DECISION SUPPORT SYSTEM ARCHITECTURE: The data management component.

Slides:



Advertisements
Similar presentations
Chapter 13 The Data Warehouse
Advertisements

By: Mr Hashem Alaidaros MIS 211 Lecture 4 Title: Data Base Management System.
Chapter 9 DATA WAREHOUSING Transparencies © Pearson Education Limited 1995, 2005.
Chapter 3 Database Management
Database Management: Getting Data Together Chapter 14.
DATA WAREHOUSING.
L The Difference Between Logical and Physical Views of Information l Databases and Database Management Systems l How You Can Develop Database Applications.
Data Mining and Data Warehousing – a connected view.
1 SEGMENT 2 Decision Support Systems: An Overview.
1 Data and Knowledge Management. 2 Data Management: A Critical Success Factor The difficulties and the process Data sources and collection Data quality.
1 © Prentice Hall, 2002 Chapter 11: Data Warehousing.
Business Intelligence: Essential of Business
DASHBOARDS Dashboard provides the managers with exactly the information they need in the correct format at the correct time. BI systems are the foundation.
Designing a Data Warehouse
Lecture-8/ T. Nouf Almujally
Copyright © 2014 Pearson Education, Inc. 1 It's what you learn after you know it all that counts. John Wooden Key Terms and Review (Chapter 6) Enhancing.
M ODULE 5 Metadata, Tools, and Data Warehousing Section 4 Data Warehouse Administration 1 ITEC 450.
XP Information Information is everywhere in an organization Employees must be able to obtain and analyze the many different levels, formats, and granularities.
Operational Data Tools Chapter Eight. Copyright © Houghton Mifflin Company. All rights reserved.8–28–2 Chapter Eight Learning Objectives To learn database.
1 Chapter 4 Data Management: Warehousing, Access and Visualization MSS foundation New concepts Object-oriented databases Intelligent databases Data warehouse.
Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization.
CSI315CSI315 Web Development Technologies Continued.
5.1 © 2007 by Prentice Hall 5 Chapter Foundations of Business Intelligence: Databases and Information Management.
Intro to MIS – MGS351 Databases and Data Warehouses Chapter 3.
Data Management Turban, Aronson, and Liang Decision Support Systems and Intelligent Systems, Seventh Edition.
Ihr Logo Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization Turban, Aronson, and Liang.
Copyright © 2003 by Prentice Hall Computers: Tools for an Information Age Chapter 13 Database Management Systems: Getting Data Together.
Chapter 6: Foundations of Business Intelligence - Databases and Information Management Dr. Andrew P. Ciganek, Ph.D.
Management Information Systems By Effy Oz & Andy Jones
Decision Support System Definition A Decision Support System is an interactive computer-based system or subsystem that helps people use computer communications,
Business Intelligence Zamaneh Jahed. What is Business Intelligence? Business Intelligence (BI) is a broad category of applications and technologies for.
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 5-1 Chapter 5 Business Intelligence: Data.
© 2007 by Prentice Hall 1 Introduction to databases.
1 Data Warehouses BUAD/American University Data Warehouses.
5-1 McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved.
Ihr Logo Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization Turban, Aronson, and Liang.
5 - 1 Copyright © 2006, The McGraw-Hill Companies, Inc. All rights reserved.
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?
6.1 © 2010 by Prentice Hall 6 Chapter Foundations of Business Intelligence: Databases and Information Management.
MANAGING DATA RESOURCES ~ pertemuan 7 ~ Oleh: Ir. Abdul Hayat, MTI.
1 Categories of data Operational and very short-term decision making data Current, short-term decision making, related to financial transactions, detailed.
Data resource management
Chapter 5: Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization DECISION SUPPORT SYSTEMS AND BUSINESS.
Next Back MAP 3-1 Management Information Systems for the Information Age Copyright 2002 The McGraw-Hill Companies, Inc. All rights reserved Chapter 3 Data.
Architecture of Decision Support System
DATABASES AND DATA WAREHOUSES
Chapter 3 Databases and Data Warehouses: Building Business Intelligence Copyright © 2010 by the McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin.
Organizing Data and Information
DATA RESOURCE MANAGEMENT
CHAPTER 4 Data Warehousing, Access, Analysis, Mining, and Visualization 2 1.
Foundations of Business Intelligence: Databases and Information Management.
Chapter 10 Database Management. Data and Information How are data and information related? p Fig Next processing data stored on disk Step.
Distributed Data Analysis & Dissemination System (D-DADS ) Special Interest Group on Data Integration June 2000.
CHAPTER 5 Data and Knowledge Management. CHAPTER OUTLINE 5.1 Managing Data 5.2 The Database Approach 5.3 Database Management Systems 5.4 Data Warehouses.
Data Resource Management Agenda What types of data are stored by organizations? How are different types of data stored? What are the potential problems.
Business intelligence systems. Data warehousing. An orderly and accessible repositery of known facts and related data used as a basis for making better.
Primary Decision Support Technologies Management Support Systems (MSS)
1 Copyright © Oracle Corporation, All rights reserved. Business Intelligence and Data Warehousing.
Decision Support Systems
MBA/1092/10 MBA/1093/10 MBA/1095/10 MBA/1114/10 MBA/1115/10.
Database Concepts and Applications in HRIS
1 Data Warehousing Data Warehousing. 2 Objectives Definition of terms Definition of terms Reasons for information gap between information needs and availability.
1 Chapter 1 Introduction to Accounting Information Systems Chapter 2 Intelligent Systems and Knowledge Management.
Introduction to Business Analytics
Intro to MIS – MGS351 Databases and Data Warehouses
Data Warehouse.
MANAGING DATA RESOURCES
Chapter 1 Database Systems
The Database Environment
Presentation transcript:

DECISION SUPPORT SYSTEM ARCHITECTURE: The data management component

Data Collection SOURCE: Primary / Secondary or External / Internal / Personal TYPE: ‘Hard’ / ‘Soft’ LEVEL: Strategic / Tactical / Operational What are the problems with data collection? What gives information quality?  ACCURACY  TIMELINESS  RELIABILITY  RELEVANCE  COMPLETENESS  CURRENCY  INTERPRETABILITY  PRESENTATION  ACCESSIBILITY

The Data Management sub system of a DSS  Extracts information from internal company databases (specialised integrated database or data warehouse)  Has links to external data sources (Web access)  Interfaces with modelling capabilities, user interface design.  May have a knowledge component (AI capabilities)

Database Management Systems  A DBMS enables greater integration of data, complex file structure, user query facilities. e.g. The university’s DBMS is Oracle. The query facility is through the language SQL  The main type of DSS database organisation is relational.

Data Warehouses  The combination of many data sources into one store, specifically for end user access. This store is separate from the organisation’s records of operations (transaction processing system files) but partly derived from them.  Appropriate in large organisations with different systems which may store the same data for different needs and in different formats.  Data warehousing provides a means for integrating the data from the various systems.  Useful for static (usually historical) data

Data Mining a.k.a. data exploration or data pattern processing  The need for tools to help with data access is due to the complexity and size of many organisation’s databases (data warehouses)  The query can be conducted quickly, and the miner does not need programming skills to explore the database (end user support)  A focus on discovery vs verification  On line Analytical Processing – multidimensional databases  Problems with data warehouses/ data mining may be Data Noise, Missing information, Security, Reliability

Data Visualisation Incorporates any technology that allows the user to picture the information in a more meaningful way.  GUI (windows and icons applications  graphical facilities  GIS (geographical information systems)  3D presentations/ animation

Continuing Research and Development Progress over time……………………. DATA INFORMATIONKNOWLEDGE sources sourcessources tables/ lists documentsexpertise, experience facts/ figures concepts, opinions, best practice cases verbal reportsshared practice “hard data” “soft data” intelligence

Continuing Research…..  Intelligent component Intelligent agents (‘detect and alert’ capabilities) on the Internet Case based reasoning and neural networks (pattern recognition capabilities)  Web integrated database systems