Data Warehousing Alex Ostrovsky CS157B Spring 2007.

Slides:

Advertisements

Similar presentations

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

Advertisements

Database Management3-1 L3 Database Management Santa R. Susarapu Ph.D. Student Virginia Commonwealth University.

Data Warehousing Willem Visser RW334. Somebody is watching! Everybody seems to be recording your every move Loyalty cards Cookies – Facebook, Twitter,…

Data Warehouse Architecture Sakthi Angappamudali Data Architect, The Oregon State University, Corvallis 16 th May, 2005.

Database – Part 3 Dr. V.T. Raja Oregon State University External References/Sources: Data Warehousing – Mr. Sakthi Angappamudali.

ICS 421 Spring 2010 Data Warehousing (1) Asst. Prof. Lipyeow Lim Information & Computer Science Department University of Hawaii at Manoa 3/18/20101Lipyeow.

Data Warehouse IMS5024 – presented by Eder Tsang.

1 Data Warehousing. 2 Data Warehouse A data warehouse is a huge database that stores historical data Example: Store information about all sales of products.

Overview of Databases and Transaction Processing Chapter 1.

Chapter 3 Database Management

Introduction to Data Warehousing. From DBMS to Decision Support DBMSs widely used to maintain transactional data Attempts to use of these data for analysis,

Distributed DBMSs A distributed database is a single logical database that is physically distributed to computers on a network. Homogeneous DDBMS has the.

Database – Part 2b Dr. V.T. Raja Oregon State University External References/Sources: Data Warehousing – Sakthi Angappamudali at Standard Insurance; BI.

Chapter 14 Organizing and Manipulating the Data in Databases

Data Mining and Data Warehousing – a connected view.

Database – Part 2 Dr. V.T. Raja Oregon State University.

Chapter 13 The Data Warehouse

1 © Prentice Hall, 2002 Chapter 11: Data Warehousing.

Data Warehousing DSCI 4103 Dr. Mennecke Introduction and Chapter 1.

Patrick Seto CS157A Section 3 Data Warehouses Presented by Patrick Seto CS157A Section 3.

Chapter 13 – Data Warehousing. Databases  Databases are developed on the IDEA that DATA is one of the critical materials of the Information Age  Information,

Defining Data Warehouse Concepts and Terminology.

XP Information Information is everywhere in an organization Employees must be able to obtain and analyze the many different levels, formats, and granularities.

Data Conversion to a Data warehouse Presented By Sanjay Gunasekaran.

Understanding Data Warehousing

1 Brett Hanes 30 March 2007 Data Warehousing & Business Intelligence 30 March 2007 Brett Hanes.

Database Systems – Data Warehousing

Ihr Logo Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization Turban, Aronson, and Liang.

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.

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 5-1 Chapter 5 Business Intelligence: Data.

I Information Systems Technology Ross Malaga 4 "Part I Understanding Information Systems Technology" Copyright © 2005 Prentice Hall, Inc. 4-1 DATABASE.

Data warehousing and online analytical processing- Ref Chap 4) By Asst Prof. Muhammad Amir Alam.

1 Data Warehouses BUAD/American University Data Warehouses.

OLAP & DSS SUPPORT IN DATA WAREHOUSE By - Pooja Sinha Kaushalya Bakde.

Copyright © 2015 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of McGraw-Hill Education.

The Data Warehouse “A data warehouse is a subject-oriented, integrated, time-variant, and nonvolatile collection of “all” an organisation’s data in support.

Module 1: Introduction to Data Warehousing and OLAP

1 Reviewing Data Warehouse Basics. Lessons 1.Reviewing Data Warehouse Basics 2.Defining the Business and Logical Models 3.Creating the Dimensional Model.

MIS2502: Data Analytics The Information Architecture of an Organization.

Operational vs. Informational System. Operational System Operational systems maintain records of daily business transactions whereas a Data Warehouse.

1 Topics about Data Warehouses What is a data warehouse? How does a data warehouse differ from a transaction processing database? What are the characteristics.

Building Data and Document-Driven Decision Support Systems How do managers access and use large databases of historical and external facts?

Decision Support and Date Warehouse Jingyi Lu. Outline Decision Support System OLAP vs. OLTP What is Date Warehouse? Dimensional Modeling Extract, Transform,

6.1 © 2010 by Prentice Hall 6 Chapter Foundations of Business Intelligence: Databases and Information Management.

13 1 Chapter 13 The Data Warehouse Database Systems: Design, Implementation, and Management, Seventh Edition, Rob and Coronel.

Ch3 Data Warehouse Dr. Bernard Chen Ph.D. University of Central Arkansas Fall 2009.

Chapter 5 DATA WAREHOUSING Study Sections 5.2, 5.3, 5.5, Pages: & Snowflake schema.

The Data Warehouse “A data warehouse is a subject-oriented, integrated, time-variant, and nonvolatile collection of “all” an organisation’s data in support.

Foundations of Business Intelligence: Databases and Information Management.

Chapter 1 Overview of Databases and Transactions.

Business Intelligence Transparencies 1. ©Pearson Education 2009 Objectives What business intelligence (BI) represents. The technologies associated with.

© 2003 Prentice Hall, Inc.3-1 Chapter 3 Database Management Information Systems Today Leonard Jessup and Joseph Valacich.

Copyright© 2014, Sira Yongchareon Department of Computing, Faculty of Creative Industries and Business Lecturer : Dr. Sira Yongchareon ISCG 6425 Data Warehousing.

Data Resource Management Agenda What types of data are stored by organizations? How are different types of data stored? What are the potential problems.

Acct 6910 Building Business Intelligence Systems An Introduction to Data Warehouse.

Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke1 Data Warehousing and Decision Support Chapter 25.

Copyright © 2016 Pearson Education, Inc. Modern Database Management 12 th Edition Jeff Hoffer, Ramesh Venkataraman, Heikki Topi CHAPTER 9: DATA WAREHOUSING.

BUSINESS INTELLIGENCE. The new technology for understanding the past & predicting the future … BI is broad category of technologies that allows for gathering,

Business Intelligence Overview

Jaclyn Hansberry MIS2502: Data Analytics The Things You Can Do With Data The Information Architecture of an Organization Jaclyn.

Intro to MIS – MGS351 Databases and Data Warehouses

Basic Concepts in Data Management

Overview of Databases and Transaction Processing

An Introduction to Data Warehousing

MIS2502: Data Analytics The Information Architecture of an Organization Acknowledgement: David Schuff.

CHAPTER SIX OVERVIEW SECTION 6.1 – DATABASE FUNDAMENTALS

MIS2502: Data Analytics The Information Architecture of an Organization Aaron Zhi Cheng Acknowledgement:

Data Warehousing Concepts

Presentation transcript:

Data Warehousing Alex Ostrovsky CS157B Spring 2007

Introduction ► Data warehouse is a main repository of corporate data ► Multiple databases are employed per specific purpose ► Contains raw events and unprocessed data, although separate tables might exist for processed information displaying meaningful data

What is it used for? ► Data analysis ► Data mining ► Complex queries with multiple table join ► Forecasting ► Historical reporting ► OLAP (Online Analytical Processing)

High level view

Key Concepts and Features ► Data is not required to be heavily normalized ► Transaction Processing is done mostly offline, thus processing time is not very critical. Although, this might depend on amount of data, normalization, query complexity, and application specifications.

Key Concepts and Features (cont.) ► Unlike regular OLTP real-time databases data is subject-oriented ► Non-volatile, i.e. data is essentially stored forever without being pruned or deleted. ► Heavily integrated: contains data from majority of organization’s applications ► Time-variant: most of the data has some time reference for the purpose of producing the reports

Types of data warehousing DBs ► Offline operational database: similar to regular data replication. Used to minimize the impact of queries on a running primary operational system ► Offline data warehouse: heavily integrated, reporting-oriented warehouse databases which are updated with data from operational databases on regular time intervals

Types of data warehousing DBs (cont) ► Real-time data warehouse: database data is updated instantaneously as soon as transaction happens ► Integrated data warehouse: database is integrated with primary operational system for immediate decision making and reporting.

Benefits of Data Warehousing ► No need to stress operational database with complex queries ► Separation of processing and business logic ► Very flexible, multiple distinct relations can be defined from a set of data ► Can be customer or object specific ► Persistent – once result is computed from the raw events, it doesn’t need to be recomputed again, giving faster response time on subsequent queries.

Dangers of Data Warehousing ► Heavy processing requires physically separate database machines for warehousing and OLTP ► Must be optimized for novice users, complex queries might take a very long time ► Much more complex multidimensional design compared to regular relational databases ► Errors in computational logic can cause serious financial losses and computational recalculations. ► Data representation ► Relatively difficult to perform data migration

Database Design ► Data warehousing databases mostly utilize complex multidimensional design ► Relationships must be meaningful and represent clear patterns and trends of unprocessed data. More data and relationships you have more dimensions database will have. ► Information is viewed along one common dimensional position. Can be thought of as intersection of a few planes.

OLAP Market

References ► ► ► ata_Warehousing/ ata_Warehousing/ ata_Warehousing/ ► ata_Warehousing/Articles/ ata_Warehousing/Articles/ ata_Warehousing/Articles/ ► base base base ►