PG Program in Business Analysis and Product Management

2.1 Introduction to Business Analysis 

• Business Analysis overview
• Who is a Business Analyst?
• Introduction to governance body (IIBA)
• Business Analysis body of knowledge
• Knowledge areas of BABOK
• SDLC & requirement analysis

2.2 Business Analysis Concepts and Knowledge Areas                    

• Business Analysis core concepts and knowledge areas
• Planning and monitoring
• Business Analysis approach and governance
• Business Analysis information management
• Elicitation and collaboration

2.3 Requirement Lifecycle Management and Strategy Analysis 

• Trace, maintain, & prioritize requirements
• Assess requirement changes and approval
• Analyze current state
• Define future state
• Assess risks
• Define change strategy

2.4 Requirement Analysis, Design Definition, Model Requirements, and Solution Evaluation 

• Specify model requirements
• Verify and validate requirements
• Define requirement architecture and design options
• Measure and analyze solution performance
• Assess solution and enterprise limitations
• Recommend actions to increase solution values
• Data model, UI model, user stories

2.5 Agile Business Perspectives and Creating UML 

• Introduction to business Agile perspective
• Business Intelligence perspective
• Information Technology perspective
• Business architecture perspective
• Business Process Management perspective

2.6 Understand BA Role on the Agile Team

• Write effective user stories and acceptance criteria
• Develop backlogs into great products
• BA role in new age Business Analysis

2.7 Underlying Competencies of a Business Analyst & Microsoft Visio 

• Business Analyst underlying competencies
• BA Skills
• Soft skills, leadership and personal development
• UML diagrams using Microsoft Visio
• Types of flowcharts, cross-functional flowcharts

3.1 Data Science and Analytics Fundamentals

• Introduction to data science and analytics
• Use cases in data science and analytics
• Data science life cycle
• Data Analytics: Types
• AI and Machine Learning: Overview

3.2 CBDA: Introduction

• CBDA: Overview
• What is Business Data Analytics?
• Eligibility criteria
• Six Business Data Analytics domains

3.3 Business Analysis and Data Analytics

• Business analysis in data analytics projects
• Comparison between business analysis and data analytics

3.4 Business Data Analytics Domains: Introduction

Domain 1: Identifying the Research Questions

• Defining business problems or opportunities
• Identifying and understanding stakeholders
• Current state assessment
• Defining the future state
• Formulation of research questions
• Planning the Business Data Analytics approach

• Selection of techniques for the identification of research questions

Domain 2: Source Data

• Data collection planning
• Determination of datasets
• Data collection
• Data validation

Domain 3: Data Analysis

• Developing a Data Analysis plan
• Data preparation
• Data exploration
• Performing data analysis
• Assessment of the analytics and system approach

Domain 4: Interpreting and Reporting Results

• Validating the understanding of stakeholders
• Planning for stakeholder communication
• Determining the communication requirements of the stakeholders
• Deriving insights from data
• Documentation and communication of findings from the completed analysis
• Selection of techniques for interpreting and reporting results

Domain 5: Using Results to Influence Business Decision-making

• Action recommendation
• Implementation plan development
• Change management
• Guiding the organizational-level strategy for Business Data Analytics
• Organizational strategy
• Talent strategy
• Data strategy

3.5 Techniques

• Business simulation
• Business visualization
• Concept modeling
• Data dictionary, flow diagrams, mapping, and storytelling
• Decision modeling and analysis
• Descriptive and inferential statistics
• Extract, Transform, and Load (ETL)
• Exploratory data analysis
• Hypothesis formulation and testing
• Interface analysis
• Optimization
• Problem shaping and reframing
• Stakeholder list, map, and personas
• Survey and questionnaire
• Technical visualizations
• The big idea
• 3-minute story

4.1 Introduction to Agile Scrum 

• Agile Scrum overview
• Agile project principles
• Sprint and Increment in Agile Scrum
• Scrum theory
• Other Agile Frameworks

4.2 Scrum Team and Artifacts and Events

• Scrum team and Scrum Master
• Scrum roles
• Scrum flow
• Scrum artifacts: product backlog 
• Artifacts transparency
• Scrum events: sprint planning and retrospective
• Agile estimating, planning, monitoring, and control

4.3 Project Management Using Jira 

• Introduction to Project Management in Jira
• Jira issue types
• Scrum & Kanban boards
• Customizing board settings
• Release and backlog management
• Jira reports

5.1 Class diagram
5.2 Component diagram
5.3 Composite structure diagram
5.4 Deployment diagram
5.5 Object diagram
5.6 Package diagram
5.7 Profile diagram
5.8 Activity diagram
5.9 State machine diagram
5.10 Use case diagram
5.11 Communication diagram
5.12 Interaction overview diagram
5.13 Sequence diagram
5.14 Timing diagram

6.1 Communication skills
6.2 Leadership skills
6.3 Problem-solving skills
6.4 Business knowledge
6.5 IT knowledge

7.1 Introduction to Data Visualization and Power of Tableau

• What is data visualization?
• Comparison and benefits against reading raw numbers
• Real use cases from various business domains
• Examples using Tableau
• Installing Tableau, Tableau interface, connecting to DataSource, Tableau data types
• Data preparation

7.2 Architecture of Tableau

• Installation of Tableau Desktop
• Architecture of Tableau
• Tableau interface
• How to start with Tableau
• The ways to share and export the work done in Tableau

Hands-on Exercise:

Play with Tableau desktop, learn about the interface, share and export existing works

7.3 Working with Metadata and Data Blending

• Connection to Excel
• Cubes and PDFs
• Management of metadata and extracts
• Data preparation
• Joins and Union

Hands-on Exercise:

Connect to Excel sheet to import data, use metadata and extracts, manage NULL values, clean up data before using, perform the join techniques, execute data blending from multiple sources

7.4 Creation of Sets

• Mark, highlight, sort, group, and use sets 
• Constant sets
• Computed sets, bins, etc.

Hands-on Exercise:

Use marks to create and edit sets, highlight the desired items, make groups, apply to sort on results, make hierarchies among the created sets

7.5 Working with Filters

• Filters 
• Filtering continuous dates, dimensions, and measures
• Interactive filters, marks card, and hierarchies
• How to create folders in Tableau
• Sorting in Tableau, types of sorting, filtering in Tableau, Types of filters
• Filtering the order of operations

Hands-on Exercise:

Use the data set by date/dimensions/measures to add a filter, Use an interactive filter to view the data, Customize/remove filters to view the result

7.6 Organizing Data and Visual Analytics

• Using formatting pane 
• Formatting data using labels and tooltips
• Edit axes and annotations
• K-means cluster analysis
• Trend and reference lines
• Visual analytics in Tableau

Hands-on Exercise:

Apply labels and tooltips to graphs, annotations, edit axes’ attributes, set the reference line, perform k-means cluster analysis on the given dataset

7.7 Working with Mapping

• Working on coordinate points
• Plotting longitude and latitude
• Editing unrecognized locations
• Customizing geocoding, polygon maps, WMS: web mapping services
• Working on the background image, including add image
• Plotting points on images and generating coordinates from them
• Map visualization, custom territories, map box, WMS map
• Create map projects in Tableau
• Creating dual axes maps, and editing locations

Hands-on Exercise:

Plot longitude and latitude on a geo map, edit locations on the geo map, custom geocoding, use images of the map and plot points, find coordinates, create a polygon map, use WMS

7.8 Working with Calculations and Expressions

• Calculation syntax and functions in Tableau
• Various types of calculations
• LOD expressions, including concept and syntax
• Aggregation and replication with LOD expressions
• Nested LOD expressions
• Levels of details
• Quick table calculations
• The creation of calculated fields
• Predefined calculations
• How to validate

7.9 Working with Parameters

• Creating parameters
• Parameters in calculations
• Using parameters with filters
• Column selection parameters
• Chart selection parameters
• Parameters in the filter session
• Parameters in calculated fields
• Parameters in the reference line

Hands-on Exercise:

Creating new parameters to apply on a filter, passing parameters to filters to select columns, passing parameters to filters to select charts

7.10 Charts and Graphs

• Dual axes graph
• Histograms, single and dual axes, box plot
• Charts
• Maps
• Market basket analysis (MBA)
• Using show me, text table, and highlighted table

Hands-on Exercise:

Plot a histogram, tree map, heat map, funnel chart, and more using the given dataset, perform market basket analysis (MBA) on the same dataset

7.11 Dashboards and Stories

• What is a dashboard?
• Building and formatting a dashboard 
• Best practices for making dashboards 
• Creating stories
• Adding annotations 
• Tableau joins, Types of joins, Tableau field types
• Saving as well as a publishing data source

Hands-on Exercise:

Create a Tableau dashboard view, include legends, objects, and filters, make the dashboard interactive, use visual effects, annotations, and descriptions to create and edit a story

7.12 Tableau Prep

• Introduction to Tableau Prep
• Getting deeper insights into the data with visualizations
• Making data preparation simpler and accessible
• Integrating Tableau Prep with Tableau analytical workflow
• Data preparation to analysis with Tableau Prep

8.1 Introduction to MS Excel & Data Extraction
8.2 Referencing in formulas
8.3 Name range
8.4 Logical functions
8.5 Conditional formatting
8.6 Advanced-level validation
8.7 Important formulas in Excel
8.8 Dynamic table
8.9 Data sorting, filtering
8.10 Chart creation techniques
8.11 Pivot tables in Excel
8.12 Data and file security
8.13 VBA Macros
8.14 Best practices of dashboards visualization
8.15 Creating dashboards
8.16 Creation of interactive components

9.1 Introduction to SQL

• Various types of databases
• Structured Query Language
• Distinction between client-server and file server databases
• Understanding SQL Server Management Studio
• SQL Table basics
• Data types and functions
• Transaction-SQL
• Authentication for Windows
• Data control language
• Identification of keywords in T-SQL

9.2 Database Normalization and Entity Relationship Model

• Data anomalies
• What is normalization?
• Types of normalization forms
• Entity-relationship model

9.3 SQL Operators

• Introduction to relational databases
• Fundamental concepts of relational rows, tables, and columns
• Several operators (such as logical and relational), constraints, domains, indexes, stored procedures, primary and foreign keys
• Understanding group functions, the unique key

9.4 Working with SQL: Join, Tables, and Variables

• Advanced concepts of SQL tables
• SQL functions
• Operators & queries
• Table creation
• Data retrieval from tables
• Combining rows from tables 
• Deploying operators 
• Temporary table creation
• Set operator rules
• Table variables

9.5 Deep Dive into SQL Functions

• SQL functions 
• Scalar and aggregate functions
• Inline SQL functions
• General and duplicate functions

9.6 Working with Subqueries

• SQL subqueries and rules
• Statements and operators with which subqueries can be used
• Modify subqueries
• Types of subqueries
• Methods to create and view subqueries

9.7 SQL Views, Functions, and Stored Procedures

• Learning SQL views
• Methods of working with views
• Stored procedures and their key benefits

You will be working on multiple projects on different domains like retail, finance, banking and learn how Machine Learning is used to solve todays world problems.

Substantiate your learning experience and Business Analysis skills via this practical, industry-based capstone project based on our course and showcase your skills in the field of Product Management and Business Analysis.