Business Intelligence Systems (Decision Support Systems)

Slides:



Advertisements
Similar presentations
Decision Support Systems: An Overview
Advertisements

Information and Decision Support Systems
KARAKTERISTIK DAN KEMAMPUAN DECISION SUPPORT SYSTEM Pertemuan-2 Mata Kuliah: CSM 211, Management Support System Tahun Akademik : 2012/2013 Target Pembelajaran.
Chapter 3: DECISION SUPPORT SYSTEMS: AN OVERVIEW
DECISION SUPPORT SYSTEMS AND BUSINESS INTELLIGENCE
1 Week 4 Decision Support System (DSS)/ Intelligent DSS.
Part 2: Decision Support Systems
Marakas: Decision Support Systems, 2nd Edition © 2003, Prentice-Hall Chapter Chapter 1: Introduction to Decision Support Systems Decision Support.
Chapter 3 DECISION SUPPORT SYSTEMS CONCEPTS, METHODOLOGIES, AND TECHNOLOGIES: AN OVERVIEW.
1 SEGMENT 2 Decision Support Systems: An Overview.
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 3-1 Chapter 3 Decision Support Systems:
12-1 Copyright © 2013 Pearson Canada Inc. Enhancing Decision Making Oleh : Kundang K Juman Enhancing Decision Making Oleh : Kundang K Juman CHAPTER TWELVE.
Chapter 3 Decision Support Systems: An Overview
CHAPTER 3 Decision Support Systems: An Overview. Decision Support Systems Decision Support Methodology Technology Components Development.
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 3-1 Chapter 3 Decision Support Systems:
Mgt 20600: IT Management & Applications Decision Support Systems Tuesday April 18, 2006.
The Academy of Public administration under the President of the Republic of Uzbekistan APPLICATION MODERN INFORMATION AND COMMUNICATION TECHNOLOGY IN DECISION.
Module 3: Business Information Systems
What is Business Intelligence? Business intelligence (BI) –Range of applications, practices, and technologies for the extraction, translation, integration,
Chapter 1 Database Systems. Good decisions require good information derived from raw facts Data is managed most efficiently when stored in a database.
Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization.
Enabling Organization-Decision Making
1.Knowledge management 2.Online analytical processing 3. 4.Supply chain management 5.Data mining Which of the following is not a major application.
Data Warehouse & Data Mining
1 - 1 Copyright © 2006, The McGraw-Hill Companies, Inc. All rights reserved.
MGS4020_02.ppt/Jan 22, 2013/Page 1 Georgia State University - Confidential MGS 4020 Business Intelligence Ch 1 – Introduction to DSS Jan 22, 2013.
Fundamentals of Information Systems, Third Edition2 Principles and Learning Objectives Good decision-making and problem-solving skills are the key to.
Week 1 Reference (chapter 1 in text book (1)) Dr. Fadi Fayez Jaber Updated By: Ola A.Younis Decision Support System.
© Farhan Mir 2007 IMS MIS Development BBA-IT (Hons) 6 th Semester ( Decision Support Systems & Knowledge Management Systems ) By: Farhan Mir.
Decision Support System Definition A Decision Support System is an interactive computer-based system or subsystem that helps people use computer communications,
 Dr. Chen and Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson 1 Jason C.H. Chen, Ph.D. Professor of MIS School of Business.
Fundamentals of Information Systems, Fifth Edition Chapter 6 Information and Decision Support Systems.
1 CHAPTER 3 Decision Support Systems: An Overview.
DSS Configurations It supports individual members and an entire team.
Chapter 3 DECISION SUPPORT SYSTEMS CONCEPTS, METHODOLOGIES, AND TECHNOLOGIES: AN OVERVIEW Study sub-sections: , 3.12(p )
Introduction – Addressing Business Challenges Microsoft® Business Intelligence Solutions.
5 - 1 Copyright © 2006, The McGraw-Hill Companies, Inc. All rights reserved.
 Every Information System aims at meting information needs of the users  DSS is different from other IS in that it does not provide any information directly,
Architecture of Decision Support System
IS312: information systems theory and applications LECTURE 3: levels of systems Information Systems Department.
CHAPTER 3: DECISION SUPPORT SYSTEMS: AN OVERVIEW Decision Support Systems and Intelligent Systems, 7th.
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 3-1 Chapter 3 Decision Support Systems:
Decision Support Systems: An Overview by Dr.S.Sridhar,Ph.D., RACI(Paris),RZFM(Germany),RMR(USA),RIEEEProc. web-site :
Foundations of Information Systems in Business. System ® System  A system is an interrelated set of business procedures used within one business unit.
Introduction Complex and large SW. SW crises Expensive HW. Custom SW. Batch execution Structured programming Product SW.
Learning Objectives Understand the concepts of Information systems.
Chapter 1 DECISION SUPPORT SYSTEMS AND BUSINESS INTELLIGENCE Skip subsections: 1.1, 1.2, 1.8, 1.10.
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang1-1 Turban, Aronson, and Liang Decision.
Decision Support and Business Intelligence Systems (9 th Ed., Prentice Hall) Chapter 3: Decision Support Systems Concepts, Methodologies, and Technologies:
Primary Decision Support Technologies Management Support Systems (MSS)
The Need for Data Analysis 2 Managers track daily transactions to evaluate how the business is performing Strategies should be developed to meet organizational.
Decision Support Systems
Decision Support and Business Intelligence Systems Chapter 1: Decision Support Systems and Business Intelligence.
DECISION SUPPORT SYSTEMS CONCEPTS, METHODOLOGIES, AND TECHNOLOGIES: AN OVERVIEW.
Decision Support and Business Intelligence Systems (9 th Ed., Prentice Hall) Chapter 3: Decision Support Systems Concepts, Methodologies, and Technologies:
Decision Support and Business Intelligence Systems (9 th Ed., Prentice Hall) Chapter 3: Decision Support Systems Concepts, Methodologies, and Technologies:
Database Principles: Fundamentals of Design, Implementation, and Management Chapter 1 The Database Approach.
Chapter 3 Decision Support Systems: An Overview
(Disarikan dari berbagai sumber)
Kapabilitas Struktur Klasifikasi
Decision Support and Business Intelligence Systems (9th Ed
Chattrakul Sombattheera
Chapter 1 Database Systems
Kapabilitas Struktur Klasifikasi
Information Systems Essentials, Fifth Edition Chapter 6 Information and Decision Support Systems.
Decision Support Systems: An Overview
Chapter 3 Decision Support Systems: An Overview
Presentation transcript:

Business Intelligence Systems (Decision Support Systems) Chapter 5 Business Intelligence Systems (Decision Support Systems)

Agenda Business Intelligence (BI) Types of data History of BI Evolution of BI Architecture of BI Benefits of BI Types of data Structured Semi-Structured Unstructured Decision Support Systems (DSS) Definition Characteristics and capabilities of DSS DSS Components

Business Intelligence (BI) BI is an umbrella term that combines architectures, tools, databases, analytical tools, applications, and methodologies BI's major objective is to enable easy access to data (and models) to provide business managers with the ability to conduct analysis BI helps transform data, to information (and knowledge), to decisions and finally to action

The Evolution of BI Capabilities

Components in a BI Architecture The data warehouse is a large repository of well-organized historical data Business analytics are the tools that allow transformation of data into information and knowledge Business performance management (BPM) allows monitoring, measuring, and comparing key performance indicators User interface (e.g., dashboards) allows access and easy manipulation of other BI components

A High-Level Architecture of BI

Faster, more accurate reporting Improved decision making The Benefits of BI The ability to provide accurate information when needed, including a real-time view of the corporate performance and its parts. Faster, more accurate reporting Improved decision making Improved customer service Increased revenue

The DSS–BI Connection (1) First, their architectures are very similar because BI evolved from DSS Second, DSS directly support specific decision making, while BI provides accurate and timely information, and indirectly support decision making Third, BI has an executive and strategy orientation, especially in its BPM and dashboard components, while DSS, in contrast, is oriented toward analysts

The DSS–BI Connection (2) Fourth, most BI systems are constructed with commercially available tools and components, while DSS is often built from scratch Fifth, DSS methodologies and even some tools were developed mostly in the academic world, while BI methodologies and tools were developed mostly by software companies Sixth, many of the tools that BI uses are also considered DSS tools (e.g., data mining and predictive analysis are core tools in both)

The DSS–BI Connection (3) Although some people equate DSS with BI, these systems are not, at present, the same Some people believe that DSS is a part of BI—one of its analytical tools Others think that BI is a special case of DSS that deals mostly with reporting, communication, and collaboration (a form of data-oriented DSS) BI is a result of a continuous revolution and, as such, DSS is one of BI's original elements Management Support Systems MSS = BI and/or DSS

What is Business Intelligence (BI)? Business intelligence is an umbrella term that refers to competencies, processes, technologies, applications and practices used to support evidence-based decision making in organizations. In the widest sense it can be defined as a collection of approaches for gathering, storing, analyzing and providing access to data that helps users to gain insights and make better fact-based business decisions.

What is BI used for? Analyzing customer behaviors, buying patterns and sales trends. Measuring, tracking and predicting sales and financial performance Budgeting and financial planning and forecasting Tracking the performance of marketing campaigns Optimizing processes and operational performance Improving delivery and supply chain effectiveness Web and e-commerce analytics Customer relationship management Risk analysis Strategic value driver analysis

The Basics of Business Intelligence 1 4 2 3

Gathering Data Collecting or accessing data that can be used to inform decision making. It can come in many formats and basically refers to the automated measurement and collection of performance data. Relevant data should be collected in the right way at the right time. Uncontrolled data can jeopardize the entire BI efforts that might follow.

Storing Data Data is filed and stored in appropriate ways to ensure it can be found and used for analysis and reporting. Data can be stored under different categories; also called data marts or data-warehouse access layers. Good data storage starts with the needs and requirements of the end users and a clear understanding of what they want to use the data for.

Analyzing Data Inspect, transform or model data in order to gain new insights that will support our business decision making. Data analysis comes in many different formats and approaches, both quantitative and qualitative. Analysis techniques includes the use of statistical tools, data mining approaches as well as visual analytics or even analysis of unstructured data such as text or pictures.

Providing Access Access to data is needed to perform analysis or to view the results of the analysis. Software tools allow end-users to perform data analysis Data are provided through reporting, dashboard (control panel) and scorecard (note, card, memo) applications.

Becoming an ‘Intelligent Company’ 1 5 2 3 4

Becoming an ‘Intelligent Company’ Step 1: More intelligent strategies – by identifying strategic priorities and agreeing your real information needs. Step 2: More intelligent data – by creating relevant and meaningful performance indicators as well as qualitative management information linked back to your strategic information needs. Step 3: More intelligent insights – by using good evidence to test and prove ideas and by analyzing the data to gain robust and reliable insights. Step 4: More intelligent communication – by creating informative and engaging management information packs and dashboards that provide the essential information, packaged in a way that is targeted and easy-to-understand. Step 5: More intelligent decision making – by fostering an evidence- based culture of turning information into actionable knowledge and real decisions.

Types of Data Structured Semi-Structured Unstructured Both inputs and outputs are clear Semi-Structured Either inputs or outputs are unclear Unstructured Both inputs and outputs are unclear

A Decision Support Framework (1)

A Decision Support Framework (2) Degree of Structuredness (Simon, 1977) Decisions are classified as Highly structured (a.k.a. programmed) Semi-structured Highly unstructured (i.e., non-programmed) Types of Control (Anthony, 1965) Strategic planning (top-level, long-range) Management control (tactical planning) Operational control

Simon’s Decision-Making Process

How Decisions Are Supported Artificial Neural Networks (ANN) Management Information Systems (MIS) Online Analytical Processing (OLAP) Expert Systems (ES) Enterprise Resource Planning (ERP) (ESS) Software Configuration Management (SCM) is the task of tracking and controlling changes in the software, part of the larger cross-discipline field of configuration management Customer Relationship Management (CRM) is a system for managing a company’s interactions with current and future customers. It often involves using technology to organize, automate and synchronize sales, marketing, customer service, and technical support. Knowledge Valuation System (KVS) Knowledge Managmement System (KMS)

Classical Definitions of DSS Interactive computer-based systems, which help decision makers utilize data and models to solve unstructured problems" - Gorry and Scott-Morton, 1971 It is a computer-based support system for management decision makers who deal with semi-structured problems - Keen and Scott-Morton, 1978

DSS as an Umbrella Term The term DSS can be used as an umbrella term to describe any computerized system that supports decision making in an organization E.g., an organization wide knowledge management system; a decision support system specific to an organizational function (marketing, finance, accounting, manufacturing, planning, SCM, etc.)

High-Level Architecture of a DSS

Decision Support Systems (1) Systems designed to support managerial decision-making in unstructured problems More recently, emphasis has shifted to inputs from outputs Mechanism for interaction between user and components Usually built to support solution or evaluate opportunities

Decision Support Systems (2) A DSS is a methodology that supports decision-making. It is: Flexible Adaptive Interactive GUI-based Iterative Employs modeling.

Key Characteristics and Capabilities of DSS

Characteristics and Capabilities of DSS (1) Provide support in semi-structured and unstructured situations, includes human judgment and computerized information Support for various managerial levels Support to individuals and groups Support to interdependent and/or sequential decisions Support all phases of the decision-making process Support a variety of decision-making processes and styles (more)

Characteristics and Capabilities of DSS (2) Are adaptive Have user friendly interfaces Goal: improve effectiveness of decision making The decision maker controls the decision-making process End-users can build simple systems Utilizes models for analysis Provides access to a variety of data sources, formats, and types Decision makers can make better, more consistent decisions in a timely manner

Components of DSS Subsystems: Data management Managed by DBMS Model management User interface Knowledge Management and organizational knowledge base

Data Management Subsystem Components: Database Database management system Data directory Query facility

Database Interrelated data extracted from various sources, stored for use by the organization, and queried Internal data, usually from TPS External data from government agencies, trade associations, market research firms, forecasting firms Private data or guidelines used by decision-makers

Database Management System Extracts data Manages data and their relationships Updates (add, delete, edit, change) Retrieves data (accesses it) Queries and manipulates data Employs data dictionary

What are the major functions (capabilities) of DBMS? Storage, retrieval, and control are the three basic functions. The DBMS manages the database: organize, extract/access, modify, delete, and catalogue data.

Data Directory Catalog of all data Contains data definitions Answers questions about the availability of data items Source Allows for additions, removals, and alterations

Data Directory Extraction: is to capture data from several sources, filter them, summarize, condense, and reorganize the data.  The function of a query facility is to provide the basis for access to data. Accepts requests, checks for feasibility, provides answers. The function of a directory is a catalog of all data in the database. It includes data definitions.

Model Management Subsystem Components: Model base Model base management system Modeling language Model execution, integration, and command processor

Models Strategic models Support top management's strategic planning. For example, examination of acquisitions, diversifications, and mergers. Tactical models Support mainly middle management in resource allocation and in control. For example, make or buy decisions or devising a major promotion plan.

Types of Models Operational Supports daily activities Analytical Used to perform analysis of data

Model Base Management System Functions: Model creation Model updates Model data manipulation Model directory: Catalog of models Definitions

Model Management Activities Model execution Controls running of model Model command processor Receives model instructions from user interface Routes instructions to MBMS or module execution or integration functions Model integration Combines several models’ operations

User Interface System Knowledge-based system Data management and DBMS Model management and MBMS User Interface Management System (UIMS) Natural Language Processor Input Action Languages Output Display Language Users Printers, Plotters PC Display

User Interface Management System GUI Natural language processor Interacts with model management and data management subsystems Examples Speech recognition Display panel

User Interface Management System A user interface covers all aspects of the communications between a user and the MSS. Most of the power, flexibility, and ease-of-use characteristic of MSS are derived from this component. It is the part of the system that the user sees, to him/her, it is the system.

Knowledge-Based Management System Expert or intelligent agent system component Complex problem solving Enhances operations of other components

DSS Hardware De facto standard Web server with DBMS: Operates using browser Data stored in variety of databases Can be mainframe, server, workstation, or PC Any network type Access for mobile devices

Holsapple and Whinston DSS Classifications Alter Extent to which outputs can directly support or determine the decision Data oriented or model oriented Holsapple and Whinston Text oriented, database oriented, spreadsheet oriented, solver oriented, rule oriented, or compound

DSS Classifications Intelligent Descriptive Procedural Reasoning Linguistic Expert-system based Adaptive Hackathorn and Keen Personal support, group support, or organizational support

Custom made vs. vendor ready made DSS Classifications GSS v. Individual DSS Decisions made by entire group or by alone decision maker Custom made vs. vendor ready made Generic DSS may be modified for use Database, models, interface, support are built in Addresses repeatable industry problems Reduces costs

List the major components of DSS and briefly define each of them. DSS Components List the major components of DSS and briefly define each of them. The major components are: Data management; includes a database and its management system. Model management; includes models and their management system. Knowledge base; includes artificial intelligence enhancements to the other components. The user; he or she is the decision maker.

DSS Users (1) List and describe the major classes of DSS users. The major classes of DSS users are: Management (user, decision-maker) - looking for more user-friendly systems that can do more general analysis and aid in decision making. Staff (intermediaries) - are looking for more detailed- oriented system and are willing to use more complex system. Staff acts as intermediary between MSS and manager. Different intermediaries: Staff assistants have specialized knowledge about management problems and some experience with the decision support technology.

DSS Users (2) An expert tool user is skilled in the application of one or more types of specialized problem- solving tools. The expert tool user performs the tasks the problem solver does not have the technical skills to do. Business (system) analysts have a general knowledge of the application area, a formal business administration education, and considerable skill in DSS construction tools. Facilitator in GSS controls and coordinates the software of group DSS.

What types of support are provided by DSS? DSS provides: DSS Support What types of support are provided by DSS? DSS provides: Support in semistructured and unstructured situations Support by bringing human judgment and computerized information together. Support for various managerial levels, ranging from top executives to line managers.

DSS Support Support to individuals as well as groups, since less structured problems sometimes require several individuals from different departments and organizational levels. Support to several interdependent and or sequential decisions. Support in all phases of the decision-making process: intelligence, design, choice, and implementation.