Copyright © 2014 Pearson Education, Inc. 1 Managers need high-quality and timely information to support decision making Chapter 6 - Enhancing Business Intelligence Using Information Systems

Copyright © 2014 Pearson Education, Inc. 2 Administrivia Project 1 is due today! Project 3 is posted! – Project 2 will be posted soon Exam 1 in two weeks!

Copyright © 2014 Pearson Education, Inc. 3 A Map of Where We Are Societal Level Changes Facilitated By IT How This Influences Firm Positioning Executing Firm Strategy How do we know where we should be?

Copyright © 2014 Pearson Education, Inc. 4 Agenda Today is all about business intelligence My argument, at root, is that BI is about the effective capture, manipulation, and interpretation of data This, is analytics

Copyright © 2014 Pearson Education, Inc. 5 Chapter 6 Learning Objectives Business Intelligence Describe the concept of business intelligence and how databases serve as a foundation for gaining business intelligence. Business Intelligence Components Explain the three components of business intelligence: information and knowledge discovery, business analytics, and information visualization.

Copyright © 2014 Pearson Education, Inc. 6 Why Does an Organization Need BI? Respond to threats and opportunities – How will we know something is a threat unless we track it

Copyright © 2014 Pearson Education, Inc. 7 Why Does an Organization Need BI? Exploitation of the Big Data Movement – Information is freely available – “Sometimes I have difficulty talking to people who don’t race sailboats.” – Bruno Gianelli Big Data – High Volume Unprecedented amounts of data – High Variety Structured data Unstructured data – High Velocity Rapid processing to maximize value

Copyright © 2014 Pearson Education, Inc. 8 Why Does an Organization Need BI? Effective Planning is Continuous – Strategy is a multi-period game

Copyright © 2014 Pearson Education, Inc. 9 Why Organizations Need Business Intelligence: Continuous Planning

Copyright © 2014 Pearson Education, Inc. 10 Why Does an Organization Need BI? Responding to threats an opportunities Big Data Movement Effective Planning is Continuous Why does this matter? Speculation with the future of the firm is the hallmark of a bankrupt intellect when data is AVAILABLE and FREE

Copyright © 2014 Pearson Education, Inc. 11 Ok, so BI is important… The first thing we need is a place to store all of this data Where might we do that?

Copyright © 2014 Pearson Education, Inc. 12 Databases are cool All databases do is provide an efficient way to store information in a way that is efficient, stable, and secure

Copyright © 2014 Pearson Education, Inc. 13 Foundations The traditional database you may have seen is called an RDBMS – Relational Database Management System It has three levels – Entities, or tables What we are storing information about – Attributes, or columns The things that describe the entity – Rows, or records, or tuples The actual data that you are storing Entities Attributes Records

Copyright © 2014 Pearson Education, Inc. 14 Why do we do it this way? In the dark ages we would manage things in giant lists – Flat files How do you properly update this information? How do you change it? How do you manage it?

Copyright © 2014 Pearson Education, Inc. 15 BLARG! Low quality information example

Copyright © 2014 Pearson Education, Inc. 16 MORE BLARG! EmployeeSkillCurrent Work Location BrownLight Cleaning73 Industrial Way BrownTyping73 Industrial Way HarrisonLight Cleaning73 Industrial Way JonesShorthand114 Main Street JonesTyping114 Main Street JonesWhittling114 Main Street EmployeeCurrent Work Location Brown73 Industrial Way Harrison73 Industrial Way Jones114 Main Street EmployeeSkill BrownLight Cleaning BrownTyping HarrisonLight Cleaning JonesShorthand JonesTyping JonesWhittling

Copyright © 2014 Pearson Education, Inc. 17 How do we manage these data? The data resides in a database – The MyFirm database The database sits on a server – A powerful machine with lots of memory The data manipulation is done through a database engine or a work bench – SQL Server, Oracle, etc. The language we speak to the database in is called SQL – Structured Query Language

Copyright © 2014 Pearson Education, Inc. 18 SQL SQL is the simplest language conceived by man Four general commands – Select  retrieve data – Alter  Change the form of data – Update  Change the data itself – Drop  Get rid of things Select [customer_name] from [customer_list] where name = ‘Bob’

Copyright © 2014 Pearson Education, Inc. 19 And there are some super dooper benefits to them Enable interactive website An example?

Copyright © 2014 Pearson Education, Inc. 20 Then we define the goal The RDBMS is the king of the database world Slight modifications can help us achieve more strategic goals – i.e. specialized individual data models to increase efficiency of use

Copyright © 2014 Pearson Education, Inc. 21 Databases & Data Warehouses Operational Databases

Copyright © 2014 Pearson Education, Inc. 22 Data Warehousing and Data Marts

Copyright © 2014 Pearson Education, Inc. 23 Hypercubes… Create multi-dimensional “cubes” of information that summarize transactional data across a variety of dimensions. OLAP vs. OLTP Envisioned by smart businesspeople, built by the IT pros

Copyright © 2014 Pearson Education, Inc. 24 Demo Lets see a database in action

Copyright © 2014 Pearson Education, Inc. 25 Scenario – Stock Outs $200 million tied up in inventory Spend $1 million on new system to safely reduce inventory levels 10% – New system would actually be a better job at reducing “stock outs” What could your organization do with that $20 million? – Use that $20 million to put more salespeople out in the field. – Research and development – Other?

Copyright © 2014 Pearson Education, Inc. 26 Time for a break… Business Intelligence – Why we need it Data management fundamentals Tools you can use to get there

Copyright © 2014 Pearson Education, Inc. 27 Take a break…

Copyright © 2014 Pearson Education, Inc. 28 Recap of the Pre-Break Business Intelligence – Why we need it – In Generalities… Data management fundamentals – In a database… why do we use entities? – Entities are described by what? – The actual data which populates the entity is what? – Why would we need multiple databases? – If we put many databases together it is called what? – If we split data off of the data warehouse, what do we call it? – Why would we do this?

Copyright © 2014 Pearson Education, Inc. 29 Agenda How to store data Where we might pull data from How we might process these data How we might present these data We will now harken back to the transformation of data into knowledge. Having data is awesome, but only if we can leverage it

Copyright © 2014 Pearson Education, Inc. 30 Business Intelligence Components Business Intelligence Describe the concept of business intelligence and how databases serve as a foundation for gaining business intelligence. Business Intelligence Components Explain the three components of business intelligence: information and knowledge discovery, business analytics, and information visualization.

Copyright © 2014 Pearson Education, Inc. 31 Business Intelligence Components Three types of tools – Information and knowledge discovery – Business analytics – Information visualization Information and Knowledge Discovery – Search for hidden relationships. – Hypotheses are tested against existing data. For example: Customers with a household income over $150,000 are twice as likely to respond to our marketing campaign as customers with an income of $60,000 or less.

Copyright © 2014 Pearson Education, Inc. 32 Ad Hoc Reports and Queries

Copyright © 2014 Pearson Education, Inc. 33 Online Analytical Processing (OLAP) Complex, multidimensional analyses of data beyond simple queries OLAP server —main OLAP component Key OLAP concepts: – Measures and dimensions – Cubes, slicing, and dicing – Data mining – Association discovery – Clustering and classification – Text mining and Web content mining – Web usage mining

Copyright © 2014 Pearson Education, Inc. 34 Cubes Cube—an OLAP data structure organizing data via multiple dimensions Cubes can have any number of dimensions – Be careful, most people can’t comprehend after 3 dimensions! – When might we need more? A cube with three dimensions

Copyright © 2014 Pearson Education, Inc. 35 Slicing and Dicing Slicing and dicing—analyzing the data on subsets of the dimensions

Copyright © 2014 Pearson Education, Inc. 36 Data Mining Used for discovering “hidden” predictive relationships in the data – Patterns, trends, or rules – Example: identification of profitable customer segments or fraud detection – Any predictive models should be tested against “fresh” data. Data-mining algorithms are run against large data warehouses. – Data reduction helps to reduce the complexity of data and speed up analysis. ENDOGENEITY! - Bias resulting from omitted variables etc. – Relationship between ice cream sales and crime – Relationship between news media and firm founding

Copyright © 2014 Pearson Education, Inc. 37 Text mining the Internet

Copyright © 2014 Pearson Education, Inc. 38 Textual Analysis Benefits Marketing—learn about customers’ thoughts, feelings, and emotions. Operations—learn about product performance by analyzing service records or customer calls. Strategic decisions—gather competitive intelligence. Sales—learn about major accounts by analyzing news coverage. Human resources—monitor employee satisfaction or compliance to company policies (important for compliance with regulations such as the Sarbanes-Oxley Act).

Copyright © 2014 Pearson Education, Inc. 39 Web Usage Mining Used by organizations such as Amazon.com Used to determine patterns in customers’ usage data. – How users navigate through the site – How much time they spend on different pages Clickstream data—recording of the users’ path through a Web site. Stickiness—a Web page’s ability to attract and keep visitors.

Copyright © 2014 Pearson Education, Inc. 40 Web Usage Mining Google Analytics? News Related Information – ters/Dingman/EntrepreneurshipResearchBooklet.pd f#page=21 ters/Dingman/EntrepreneurshipResearchBooklet.pd f#page=21 Crowd Funding –

Copyright © 2014 Pearson Education, Inc. 41 Twitter Feeds Have you ever heard of anyone mining Twitter feeds? As a business person, what kind of information could you learn about your customers if you subscribed to every Twitter feed imaginable and mined the data?

Copyright © 2014 Pearson Education, Inc. 42 Any Danger? Is there any danger in a business student becoming too “tech savvy”? Is there an danger in a business student not becoming “tech savvy” enough? What is a “program” and is there anything that is more nerdy that being a “programmer”?

Copyright © 2014 Pearson Education, Inc. 43 How do we use these results? We must now transform the output from our analysis into usable information… We can do two things – Guide decision making through structured interaction with the data – Inform the user and allow them to make up their own minds

Copyright © 2014 Pearson Education, Inc. 44 Presenting Results

Copyright © 2014 Pearson Education, Inc. 45 Guiding Decision Making BI applications to support human and automated decision making – Decision Support Systems (DSS)—support human unstructured decision making – Intelligent systems

Copyright © 2014 Pearson Education, Inc. 46 Decision 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 – Example: Microsoft Excel

Copyright © 2014 Pearson Education, Inc. 47 Architecture of a DSS

Copyright © 2014 Pearson Education, Inc. 48 Common DSS Models

Copyright © 2014 Pearson Education, Inc. 49 Intelligent Systems Spencer Platt/Getty Images, Inc.. © 2002 Paramount Pictures/Courtesy: Everett Collection.. Three general types Expert Systems Neural Networks Intelligent Agent Systems talking-to-machines/ talking-to-machines/

Copyright © 2014 Pearson Education, Inc. 50 Expert Systems Likely the best example is WebMD –

Copyright © 2014 Pearson Education, Inc. 51 Could You Use an Expert System? The purpose of an intelligent system is to recognize patterns and try to inform the user of likely outcomes. Lets try a classification example…

Copyright © 2014 Pearson Education, Inc. 52 Can you recognize patterns and be trained? Classification of the unknown You see a new thing (noun) What is it? How do you know it is a dog? How do you know it is even an animal? How do you know if an animal is a mammal? How about a whale? How about a platypus?

Copyright © 2014 Pearson Education, Inc. 53 Scenario – Loan Officer You need to make approval/rejection decisions on loan applications? What information do you look at to make your decisions? Do you make decisions based on individual pieces of information or combinations of information? What combinations correlate with good/bad loans?

Copyright © 2014 Pearson Education, Inc. 54 Neural Network System We can also do this through a network

Copyright © 2014 Pearson Education, Inc. 55 Intelligent Agent Systems Program working in the background Bot (software robot) Provides service when a specific event occurs

Copyright © 2014 Pearson Education, Inc. 56 Types of Intelligent Agent Systems User agents – Performs a task for the user Buyer agents (shopping bots) – Search for the best price Monitoring and sensing agents – Keep track of information and notifies users when it changes Data-mining agents – Continuously browse data warehouses to detect changes Web crawlers (aka Web spiders) – Continuously browses the Web Destructive agents – Designed to farm addresses or deposit spyware

Copyright © 2014 Pearson Education, Inc. 57 Knowledge Management

Copyright © 2014 Pearson Education, Inc. 58 Benefits and Challenges of Knowledge-Based Systems

Copyright © 2014 Pearson Education, Inc. 59 Alternative It is also plausible that the data are so unstructured that creating rules about them is not feasible In this case we may want to assist the decision maker by making the data more simple to interpret

Copyright © 2014 Pearson Education, Inc. 60 Information Visualization Display of complex data relationships using graphical methods – Enables managers to quickly grasp results of analyses – Visual analytics – Dashboards – Geographic information systems

Copyright © 2014 Pearson Education, Inc. 61 Digital Dashboards

Copyright © 2014 Pearson Education, Inc. 62 Dashboards Dashboards use various graphical elements to highlight important information.

Copyright © 2014 Pearson Education, Inc. 63 Thematic Maps A thematic map showing car thefts in a town

Copyright © 2014 Pearson Education, Inc. 64 Geographic Information System (GIS)

Copyright © 2014 Pearson Education, Inc. 65 Todays Critical Thinking – Sir Charles and Shaq GWM GWM Amusing character that we all know Mr. Barkley to be, he has some strong opinions on analytics What is the strength of Charles’ argument? What is the weakness?

Copyright © 2014 Pearson Education, Inc. 66 Recap Online Analytical Processing Data Mining Decision Support Systems Information Visualization