

raising an individual invoice, keeping track of eachindividual payments or issuing one item from stores.

In todays world all these systems work on-line. Sothe term On-line transaction processing or OLTP


4/25

Analytical CRM Data warehouse ..

Maintains old data as old as is necessary to

answer management queries.


5/25

Database Data Warehouse

Used in OLPT systems Used for analytical queriesOperational staff By management

Usually up-to date Up dated on monthly basis

Stores details of every

transaction

Stores summary data

Usually stores current

data with perhaps recent

history

Stores historical data,

usually in snapshots taken

at regular intervalsUsually normalised doesnt need to be

normalised

Updated from the

database


6/25

Definition

Data warehouse is a large reservoir of detailed

and summary data that describes the

organization and its activities, organized by the

various business dimensions in a way thatfacilitates easy retrieval of information that

describes the organization's activities.


7/25

Data mart is a subset of the data warehouse

that is tailored to meet the specialized needs

of particular group of users


8/25

Data Warehousing Objectives

Ensure that the warehouse data is accurate

Keep the warehouse data secure

Make the data easily available to authorizedusers

Maintain descriptions of the warehouse data sothat users and systems developers can

understand the meaning of each element


9/25

Data Warehouse System

Staging

Area

Management

And

control

Data

Gathering

system

Information

Delivery

system

Warehouse

Data

repository

Metadata

repository

Data flow

Control flow


10/25

Data Warehouse Architecture

Four components- two providing a processing

capability and two providing data to be used

in processing

Staging area and management and controlperforms the processing capacity.

Data is provided by the warehouse data

repository and the metadata repository


11/25

Management and Control

The Management and control components are like a

traffic officer standing in the middle of a streetintersection, controlling the flow of traffic through theintersection.

M&C causes the following data flows:

Into the staging area Through the staging area as the various screening

processes are performed

From the staging area to the warehouse data

repository From the warehouse data repository to information

delivery

From metadata repository to information delivery


12/25

Staging Area

This is where data is prepared to be moved

into the warehouse data repository and

metadata repository

ETL extraction, transformation and loading

The data has to be extracted from internal

databases and files and combined with data

from other external sources


13/25

Extraction

The data must be extracted from thedatabases and files which includes internaltransaction processing systems, marketing

research and marketing intelligence and alsosuch external sources as customers,suppliers and the government

The data must be transformed into a format

for loading into the warehouse a processthat includes cleaning, standardizing,reformatting and summarizing.


14/25

Transformation of Data Includes

Cleaning the data for inaccuracies andinconsistencies

Standardizing involves converting the cleansed datato a uniform format for data element names, codes(

customer codes, product codes and geographiccodes) and units of measurement (dozens, pounds)

Reformatting is required when the gathered data is ina different format than that of the warehouse datarepository

Summarizing is performed so that requestedsummary information can be presented without theneed for processing, thus speeding up the delivery


15/25

Loading

When data is written into the data warehouse, the

data is loaded. It is kept updated by adding new

data on a periodic basis.

Once the ETL processes are completed, the dataresides in the warehouse data repository, waiting to

be used.


16/25

Warehouse Data Repository

The data is stored

The data content in the data warehouse gives

a compilation of geographic, demographic,

activity, psychographic and behavioral data.


17/25

Geographic Data

Geographic data describes where the

customer is physically located and where the

customer-related transaction or activity

occurs


18/25

Demographic Data

This consists of those customer

characteristics that are either permanent or

slow to change.

Examples: gender, birth data, ethic origin,religion


19/25

Activity Data This traces the activities of customers as they

interact with the organisation by making purchases,returning items, making inquiries, seeking servicesand so on.

This data is generated in high volumes each day by

the transaction processing systems andtelemarketing systems

This data is useful to find the RFM score andsupport such marketing strategies as cross-sellingand up-selling

The data can be furthered used to reveal shoppingbehavior patterns and be used to project eachcustomers lifetime value


20/25

Psychographic and Behavioral Data

Psychographic data consists of psychological

and sociological characteristics that influence

customer behavior

Behavioral Data captures the uniqueshopping behavior patterns and consumption

habits of individual consumers

Warranty card can be used get this data


21/25

Warranty card

The main reasons for purchasing the product

How the customer learned about the product

A special occasion (such as birthday or

anniversary) for which the purchase wasmade

Recent activity in making purchases by mailor over the internet

Activities (hobbies and interests) of personsin the household


22/25

Data mining is a collection of process that

enables a data warehouse user to learn of

patterns, relationships and trends in data not

previously known to exist


23/25

Data Mining

Using the past data to find patterns.

These patterns together give a model whichhelps predict the future

This process is predictive modeling

Data mining can be directed and undirecteddata mining

When the goal of finding patterns is not

known it is called undirected data mining. When the goal of finding patterns is known it

is called as directed data mining


24/25

Data Mining Functions

Harrahs gambling casino organization mines its datawarehouse. It offers its customers a frequent gamblermagnetic stripe card, called Total Rewards, which can be usedto get free trips, meals and hotel rooms.

Based on the data mining the casino is able to cluster theircustomers into demographic grouping.

Identify associations among gambling machines

And even project sequences in which the machines will beused.

The customers can be classified into those who give morerevenue.


25/25

Data Mining Functions

Classification helps the companys to divide thecustomers based on the customers behavior so thatspecial products and services can be offered to morevaluable classes

Clustering is identifying customers with similar

characteristics who can be tapped with a particular typeof marketing program

Associations are relationships between such entities asproducts.

Sometimes there might be a pattern or sequences in a

customers purchase behavior.

Documents

Data Warehouse 8