2. Dr. K. D. Joshi © 2

3. 3 Quality Data Data Modeling Data Analysis Data presentation & Visualization Data presentation & Visualization Business Intelligence Capabilities

4. 4 Companies need to develop four types of BI capabilities to successfully implement a data driven decision making. The four BI capabilities include:  (BIC#1)Visualization and Intelligence Delivery Capability: This capability allows companies to access and visualize data in a fashion that assist in good decision making (make the decision makers more intelligent). More specifically, this capability allows companies to monitor and assess progress towards its strategic goals.  (BIC#2) Data Warehousing Capability: Data modeling capability provides companies with the ability to structure a data repository in a standardized and integrated manner.  (BIC#3) Analytical Capability: This capability allows companies to grow into an analytical company which is data and fact-driven in its approach to decision making.  (BIC#4) Data Cleaning and Integration Capability: Data cleaning and integration capability allow companies to profile, clean, map, and load the data into data repositories.

5. Flat File Databas e Excel Sheets XM L Databa se Data Integration Capability Analytical Capability Visualization and Intelligence Visualization and Intelligence Delivering Capability Delivering Capability Module 4 Module 2 Module 3 Module 1

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7. Text Book Chapters 1, 2, 18, 10

8.  Manufacturing Firm  Manufactures and sells small, hand-painted figurines.  Four Product lines: 1. Woodland Creatures collection of North American animals 2. The Mythic World collection, which includes dragons, trolls, and elves 3. The Warriors of Yore collection containing various soldiers from Roman times up through World War II 4. The Guiding Lights collection featuring replica lighthouses from the United States Four product lines, 15 product subtypes, and about 50 products  The miniatures are made from clay, pewter, or aluminum. 8

9. 9 Distribution Channels: Three different channels 1. Retail: It operates five of its own "Maximum Miniature World" stores dedicated to selling the Max Min product line. 2. Online: Max Min also operates MaxMin.com to sell its products online. 3. Wholesale: In addition, Max Min sells wholesale to other retailers.

10. 10 Business Needs  Rapid growth in the past three years - with orders increasing by over 300%  This growth has put a strain on Max Min's only current source of business intelligence, the printed report  Reports that worked well to support decision making just a few years ago now take an hour or more to print and even longer to digest. These reports work at the detail level with little summarization. Max Min's current systems provide few, if any, alternatives to the printed reports for viewing business intelligence.  Facing tough competition in a number of its product areas  This competition requires Max Min to practice effective decision making to keep its competitive edge. Unfortunately, Max Min's current business intelligence infrastructure, or lack thereof, is making this extremely difficult.

11. 11 Business Solution  Launched a new project to create a true business intelligence environment to support its decision making  This project includes the design of a data warehouse structure, the population of that data warehouse from its current systems, and the creation of analysis applications to serve decision makers at all levels of the organization.  The new business intelligence platform is based on SQL Server 2012  After an extensive evaluation, it was decided that the SQL Server 20012 platform would provide the highest level of business intelligence capability for the money spent. SQL Server 2012 was also chosen because it features the tools necessary to implement the data warehouse in a relatively short amount of time.

12. 12 Decisions about the performance of their manufacturing process and sale/marketing processes. Two Business Processes 1. Manufacturing Process 2. Sales and Marketing Process

13. MANUFACTURING PROCESS 13  The vice president (VP) of production for Max Min, Inc. wants to analyze the statistics available from the manufacturing automation system. He would like an interactive analysis tool, rather than printed reports, for this analysis.  The data is collected from Plant floor Transaction system, Order Processing Transaction Systems, Accounting Transaction Systems.

14. 14  Business Process  Manufacturing data  Inventory data  Manufacturing Transaction MoldingPaintingDo Quality Test Start the process Start of Transaction Finish the process End of Transaction Collect transactional data

15. 15  Decision Maker’s Needs -An interview with the VP of production yielded the following data requirements for effective decision making:  Number of accepted products by batch by product by machine by day  Number of rejected products by batch by product by machine by day  Elapsed time for manufacturing by product by machine by day  Product rolls up into product subtype, which rolls up into product type  Machine rolls up into machine type, which rolls up into material (clay, pewter, or aluminum)  Location - Machine also rolls up into plant, which rolls up into country  Time - Day rolls up into month, which rolls up into quarter, which rolls up into year  The information should be able to be filtered by machine manufacturer and purchase date of the machine

16. 16  Decision Maker’s Needs  Measures  Manufacturing Measures  Accepted Products  Rejected Products  Elapsed time for manufacturing  Percent Rejected (Total Rejects/Total Produced)  Inventory Measure  Inventory level  Backorders  Dimensions  Batch  Time  Product  Machine  Location  Hierarchies  Date-Month-Quarter-Year  Product – ProductSubType – ProductType  Machine – MachineType – Material  Machine – Plant - Country

17. 17  The VP of sales for Max Min, Inc. would like to analyze sales and Marketing information. This information is collected by three OLTP systems: the Order Processing System, the Point of Sale (POS) System, and the MaxMin.com Online System

18. 18  Decision Maker’s Needs -The VP of sales would like to be able to analyze the following numbers:  Dollar value of products sold  Number of products sold  Sales tax charged on products sold  Shipping charged on products sold  These numbers should be viewable by:  Store  Sales Promotion  Product  Day, Month, Quarter, and Year  Customer  Sales Person

19. Using Management Studio 19

20. BI Systems are commonly referred to as: 1. Online Analytical Processing Systems (OLAP Systems) or 2. Cubes 20

21. 21 Information Retrieval for Decision Making using the Cube  Total Number of Rejected Products  Total Number of Rejected Products by all the Products  Further manipulation of Query in Ad-hoc fashion  Sort in some order – Order of total rejects  Filer and Group based on the measure –Top 10, Bottom 10, Top 1% etc.  Filter by dimension  Filer by a value of a dimension  View/Show as Percentages  Commands and Options

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24. 24 Note: The Analysis Services automatically uses the authentication information that you used to log into the computer

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27. 27 This Window Lists all the Measures and Dimensions Folders This Bar allows for filtering the Query results using operators and expression This area displays the Dimensions and the Measures. Drag and Drop the Dimensions and the Measures from the Measure window into this area

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29. 29 Is this information useful?

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31. 31 Is this information useful?

32. 32  Defect Analysis ? Have we been able to decrease the defect count over past three years? ? What product lines are producing the most number of defects? ? What impact does this (defect rate) have on the Customers?

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41. 41 NOTE: If you do not see the PivotTable Fields on the right side, click anywhere on the PivotTable and it will be shown.

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44. 44  Cycle Time (Drill Down Feature) ? How long does it take to make each product? ? How long does it take to make each product on each machine? ? Does the production time change by Plants?

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48.  Link to the Tableau tutorial

49. Effective Organizational Decision Making  Who is the decision maker? 1. Goal – Based of Strategic Objectives 2. Measures 3. Closing of the loop - feedback & next steps  Good Goals should have  Specific Target  Means to measure whether we are progressing toward the Target  Effective Decision Making at MaxMin Inc. Manufacturing Floor

50.  How to build IT systems such as MaxMin Manufactring  Very complex & expensive  It should contains all four BICs

51. BI SYSTEM COMPONENTS Data Source Flat Files Transactions DB (OLTP) XML Files Excel Files Etc. Data Repository Datamart DataWarehourse OLAP System Multidimensional Database - Cubes Data Analysis Visualization Cube Browsing Reporting Dashboards Data Mining Module 4: Populate a DataMart Chapter 7 & 8 – Larson Book ETL Process SSI Services Module 2: Design a Datamart: Chapter 3 & 6 Larson Book Requirement Analysis Creating a Schema SS DB Engine Module 3: Business Analytics Chapter 4,9, 10 – Larson Book Build an OLAP/Cube SSA Services Module 1: Delivering BI Chapter 1, 2, 10,18– Larson Book Creating KPI Creating Reports Excel and Tableau

52.  What kind of data should be stored in a BI system?  Data for decision making?  Data for measuring goals/performance/  Data for filtering/slicing/dicing the measures – Data for Slicers and Drilldowns  The two types of data structures stored in the BI systems  Measures  Dimensions

53. Examples by Functional Area Module 1 - Part II 53 Data used to compute Metrics or KPIs Categories used to Summarize the Metrics/KPIs

54. Module 1 - Part II 54  Measures and Dimensions for Manufacturing BI Systems.  Measures and Dimensions for Marketing BI Systems.  Measures and Dimensions for Financial BI Systems.

55. Module 1 - Part II 55  Identify possible performance measures used to examine manufacturing processes and outcomes.  Identify possible dimensions used to view the performance measures.

56. Module 1 - Part II 56  Performance Measures Units /Products Produced Units /Products Rejected Defect Ratio/Percent of Rejected Products Cost Average, Beginning, and Ending Inventory (Units and Dollars)  Dimensions Time Product Assembly Line/Machine Defect Type Shift Employee Warehouse Suppliers

57. Module 1 - Part II 57  Identify possible performance measures used to examine Sales and Marketing processes and outcomes.  Identify possible dimensions used to view the performance measures.

58. Module 1 - Part II 58  Performance Measures Dollar Sales Unit Sales Cost Profit Margin Web Visits  Dimensions Time Product Customer Salesperson Promotion Other Demographics Data – Gender, Age, Income Level, Education Level

59. Module 1 - Part II 59  Identify possible performance measures used to examine Financial processes and outcomes.  Identify possible dimensions used to view the performance measures.

60. Module 1 - Part II 60  Performance Measures Revenue Expenses Margin ROI COGS – Cost of Goods Sold Taxes  Dimensions  Time  Product  General Ledger Account Type  Customer

61.  BICs for data driven decision making  BIC#1,Visualization and Intelligence Delivery Capability, for better decisions.  BIC#1 key to effective decision making because it equips decision makers with data which are critical for making intelligent decisions.  MaxMin Inc. in Need of a BI system to make better decisions  Manufacturing System  Sale/Marketing System  What is a BI system comprised of?  What is stored in the BI Systems?  How does a BI systems support organizational decisions making?

62.  Get your own copy – see the syllabus for the instructions  Todd203 also have a copy of this software on each machine