ISQS 6339, Business Intelligence Anatomy of Business Intelligence

1. ISQS 6339, Business IntelligenceAnatomy of Business Intelligence Zhangxi Lin Texas Tech University 1

2. Learning Objectives • Understand the general ideas in business intelligence by cases • Catch main BI concepts • Get familiar with the most popular BI applications and tools • Know how to access your BI resources for this course

3. Outline • BI case studies • BI framework • BI applications • BI tools

4. BI Case Studies • Cases • Premier Bank Card 3’46” • SAP Rail Analytics 9’44” • Advanced applications • Mobile Business Intelligence with iPhone 2’58” • Business intelligence with iPad 6’49”

5. Case: Toyota Motor Sales USA – 2011 Gartner BI Excellence Awards • Challenge: how to reduce vehicle transit cost • Average: $8/day-car * 10 days = $72-80/car, 9-10days/transit • Total $144-160 million/year for transit of two million cars • Problem: • Inability to deliver cars to dealers timely • Computers generated tons of directionless reports and data with little help • Unable to make timely decisions

6. Case: Toyota Motor Sales USA (II) • Solution: Data warehouse • Use right technologies provided by a right vendor following correct concepts – Oracle’s data warehouse + Hyperion’s BI platform • Lesson learned: data cleansing is important • Results • Discovered that the company was billed twice in some occasions • Increase the volume of cars by 40% between 2001-2005 • In-transit time was reduced 5% • Market share increased • According to IDC Inc. the return on the BI investment was 506%

7. Questions • In what way did the old system create problems for Toyota? • What information needs of managers re satisfied by the new system? • What decisions are supported by the BI system?

8. Case: Chery Automobile • Chery Automobile (simplified Chinese: 奇瑞汽车) is an automobile manufacturer in China. • It is owned by the local government of Wuhu, Anhui province, but is scheduled to be privatized. • In 2009 Chery produced 508,500 units of automobile. • Of the 500,000 Chery vehicles sold in 2009, 409,300 units were sedans. • It is the largest independent Chinese auto manufacturer and one of the fastest growing automakers in the world. Source: http://en.wikipedia.org/wiki/Chery_Automobile

9. Chery Automobile’s BI System • Problems – supply chain did not meet JIT • Suppliers have to build their inventory storages in surrounding Chery main production lines. • Objectives • Improve the performance of JIT system • Save the cost of part suppliers by reducing the inventory storages. • Solution • Hefei University of Technology helped the company establishing a BI system to improve the efficiency of production. • A 90-day automatic early notification of order is set to coordinate the suppliers’ production plan.

10. Questions • What is the relationship between BI and MIS? • What are main applications in BI? • What are main BI technologies?

11. Different Users of Business Intelligence 11 • There are many different users who can benefit from business intelligence • Executives – Those who focus on the overall business • Business Decision Makers – Usually focused on single areas of the business (finance, HR, manufacturing, and so forth) • Information Workers – Typically managers or staff working in the back office • Line Workers – Employees who might use BI without knowing it • Analysts – Employees who will perform extensive data analysis

12. Business Intelligence Business Analytics BI Applications: • Data warehousing • Data mining • BPM • OLAP • etc. Executives Managers Operators Data BI Users Business Environment Data Decisions

13. BI vs. MIS • MIS were used by a select few in the organization, due to the efforts involved in collecting data and preparation of summaries from the same. Use of Computers in the MIS process helped in speeding up the process and increased its reach. • Then came the phase of BI • BI has been privilege of the TOP segment of the pyramid. • The cost involved prohibited the expansion of BI to the Middle tier Business users. • Operational BI is expected to do the task of making it available to masses, as they are the ones who need BI, more times in a day.

14. BI Framework

15. A Framework for Business Intelligence (BI) • The Origins and Drivers of Business Intelligence • Organizations are being compelled to capture, understand, and harness their data to support decision making in order to improve business operations • Managers need the right information at the right time to make right decisions.

16. A Framework for Business Intelligence (BI) • The Business Value of BI • How BI Can Help • Assess their readiness for meeting the challenges posed by these new business realities • Take a holistic approach to BI functionality • Leverage best practices and anticipate hidden costs • Key Issues and Framework for BI Analysis • How can enterprises maximize their BI investments? • What BI functionality do enterprises need, and what are they using today? • What are some of the hidden costs associated with BI initiatives?

17. A Framework for Business Intelligence (BI) • Time savings • Single version of truth • Improved strategies and plans • Improved tactical decisions • More efficient processes • Cost savings • Faster, more accurate reporting • Improved decision making • Improved customer service • Increased revenue • The Benefits of BI

18. Changing Business Environments and Computerized Decision Support

19. A Framework for Business Intelligence (BI) • BI’s Architecture and Components • Data Warehouse • Business Analytics • Automated decision systems • Performance and Strategy

20. A Framework for Business Intelligence (BI)

21. A Framework for Business Intelligence

22. BI Applications

23. Main BI Topics • Data warehousing – Making historical data available for analytics • Data preparation – Extraction, transformation and loading • Query - a collection of specifications that enables you to focus on a particular set of data. • Online Analytical Processing (OLAP) - a capability of information systems that supports interactive examination of large amounts of data from many perspectives. • Reporting - generates aggregated views of data to keep the management informed about the state of their business. • Data mining - extraction of knowledge by utilizing software that can isolate and identify previously unknown patterns or trends in large amounts of data. 23 23 ISQS 3358 Business Intelligence

24. BI Applications • Visualizations • Scorecards • Dashboard • Reports • Analytic applications • Data mining • Predictions • OLAP & OLTP

25. Visualization Cases • Economic Inequality 4’22” • Stock market performance 1’15” • Ocean Environment Animation 5’13”

26. Predictive Multi-channel Marketing for Everyone Example Name Metric Engine Cube Engine Metric Engine Cube Engine Metric Engine Cube Engine Address Phone email Predictive Model Predictive Model Predictive Model Social Profile Web Behavior

27. Example

28. Example

29. Business Scorecards We see this everyday 29

30. The Purpose of a Scorecard • A scorecard should give an executive a visual representation of the health of an organization in a single glance • The scorecard is of sufficiently high level to represent major business operations and their goals • The data in a scorecard should be as recent as possible to make them more actionable 30

31. The Contents of a Scorecard • Scorecards usually contain some or all of the following elements: • Key Performance Indicators (KPIs) • KPI actual values compared to historical values (for trend analysis) • KPI actual values compared to a forecast or budget amount • Rankings of different departments, locations, products, and so forth • Developing KPIs and Scorecards with SharePoint 31

32. Dashboards 32

33. The Purpose of a Dashboard • A dashboard is designed to allow decision makers to see a variety of data that affects their divisions or departments • This data may be in the form of scorecards, charts, tables, and so forth • The dashboard is generally customized for each user • More targeted and detailed than a scorecard 33

34. The Contents of a Dashboard • A Dashboard generally contains a variety of different views of data • The data is generally KPIs and shows trends, breakdowns, and comparisons against a forecast or historical data • The dashboard often consists of charts and tables, and may include scorecard elements as well 34

35. Reports 35

36. The Purpose of Custom Application Integration 36 • An application used by line workers may include business intelligence without the worker realizing what is happening • A sales clerk may get a list of targeted recommendations to make based on what the customer is buying • A loan officer may be presented with the level of risk associated with granting a loan to a particular customer

37. The Contents of Custom Application Integration 37 Custom applications may include predictive output from data mining models Custom applications can show history and trends for the current customer, supplier, and so forth Custom applications may allow easy ways for users to explore the data for relationships

38. Analytic Applications 38

39. The Purpose of Analytic Applications 39 Analytic applications free analysts from building complex models and writing complex queries Analysts are free to focus on the data and discover relationships and drivers behind numbers Rich visualizations allow much easier understanding of trends and relationships

40. The Contents of Analytic Applications 40 Analytic applications typically have no limits; analysts can see everything Analytic applications can view and analyze all of an organization’s data in a number of ways Analytic applications are powerful, but not as easy to use as other mechanisms

41. OLTP vs. OLAP • Online transaction processing systems (OLTP) Systems thathandle a company’s routine ongoing business • Online analytic processing (OLAP) An information system that enables the user, while at a PC, to query the system, conduct an analysis, and so on. The result is generated in seconds 41 ISQS 3358 Business Intelligence

42. 2011 China Social Media Password Leak • In 2011, a huge cache of personal data from China’s most popular websites leaked onto Internet. Between December 21 and 25, hackers released more than 100 million users account information including usernames, passwords, and emails (reference here). • Victims include users in IT technical community, social networking, gaming, and microblogging websites. • Due to many China’s online companies failed to encrypt user password, the online security crisis has caused panic among Internet users in China and worry about more websites were hacked and personal information is at risk.

43. Password Length • Except for company B, the average password lengths in companies A, C, and D are close to 8 digits. • The average password length of company B is 9.46 (about 1.5 digits higher than users in A, C, D). • The results indicate IT professions have higher sense of security even the company B has lower password length requirement.

44. Unsecured Rules of Password Constitution • The results show most long password constitutions followed one of the rules below: • Name abbreviation + ID numbers • Full name + phone numbers • English name + birthday • Full email address • Pingyin (transcribe Chinese characters into the Roman alphabets)

45. BI Tools

46. BI Products & Providers • Traditional Providers • Microsoft • SAS • IBM • Oracle • SyBase • Business Objects • BI Tools Survey • Big Data solution providers • Cloudera • Yahoo! • IBM • Amazon • Google 46 46 ISQS 3358 Business Intelligence

47. List of Traditional BI tools 47 47 ISQS 3358 Business Intelligence

48. Software Used in this Class • Microsoft SQL Server 2008 • SAS Enterprise Guide v4.2 • Base SAS for Data Preparation Programming ISQS 6339, Data Mgmt & BI 48

49. Reading Assignments • Find and read “How Much Information? 2003” (http://www2.sims.berkeley.edu/research/projects/how-much-info-2003/execsum.htm) - Could you find newer information about the information explosion? • Find a BI application case from the web, and understand how it works. • Find paper “CACM2011 Overview of BI.pdf” in the network drive under ~\Texts\Readings\. Read it carefully.

50. CAABI • Center for Advanced Analytics and Business Intelligenceinitially started in 2004 by Dr. Peter Westfall, ISQS, Rawls College of Business. • Looking to offer support to companies in developing BI capabilities. • Lots of technical expertise. ISQS 6339, Data Mgmt & BI 50