Course Code CE609. Lecture : 03. Practical : 01. Course Credit. Tutorial : 00. Total : 04. Course Learning Outcomes

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1 Course Title Course Code Business Intelligence CE609 Lecture : 03 Course Credit Practical : 01 Tutorial : 00 Course Learning Outcomes Total : 04 On the completion of the course, students will be able to: Detailed Syllabus Differentiate between Transaction Processing and Analytical applications and describe the need for Business Intelligence Demonstrate understanding of technology and processes associated with Business Intelligence framework Demonstrate understanding of Data Warehouse implementation methodology and project life cycle Given a business scenario, identify the metrics, indicators and make recommendations to achieve the business goal Design an enterprise dashboard that depicts the key performance indicators which helps in decision making. Demonstrate application of concepts in Microsoft BI suite Sr. No. 1 Name of chapter & details Section I Introduction to Business Intelligence: Introduction to Data Warehousing & SAP BI, Data Acquisition, Data Transfer Process, Real-Time data acquisition, Introduction to digital data and its types structured, semi-structured and unstructured, Introduction to OLTP and OLAP, BI Definitions & Concepts, Business Applications of BI, BI Framework, Role of Data Warehousing in BI, BI Infrastructure Components BI Process, BI Technology, BI Roles & Responsibilities Hours Allotted 11 1

2 2 3 4 Basics of Data Integration (Extraction Transformation Loading): Concepts of data integration need and advantages of using data integration, introduction to common data integration approaches, Meta data - types and sources, introduction to ETL using SSIS, Introduction to data quality, data profiling concepts and applications, Generic extraction, Delta Mechanism & Administration, introduction to ETL using Pentaho data Integration (formerly Kettle) Section II Introduction to Multi-Dimensional Data Modeling: Introduction to data and dimension modeling, multidimensional data model, ER Modeling vs. multi dimensional modeling, concepts of dimensions, facts, cubes, attribute, hierarchies, star and snowflake schema, introduction to business metrics and KPIs, creating cubes using SSAS, Star Schema and Extended Star Schema, creating cubes using Microsoft Excel Basics of Enterprise Reporting: Introduction to Reporting, Components in Reporting Tools, Tools in Reporting, Query designer, BEx Analyzer, Report Designer, Web Application Designer, Report to Report interface A typical enterprise, Malcolm Baldrige - quality performance framework, balanced scorecard, enterprise dashboard, balanced scorecard vs. enterprise dashboard, enterprise reporting using MS Access / MS Excel, best practices in the design of enterprise dashboards Instructional Method and Pedagogy Lecture will be conducted with the aid of multi-media projector, blackboard, OHP etc. Few lectures will be conducted through live interactive webinars from Infosys; schedule will be shared with the students. Students are provided with Lecture notes and hand outs for pre reading. Edmodo is used as learning management systems for engaging students in off time. Students are engaged through various active learning activities. Assignments based on Course contents will be given to the students at the end of each unit/topic and will be evaluated at regular interval. Students will be informed of the expected time allocation of each of these learning activities during the course. Experiments shall be there in the laboratory related to course contents 2

3 Reference Books RN Prasad and Seema Acharya,Fundamentals of Business Analytics, First Edition, Wiley India David Loshin, Business Intelligence, Morgan Kauffman Series Mike Biere, Business intelligence for the enterprise, Pearson. Larissa Terpeluk Moss, Shaku Atre,Business intelligence roadmap, Addision Wesley Cindi Howson,Successful Business Intelligence: Secrets to making Killer BI Applications, McGraw Hill Brain, Larson, Delivering business intelligence with Microsoft SQL server 2008, TMH Lynn Langit,Foundations of SQL Server 2005 Business Intelligence, Apress. Stephen Few, Information dashboard design,o REILLY 3

4 List of Experiments Tutorial-1: Using Ms-Excel for Business analytics A. Understand the Need for Data Analysis. B. Organize and analyze the data. C. Understand the basics of pivot Tables and prepare pivot tables using sample data. D. Understand the basics of Charts and prepare charts using sample data. E. Customize Pivot Charts Tutorial-2: Using Ms-Access for Business analytics A. Understanding Ms-access B. Understanding MS ACCESS database data types C. Create a database a. Creating a table b. Writing Queries: c. Creating Forms. d. Preparing reports. D. Importing data from Excel Sheet E. Create a parameterized query F. Create a Pivot Chart. a. Creating a pivot table. b. Generating a Report using report wizard. G. Create a sub report Tutorial-3 Case Study: Using Pentaho data Integration4.01 for Business Analytics A. Installation and opening the Pentaho data Integration IDE. B. Creating a New repository C. Learning how to connect to the Created Repository. D. Learn how to create an ODBC CONNECTION. E. Developing transformations. a. Transform CSV file input into XML file output b. Transform Text file Input into excel file output. c. Transform Excel file input into MS-Access file output. F. Learn how to use the SELECT VALUES in Transformation. 4

5 Tutorial -4: SQl server Analysis server (SSAS) for Business analytics Create data source connection Create data source view create OLAP Cube in SQL Server Analysis Server Perform OLAP operations on CUBE. Tutorial-5: Case Study: Integrated project assignment Analyze the scores and percentages of the trainees in various modules. The analysis for scores and percentages has to be done in various assessments such as Test, Retest, Hands on, and/or Comprehensive Examination. Use the project specification document provided. 1. Perform (extraction Transformation Loading) ETL o Create a new database with the name Integrated Assignment. This database will include the following tables. (You are free to make the table names more meaningful by prefixing them with Dim or Fact.) Time (no need to create; load directly from the data provided). Assessment (to be created) Modules (to be created) Trainees (to be created) Score (to be created) 2. Perform (Multi Dimensional data Modeling) MDDM o Create the cube for analysis. Identify four dimensions for the cube. One of the dimensions is Time. Consider only calendar related attributes and create a calendar hierarchy Identify one measure group for the cube. Identify three measures for the cube 3. Perform ER Prepare chart Report Prepare table report 5