CHAPTER 9

ENABLING THE ORGANIZATION (DECISION MAKING)

DECISION MAKING

• Reasons for the growth of decision-making information systems

          ➽ People need to analyze large amounts of information

          ➽ People must make decisions quickly

          ➽People must apply sophisticated analysis techniques, such as modeling and forecasting, to                    make good decisions

          ➽ People must protect the corporate asset of organizational information

• Model - a simplified representation or abstraction of reality
• IT systems in an enterprise

TRANSACTION PROCESSING SYSTEMS

• Moving up through the organizational pyramid users move from requiring transactional  information to analytical information

• Transaction processing system - the basic business system that serves the operational level (analyst) in an organization
• Online transaction processing (OLTP) - the capturing of transaction and event information using technology to 

1. Process information according to defined business
2. Store the information
3. Update existing information to reflect the new information

• Online analytical processing (OLAP) - the manipulation of information to create business intelligence in support of strategic decision making

DECISION SUPPORT SYSTEMS

• Decision support systems (DSS) - models information to support managers and business professionals during the decision making process
• Three quantitative models used by DSSs include :

1. Sensitivity analysis - the study of the impact that changes in one (or more) parts of the model                                      have on other parts of the model 
2. What-if-analysis - checks the impact of a change in an assumption on the proposed solution
3. Goal-seeking analysis - finds the inputs necessary to achieve goals such as desired level of                                              output

• Interaction between a TPS and a DSS

EXECUTIVE INFORMATION SYSTEMS

• Executive information systems (EIS) - a specialized DSS that supports senior level executives within the organization
• Most EISs offering the following capabilities :

          ⏩ Consolidation - involves the aggregation of information and features simple roll-ups to                                                 complex groupings of interrelated information

          ⏩ Drill-down - enables users to get details, and details of details, of information

          ⏩ Slice-and-dice - looks at information from different perspectives

• Interaction between a TPS and a EIS

• Digital-dashboard - integrates information from multiple components and presents it in a                                            unified display

ARTIFICIAL INTELLIGENCE (AI)

• Intelligent system - various commercial applications of artificial intelligence
• Artificial intelligence (AI) - simulates human intelligence such as the ability to reason and                                                      learn 
• The ultimate goal of AI is the ability to build a system that can mimic human intelligence

• Four most common categories of AI include :

1.  Expert system - computerized advisory programs that imitate the reasoning processes of                                      experts in solving difficult problems
2.  Neural Network - attempts to emulate the way the human brain works                                                ( Fuzzy logic - a mathematical method of handling imprecise or subjective information)
3. Genetic algorithm - an artificial intelligent system that mimics the evolutionary, survival-of-                                      the-fittest process to generate increasingly better solutions to a problem
4. Intelligent agent - special-purposed knowledge-based information system that accomplishes                                   specific tasks on behalf of its users

           ⧭ Multi-agent systems

           ⧭ Agent-based modeling

DATA MINING

• Data mining software includes many forms of AI such as neural networks and expert systems

• Common forms of data-mining analysis capabilities include :

 CLUSTER ANALYSIS

🔺 Cluster analysis - a technique used to divide an information set into mutually exclusive groups                                        such that the members of each group are as close together as possible to one                                          another and the different groups are as far apart as possible

🔺 CRM systems depend on cluster analysis to segment customer information and identity behavioral      traits

ASSOCIATION DETECTION

🔻 Association detection - reveals the degree to which variables are related and the nature and                                                        frequency of these relationships in the information

⃗ Market basket analysis - analyzes such items as Web sites and checkout scanner information to                                                    detect customers' buying behavior by identifying affinities among                                                          customers' choices of products and services

STATISTICAL ANALYSIS

🔺 Statistical analysis - performs such functions as information correlations, distributions,                                                         calculations, and variance analysis

⤗ Forecast - predictions made on the basis of time series information

⤗ Time-series information - time-stamped information collected at a particular frequency

CHAPTER 8

ACCESSING ORGANIZATIONAL INFORMATION (DATA WAREHOUSE)

DATA WAREHOUSE FUNDAMENTALS

• Data warehouse - a logical collection of information (gathered from many different operational databases - that supports business analysis activities and decision-making tasks) 

• The primary purpose of a data warehouse is to aggregate information throughout an organization into a single repository for decision-making purposes

• Extraction, transformation, and loading (ETL) - a process that extracts information from internal and external databases, transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse

• Data mart - contains a subset of data warehouse information

MULTIDIMENSIONAL ANALYSIS AND DATA MINING

• Databases contain information in a series or two-dimensional tables
• In a data warehouse and data mart, information is multidimensional, it contains layers of columns and rows (Dimension - a particular attribute of information)
• Cube - common term for the representation of multidimensional information

       

• Data mining - the process of analyzing data to extract information not offered by the raw data                           alone
• To perform data mining, users need data-mining tools

           ⇰ Data-mining-tool - uses a variety of techniques to find patterns and relationships in large                                                    volumes of information and infers rules that predict future behavior                                                        and guide decision making

INFORMATION CLEANSING AND SCRUBBING

• An organization must maintain high-quality data in the data warehouse
• Information cleansing or scrubbing - a process that weeds out and fixes or discards inconsistent, incorrect, or incomplete information
• Contact information in an operational system

• Standardizing Customer name from Operational Systems

• Information cleansing activities

• Accurate and complete information

BUSINESS INTELLIGENCE

• Business Intelligence - information that people use to support their decision-making efforts
• Principle BI enablers include :

         ↠ Technology

         ↠ People

         ↠ Culture

CHAPTER 7

STORING ORGANIZATIONAL INFORMATION (DATABASES)

      

RELATIONAL DATABASE FUNDAMENTALS

• Information is everywhere in an organization
• Information is stored in databases  

           * Database - maintains information about various types of objects(inventory),                                                           events(transactions), people(employees), and places(warehouses)

• Database models include :

          * Hierarchical database model - information is organized into a tree-like structure(using                                                                          parent/child relationships)in such a way that it cannot have                                                                      too many relationships

             * Network database model - a flexible way of representing objects and their relationships

             * Relational database model - stores information in the form of logically related two-                                                                           dimensional tables

ENTITIES AND ATTRIBUTES 

• Entity - a person, place, thing, transaction, or event about which information is stored
• Attributes (fields, columns) - characteristics or properties of an entity class 

KEYS AND RELATIONSHIPS

• Primary keys and foreign keys identify the various entity classes (tables) in the database

             * Primary key - a field(or group of fields) that uniquely identifies a given entity in a table

             * Foreign key - a primary key of one table that appears an attribute in another table and acts                                          to provide a logical relationship among the two tables 

RELATIONAL DATABASE ADVANTAGES

• Database advantages from a business perspective include

             * Increased flexibility

                - A well designed database should

                    > Handle changes quickly and easily

                    > Provide users with different views

                    > Have only one physical view( deals with the physical storage of information on a                                 storage device. eg:hard disk)

                    > Have multiple logical views( focusses on how users logically access information)

                    > Eg : a mail-order buss-2 people view different format (logically views) but same                                           physical view

             * Increased scalability and performance

               - A database must scale to meet increased demand, while maintaining acceptable                                   performance levels

                   < Scalability - refers to how well a system can adapt to increased demands

                   < Performance - measures how quickly a system performs a certain process or                                                                  transaction 

             * Reduced information redundancy

               - Databases reduce information redundancy

                  > Redundancy - the duplication of information or storing the same information in                                                            multiple places

               - Inconsistency is one of the primary problems with redundant information- difficult to                           decide which is most current and most accurate

             * Increased information integrity (quality)

               - Information integrity - measures the quality of information

               - Integrity constraint - rules that help ensure the quality of information

                  < Relational integrity constraint - rule that enforces basic and fundamental information-                                                                            based constraints

                  < Eg : Users cannot create an order for a nonexistent customer, provide a markup                                             percentage that was negative

                  < Business-critical integrity constraint - rule that enforce business rules vital to an                                                                                                organization's success and often require more                                                                                          insight and knowledge than relational integrity                                                                                        constraints

                  < Eg : Product returns are not accepted for fresh product 15 days after purchase

             * Increased information security

                - Information is an organizational asset and must be protected

                - Databases offer several security features including :

                   > Password - provides authentication of the user

                   > Access level - determines who has access to the different types of information

                   > Access control - determines types of user access, such as read-only access

DATABASE MANAGEMENT SYSTEMS

• Database management systems (DBMS) - software through which users and application programs interact with a database

DATA-DRIVEN WEB SITES

• Data-driven Web sites- an interactive Web site kept constantly updated and relevant to the needs of its customers through the use of a database

DATA-DRIVEN WEB SITE BUSINESS ADVANTAGES

• Development - Allows the Web site owner to make changes any time-all without having to rely on a developer or knowing HTML programming. A well-structured, data-driven Web site enables updating with little or no training

• Content management - A static Web site requires a programmer to make updates. This adds an unnecessary layer between the business and its Web content, which can lead to misunderstandings and slow turnarounds for desired changes

• Future expandability - Having a data-driven Web site enables the site to grow faster than would be possible with a static site. Changing the layout, displays, and functionality of the site is easier with a data-driven solution

• Minimizing human error - Even the most competent programmer charged with the task of maintaining many pages will overlook things and make mistakes. This will lead to bugs and inconsistencies that can be time consuming and expensive to track down and fix. Unfortunately, users who come across these bugs will likely become irritated and may leave the site. A well designed, data-driven Web site will have "error trapping" mechanisms to ensure that required information is filled out correctly and that content is entered and displayed in its correct format.

• Cutting production and update costs - A data-driven Web site can be updated and "published" by any competent data entry or administrative person. In addition to being convenient and more affordable, changes and updates will take a fraction of the time that they would with a static site. While training a competent programmer can take months or even a years, training data entry person can be done in 30 to 60 minutes.

• More efficient - By their very nature, computers are excellent at keeping volumes of information intact. With a data-driven solution, the system keeps track of the templates, so users do not have to. Global changes to layout, navigation, or site structure would need to be programmed only once, in one place, and the site itself will take care of propagating those changes to the appropriate pages and areas. A data-driven infrastructure will improve the reliability and stability of  a Web site, while greatly reducing the chance of "breaking" some part of the site when adding new areas.

• Improved Stability - Any programmer who has to update a Web site from "static" templates must be very organized to keep track of all the source files. If a programmer leaves unexpectedly, it could involve re-creating existing work if those source files cannot be found. Plus, if there were any changes to the templates, the new programmer must be careful to use only the latest version. With a data-driven Web site, there is peace of mind, knowing the content never lost   

DATA-DRIVEN BUSINESS INTELLIGENCE

INTEGRATING INFORMATION AMONG MULTIPLE DATABASES

• Integration - allows separate systems to communicate directly with each other

          ⇒ Forward integration - takes information entered into a given system and sends it                                                                     automatically to all downstream systems and processes
          ⇒ Backward integration - takes information entered into a given system and sends it                                                                      automatically to all upstream systems and processes

• Forward integration

• Backward integration

• Building a central repository specifically for integrated information

• Without integration, an organization will :

          ↳ Spend considerable time entering the same info in multiple system
          ↳ Suffer from the low quality and inconsistency typically embedded in redundant info