MITP 5313 Current Trends of Database
Technology

ISSUE IN DATA WAREHOUSING
AND OLAP IN E-BUSINESS
Presented By Tamer J. Ab...
Outline
 Introduction
 What is a Data Warehousing

 Why need Data Warehousing
 What is OLAP
 Problem Statement
 Rese...
Introduction
 Decision Support Systems (DSS) are rapidly becoming

essential to achieving a competitive advantage for
bus...
What is a Data Warehousing?
 A single, complete

and consistent store
of data obtained from
a variety of different
source...
What is a Data Warehousing?
Information

A process of
transforming data into
information and making
it available to users ...
What is a Data Warehousing?
“A Data Warehouse is a
subject
oriented, integrated, n
onvolatile, and time
variant collection...
Why need Data Warehousing?
ESCALATING NEED FOR STRATEGIC INFORMATION

grew

complex

need different kinds of
information ...
What is OLAP ??


Online Analytical Processing, a category of software
tools that provides analysis of data stored in a d...
What is OLAP ??
 The chief component of OLAP is the OLAP server, which

sits between a client and a database management
s...
Problem Statement
The dramatically increase in
companies
transactions meet by increase in their database
transactions, dat...
Problem Statement Con.
which is not good for user who holds critical positions
such as top management, dissection maker an...
12
Research Objective
The main objectives of this study are:
i. To identify the requirements of the
converting operational da...
REFERENCES
 Chaudhuri S, Dayal U. (1997). An overview of data

warehousing and OLAP technology. ACM Sigmod
record, 26(1),...
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Issue in Data warehousing and OLAP in E-business

  1. 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 1
  2. 2. Outline  Introduction  What is a Data Warehousing  Why need Data Warehousing  What is OLAP  Problem Statement  Research Objective  REFERENCES 2
  3. 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). 3
  4. 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] 4
  5. 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 5
  6. 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] 6
  7. 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 7
  8. 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. 8
  9. 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. 9
  10. 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, 10
  11. 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 11
  12. 12. 12
  13. 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. 13
  14. 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 14
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