1. MITP 5313 Current Trends of Database
Technology
ISSUE IN DATA WAREHOUSING
AND OLAP IN E-BUSINESS
Presented By Tamer J. Abbas
7 December 2013
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2. Outline
 Introduction
 What is a Data Warehousing
 Why need Data Warehousing
 What is OLAP
 Problem Statement
 Research Objective
 REFERENCES
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3. Introduction
 Decision Support Systems (DSS) are rapidly becoming
essential to achieving a competitive advantage for
businesses. DSS allows businesses to obtain a huge
amount of data that are locked in operational databases
and other sources of data and turn data into useful
information. Many companies have already construct or
are constructing decision-support databases called data
warehouses, in which users can perform their data
analysis. A typical data warehouse extracts, integrates and
manages
the
relevant
information
from
multiple, independent, heterogeneous data sources into
one centralized repository of information to support
decision-making needs of knowledge workers and decision
makers in the form of Online Analytical Processing (OLAP)
(Han & Kamber 2001, Harinarayan et al. 1999).
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4. What is a Data Warehousing?
 A single, complete
and consistent store
of data obtained from
a variety of different
sources
made
available to end users
in a what they can
understand and use
in a business context.
[Barry Devlin]
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5. What is a Data Warehousing?
Information
A process of
transforming data into
information and making
it available to users in a
timely enough manner
to make a difference.
[Forrester Research, April 1996]
Data
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6. What is a Data Warehousing?
“A Data Warehouse is a
subject
oriented, integrated, n
onvolatile, and time
variant collection of
data in support of
management’s
decisions.”
[Bill Inmon, Building the Data Warehouse 1996]
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7. Why need Data Warehousing?
ESCALATING NEED FOR STRATEGIC INFORMATION
grew
complex
need different kinds of
information that could be
readily used
keeping the enterprise
competitive
formulate the business
strategies, establish goals, set
objectives, and monitor results
spread globally
competition fiercer
strategic information
not for running the
day-to-day operations
continued health and
survival of the
corporation
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8. What is OLAP ??

Online Analytical Processing, a category of software
tools that provides analysis of data stored in a database.
OLAP tools enable users to analyze different dimensions
of multidimensional data. For example, it provides time
series and trend analysis views. OLAP often is used in
Data Warehousing and data mining.
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9. What is OLAP ??
 The chief component of OLAP is the OLAP server, which
sits between a client and a database management
systems (DBMS). The OLAP server understands how
data is organized in the database and has special
functions for analyzing the data. There are OLAP servers
available for nearly all the major database systems.
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10. Problem Statement
The dramatically increase in
companies
transactions meet by increase in their database
transactions, data storage and quires which used to
retrieve data from database, these companies use the
information processing system which is used for storage
of everyday activities of these events on a regular basis
about the company. Information processing systems rely
on online transaction processing (OLTP), which have
some or all of the necessary data that he is not so easily
accessible to the user for analytical data processing. The
majority of information processing systems functionality
is to generate reports which show daily transactions and
activities which are done by companies, the response
time for these reports is time consuming specially in
information system which depends in OLTP,
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11. Problem Statement Con.
which is not good for user who holds critical positions
such as top management, dissection maker and other
concerned top level authority because the time factor is
considerable for them. Moreover, Relational database
was not designed to support multi dimensional view
Advanced data presentation functions, advanced data
aggregation,
consolidation,
and
classification
functions, advanced computational functions and
Advanced data
modeling functions (Rob &&
Coronel, 2008).Need for Multi dimensional view, Online
Analytical Processing (OLAP) and reducing time
consuming for reports generating leads to the concept of
a data warehouse. By converting the operational
database to star schema structure data can be viewed as
multi dimensional view and can be used for Online
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13. Research Objective
The main objectives of this study are:
i. To identify the requirements of the
converting operational database to star
schema structure.
ii. To select the target operational database to
convert it data warehouse structure
iii. To develop tool for converting operational
database to data star schema structure
iv. To evaluate the developed tool.
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14. REFERENCES
 Chaudhuri S, Dayal U. (1997). An overview of data
warehousing and OLAP technology. ACM Sigmod
record, 26(1), 65-74.
 Surajit C, Umeshwar D. 2002. An Overview of Data
Warehousing and OLAP Technology, Microsoft
Research, Redmond.
 Panos V, Timos S. 2006. A Survey on Logical Models for
OLAP Databases. National Technical University of
Athens.
 Michael K,Yeol S.2007. The Translation of Star Schema
into Entity-Relationship Diagrams. College of
Information Science and Technology,Drexel
University, Philadelphia
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