Enhancing Business Intelligence Using Information Systems PDF

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Teacher: Wenli Zhang...

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Chapter 6

MIS 304

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Enhancing Business Intelligence Using Information Systems BUSINESS INTELLIGENCE (BI) AND DATABASES o What is Business Intelligence (BI)?  Using information systems to gather and analyze information from internal and external sources in order to make better business decisions  E.g. “More than 35% of the top 5,000 global companies will regularly fail to make insightful decisions about significant changes in their business and markets” o Sources of BI Data  BI is used to integrate data from internal and external sources including:  Databases  Spreadsheets  Reports & articles  E.g.:  “How effective is this year’s promotion as compared to last year’s?”  “Which customers are most likely to switch to our competitor if we raise our price by 10%?” o Need for BI: Threats and Opportunities for the Organization  Globalization  Unstable markets  Competitive pressure  Consumer demands  Government regulations  Short product life cycles o BI: Understanding Big Data  Businesses are dealing with the challenge of “Big Data”  High Volume  Unprecedented amounts of data  High Variety  Structured data + Unstructured data  High Velocity  Rapid processing to maximize value o BI: Continuous Planning  Organizations must continuously monitor and analyze business processes  Results lead to ongoing adjustments  Involves decision from all levels o Databases: Inputs to BI Applications  Data, information and knowledge are among the most important assets for a company  Some type of database is behind every information system in all major companies

Chapter 6

MIS 304

Lecture Notes

Databases are collections of related data organized in a way that facilitates data entry and searches  Allows generation of dynamic and relevant content o Databases: Foundation Concepts  Database Management System (DBMS)  The software that allows users and programs to access and manage the database  Database  Collection of related tables o Main Database Elements  Table  Contains data about entities (i.e., the “thing” or object about which you want to track data, e.g., customers).  Consists of rows and columns  Row (record)  A record in a table  One row pertains to one entity instance  Column (attribute)  One cell in a row  Each attribute contains a piece of information about the entity o Databases: Advantages 

o Databases: Costs and Risks o Databases: Effective Management  Data model: A map or diagram that represents entities (e.g. CUSTOMERS, ORDERS, PARTS) and their relationships (e.g., entity-relationship diagram)  Normalization: A process to make sure the database will operate efficiently. Helps to eliminate data duplication  Data type: Each attribute has a specified data type (e.g. text, numbers, or dates)  Data dictionary: A document explaining information for each attribute (e.g. name, whether it is an identifier, data type, and valid values)  Business rules: Prevent illegal or illogical entries from entering the database o Databases: Entering and Querying Data o Databases: Query via Graphical User Interface o Databases: Basis of Other Information Systems  Online Transaction Processing (OLTP)  Systems that interact with customers and run a business in real time  Master Data Management  Data deemed most important in the operation of a business  Shared among multiple organizational units

Chapter 6

MIS 304

Lecture Notes

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Data Warehouses  Integrate data from multiple databases and other data sources  Contain historic as well as current data  Data Marts  Mini data warehouse, limited in scope to organizational unit o Operational vs. Informational Systems o Extract, Transform, and Load (ETL)

BI COMPONENTS o Information and Knowledge Discovery: Common Reports and Queries o Information and Knowledge Discovery: Online Analytical Processing (OLAP)  Complex, multidimensional analyses of data beyond simple queries o OLAP Terms and Concepts  Measures / Facts  Facts, numerical data that can be aggregated  Dimensions  Perspectives on which to view the facts  Hierarchically arranged to enable drill-down and roll-up  Cubes  Multidimensional structure of dimensions and measures  Speed up complex queries by pre-computing aggregate data  Slicing and Dicing  Analyzing data on a subset of dimensions o OLAP: Cubes, Slicing, Dicing o Data Mining  Discovering “hidden” predictive relationships in the data  Complicated algorithms run on large data warehouses  Types of data mining algorithms  Association discovery  Clustering  Classification o Text & Web Content Mining o Presenting the Results of Data Mining  Data mining results can be delivered to users in a variety of ways:  Digital dashboards  Paper reports

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MIS 304

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Web portals E-mail alerts Mobile devices Etc.

o Business Analytics to Support Decision Making  Business Analytics Systems  Decision Support Systems  Intelligent Systems  Knowledge Management Systems o Business Analytics Systems  Augments business intelligence by using statistical analysis and predictive modeling  Build explanatory models to help understand the data, identify trends o Decisions Support Systems (DSS)  Decision-making support for recurring problems  Used mostly by managerial level employees (can be used at any level)  Interactive decision aid  What-if analyses  Analyze results for hypothetical changes o Intelligent Systems  Machine Learning (e.g. neural networks)  Expert systems  Intelligent agents o Intelligent Systems: Machine Learning: Neural Networks  Neural networks approximate the functioning of the brain by creating common patterns in data and then comparing new data to learned patterns to make a recommendation o Intelligent Systems: Expert Systems  Use reasoning methods  Provide advice like a human expert  Manipulate knowledge rather than information  System asks series of questions  Inferring/pattern matching  Matching user responses with predefined rules  If-then format  Fuzzy logic  Represent rules using approximations o Knowledge Management Systems  Explicit knowledge  Easily codified and documented  Tacit knowledge  Embedded in people’s minds  Hard to get at

Chapter 6

MIS 304

Lecture Notes

 Important for best practices o Information Visualization  Dashboard  Comprised of key performance indicators (KPIs)  Visual display of summary information  Aid in situational awareness and decision making  Visual Analytics  Interactive graphics for complex analysis  Geographic Information Systems  Visualizing geographic information o Information Visualization: Digital Dashboard of Business Data  Dashboards use various graphical elements to highlight important information o Visual Analytics  Social Network Analysis  E.g. COPLINK (developed at UA, purchases by IBM) help police analyze social networks o Geographic Information System (GIS)  A GIS is a system for creating, storing, analyzing, and managing geographically referenced information  A GIS provides a user with a blank map of an area  A user can add information stored in different layers  Examples:  What areas are underserved by restaurants?...