ITEC423 DATA WAREHOUSING INTRODUCTION TO THE COURSE Asst. Prof. Dr. Nazife Dimililer Spring 2010-2011.

Slides:



Advertisements
Similar presentations
An overview of Data Warehousing and OLAP Technology Presented By Manish Desai.
Advertisements

Chapter 1 Business Driven Technology
BY LECTURER/ AISHA DAWOOD DW Lab # 2. LAB EXERCISE #1 Oracle Data Warehousing Goal: Develop an application to implement defining subject area, design.
By: Mr Hashem Alaidaros MIS 211 Lecture 4 Title: Data Base Management System.
Data Warehouse Architecture Sakthi Angappamudali Data Architect, The Oregon State University, Corvallis 16 th May, 2005.
ICS 421 Spring 2010 Data Warehousing (1) Asst. Prof. Lipyeow Lim Information & Computer Science Department University of Hawaii at Manoa 3/18/20101Lipyeow.
Chapter 3 Database Management
Business Intelligence in Detail What is a Data Warehouse?
Data Sources Data Warehouse Analysis Results Data visualisation Analytical tools OLAP Data Mining Overview of Business Intelligence Data visualisation.
Data Warehousing ISYS 650. What is a data warehouse? A data warehouse is a subject-oriented, integrated, nonvolatile, time-variant collection of data.
DATA WAREHOUSE (Muscat, Oman).
Data Warehousing: Defined and Its Applications Pete Johnson April 2002.
Basic Concepts of Datawarehousing An Overview Prasanth Gurram.
What is Business Intelligence? Business intelligence (BI) –Range of applications, practices, and technologies for the extraction, translation, integration,
C A S E S T U D I E S—S T R A T E G I E S F O R S U C C E S S November 7 - 9, 2002.
Efficient BI Solution Presented by: Leo Khaskin, PowerCubes Lab Value of Information as Business Asset.
OLAP Theory-English version On-Line Analytical processing (Buisness Intelligence) [Ing.Skorkovský,CSc] KPH_ESF_MU.
Database Systems – Data Warehousing
GBA IT Project Management Final Project – “ FoodMart Corp - Making use of Business Intelligence” July 12, 2004 N.Khuda.
Data Warehouse Concepts Transparencies
Chapter 6: Foundations of Business Intelligence - Databases and Information Management Dr. Andrew P. Ciganek, Ph.D.
DW-1: Introduction to Data Warehousing. Overview What is Database What Is Data Warehousing Data Marts and Data Warehouses The Data Warehousing Process.
Data Warehouse Overview September 28, 2012 presented by Terry Bilskie.
OLAP Theory-English version On-Line Analytical processing (Business Intelligence) [Ing.J.Skorkovský,CSc.] Department of corporate economy.
Business Intelligence Zamaneh Jahed. What is Business Intelligence? Business Intelligence (BI) is a broad category of applications and technologies for.
Data warehousing and online analytical processing- Ref Chap 4) By Asst Prof. Muhammad Amir Alam.
Chapter 1 Business Driven Technology MANGT 366 Information Technology for Business Chapter 1: Management Information Systems: Business Driven MIS.
OLAP & DSS SUPPORT IN DATA WAREHOUSE By - Pooja Sinha Kaushalya Bakde.
1 Reviewing Data Warehouse Basics. Lessons 1.Reviewing Data Warehouse Basics 2.Defining the Business and Logical Models 3.Creating the Dimensional Model.
5-1 McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved.
Introduction – Addressing Business Challenges Microsoft® Business Intelligence Solutions.
1 Categories of data Operational and very short-term decision making data Current, short-term decision making, related to financial transactions, detailed.
CISB594 – Business Intelligence
ITEC423 DATA WAREHOUSING INTRODUCTION TO THE COURSE Asst. Prof. Dr. Nazife Dimililer Spring
Decision Support and Date Warehouse Jingyi Lu. Outline Decision Support System OLAP vs. OLTP What is Date Warehouse? Dimensional Modeling Extract, Transform,
1 Categories of data Operational and very short-term decision making data Current, short-term decision making, related to financial transactions, detailed.
CISB594 – Business Intelligence Data Warehousing Part I.
Concepts in Enterprise Resource Planning Fourth Edition
CISB113 Fundamentals of Information Systems Types of IS in Organization.
Chapter 5 DATA WAREHOUSING Study Sections 5.2, 5.3, 5.5, Pages: & Snowflake schema.
CISB594 – Business Intelligence Data Warehousing Part I.
Business Intelligence Transparencies 1. ©Pearson Education 2009 Objectives What business intelligence (BI) represents. The technologies associated with.
Pooja Sharma Shanti Ragathi Vaishnavi Kasala. BUSINESS BACKGROUND Lowe's started as a single hardware store in North Carolina in 1946 and since then has.
CISB594 – Business Intelligence Data Warehousing Part I.
Why BI….? Most companies collect a large amount of data from their business operations. To keep track of that information, a business and would need to.
1 Categories of data Operational and very short-term decision making data Current, short-term decision making, related to financial transactions, detailed.
Copyright© 2014, Sira Yongchareon Department of Computing, Faculty of Creative Industries and Business Lecturer : Dr. Sira Yongchareon ISCG 6425 Data Warehousing.
Oracle 8i Data Warehousing (chapter 1, 2) Data Warehousing Lab. 석사 1 학기 HyunSuk Jung.
1 Copyright © Oracle Corporation, All rights reserved. Business Intelligence and Data Warehousing.
The Need for Data Analysis 2 Managers track daily transactions to evaluate how the business is performing Strategies should be developed to meet organizational.
1 Management Information Systems M Agung Ali Fikri, SE. MM.
Chapter 8: Data Warehousing. Data Warehouse Defined A physical repository where relational data are specially organized to provide enterprise- wide, cleansed.
Business Intelligence and Decision Support Systems (9 th Ed., Prentice Hall) Chapter 5: Data Warehousing.
Data Warehouse Data Mart Elahe Soroush. Agenda  Data Warehouse definition  Concepts  Logical transformation  Physical transformation  DW components.
Data Warehouse – Your Key to Success. Data Warehouse A data warehouse is a  subject-oriented  Integrated  Time-variant  Non-volatile  Restructure.
Business Intelligence and Decision Support Systems (9 th Ed., Prentice Hall) Chapter 8: Data Warehousing.
2 Copyright © 2006, Oracle. All rights reserved. Defining Data Warehouse Concepts and Terminology.
BUSINESS INTELLIGENCE. The new technology for understanding the past & predicting the future … BI is broad category of technologies that allows for gathering,
Cognos BI. What is Cognos? Cognos (Cognos Incorporated) was an Ottawa, Ontario-based company that makes Business Intelligence (BI) and Performance Management.
Chapter 3 Building Business Intelligence Chapter 3 DATABASES AND DATA WAREHOUSES Building Business Intelligence 6/22/2016 1Management Information Systems.
OLAP Theory-English version On-Line Analytical processing (Buisness Intelligence) Ing.Skorkovský,CSc Department of Corporate Economy Faculty of Economics.
Data Mining and Data Warehousing: Concepts and Techniques What is a Data Warehouse? Data Warehouse vs. other systems, OLTP vs. OLAP Conceptual Modeling.
Business Intelligence Overview
Advanced Applied IT for Business 2
Data warehouse and OLAP
Data Warehouse.
Data Warehousing Concepts
Data Warehouse and OLAP Technology
Data Warehousing & DATA MINING (SE-409) Lecture-1 Introduction and Background Huma Ayub Software Engineering department University of Engineering and Technology,
Presentation transcript:

ITEC423 DATA WAREHOUSING INTRODUCTION TO THE COURSE Asst. Prof. Dr. Nazife Dimililer Spring

Information  Class : CTL002  Schedule  Tuesday 12:30-14:20  Thursday 12:30-14:20  Office : CT 206  Phone :   Books  Ponniah P., Data Warehousing Fundamentals for IT Professionals, John Wiley & Sons, 2010  MS SQL server Analysis services

Assesment  Attendance  Attendance is mandatory. Missing more than 60% of classes disqualifies you from make ups  Grading  4xQuizzes : 20%  Midterm :30%  Final : 45%  Lab performance (Attendance??) 5%  Optional Work upto 5-10%  Project  Research  Design Homework

Objectives and Learning Outcomes of the course  Objectives  Provide a solid background in data warehousing  Show the differences between databases and data warehousing  Define the process of designing a data warehouse  Design and implement a data warehouse  Learning outcomes  Describe the differences between OLTP systems and data warehouses.  Describe the need for data warehousing  Analyze and transform business requirements into a dimensional model in order to build a data warehouse  Transform the dimensional model into a physical data design  Implement a high quality data warehouse or data mart  Understand multidimensional query concepts

Schedule Class/Week TopicReading 1IntroductionChapter 1 2Building blocks of a data warehouseChapter 2 3Trends in Data warehousingChapter 3 4Planning and Project ManagementChapter 4 5Defining Business RequirementsChapters 5 & 6 6Architectural ComponentsChapters 7 & 8 7Role of MetadataChapter 9 8Dimensional ModelingChapters 10 & 11 9Data extraction, transformation and loadingChapter 12 10OLAP in Data WarehouseChapter 15 11Data mining BasicsChapter 17 12Physical Design ProcessChapter 18 13Deployment and MaintenanceChapters 19 & 20

Learning Procedures  Lectures  Power point slides  Discussions  Applications  Step-by-step tutorials  Case studies  Homework/Project  Problems  Research/Homework

Operational Databases (OLTP Systems)  Every company uses a number of operational databases to store daily transactions  All activities are recorded  Performed by users  Stored in databases  Operational databases are designed and optimized for insert/delete/update  Majority of transactions involve single records

Operational Databases (OLTP Systems) Market Sales Accounting Accounting Software Market Sales Software Estate Sales Estate Agency Software abcd dfsfhdataabcd dfsfhdataabcd dfsfhdata

What is Business Information?  Information contained in the operational databases and external resources of a company  Utilized for gaining insights that drive strategic and tactical business decisions  Help make decisions faster  Encompasses a broad category of technologies  gather, store, access, and analyze data

What is Business Intelligence?  computer-based techniques used in spotting, digging-out, and analyzing business data, such as sales revenue by products and/or departments, or by associated costs and incomes  broad category of applications and technologies for gathering, storing, analyzing, and providing access to data to help clients make better business decisions.

What is business Intelligence?  environment in which business users receive information that is reliable, secure, consistent, understandable, easily manipulated and timely  enable business users to conduct analyses that yield an overall understanding of where the business has been, where it is now, and where it will be in the near future.  empowers knowledge workers to make more informed, smarter business decisions faster

Key concepts in Business Intelligence  Management makes decisions  Requires information from various/diverse sources  Information should be in required format  Past data is important  Results should be produced immediately  Managers should be able pose ad-hoc queries

Business Intelligence Accounti ng Accounting Software Estate Sales Estate Agency Software Market Sales Market Sales Software Query Business Intelligence Query I need the number of dairy products sold by each branch per month for the last 10 years! I need these NOW!!! Is there a correlation between apt sales and dairy product sales? Prepare a graph showing amount of dairy products and number of apts sold in each month for the last 5 years.

Accou nting Accountin g Software Estate Sales Estate Agency Software Market Sales Market Sales Software Business Intelligence product company category price branch employee Extract Transform Load All market sales All property sales All bills Contains historical data as well

STAR SCHEMA

What Can a Data Warehouse Do? Some of the benefits of a DW are:  Immediate information delivery to management  Data integration from across and even outside the organization  Future vision from historical trends  Tools for looking at data in new ways  Freedom from IS department resource limitations

Example of Data Warehouse Applications-I Sales Analysis  Determine real-time product sales to make vital pricing and distribution decisions.  Analyze historical product sales to determine success or failure attributes.  Evaluate successful products and determine key success factors.  Use corporate data to understand the margin as well as the revenue implications of a decision.  Rapidly identify a preferred customer segments based on revenue and margin.  Quickly isolate past preferred customers who no longer buy.  Identify daily what product is in the manufacturing and distribution pipeline.  Instantly determine which salespeople are performing, on both a revenue and margin basis, and which are behind.

Example of Data Warehouse Applications-II Financial Analysis  Compare actual to budgets on an annual, monthly and month-to-date basis.  Review past cash flow trends and forecast future needs.  Identify and analyze key expense generators.  Instantly generate a current set of key financial ratios and indicators.  Receive near-real-time, interactive financial statements.

Example of Data Warehouse Applications-III Human Resource Analysis  Evaluate trends in benefit program use.  Identify the wage and benefits costs to determine company- wide variation.  Review compliance levels for EEOC and other regulated activities. Other Areas  Warehouses have also been applied to areas such as:  Logistics  Inventory  Purchasing  detailed transaction analysis  load balancing  …

What is Data Warehouse?

central repository A data warehouse is a central repository for all or significant parts of the data that an enterprise's various business systems collect. diverse Data warehousing emphasizes the capture of data from diverse sources for useful analysis and access Data warehouse helps get information to answer questions. It is not meant for direct data entry; batch updates are the norm for refreshing warehouses. subset of a data warehouse Data mart is a subset of a data warehouse based on a specific department, function or subject Applications of data warehouses include data mining, Web Mining, and decision support systems (DSS), Business Intelligence (BI).

What is a data warehouse? “A data warehouse is a  subject-oriented,  Integrated (consolidated)  time-variant, and  nonvolatile collection of data in support of management’s decision- making process.” W. H. Inmon

End of Lecture 1