Module 1: Introduction to Business Analytics
• What is Analytics?
• Applications of Analytics: Sample Case studies across industries
• Types of Analytics: Descriptive, Predictive, Prescriptive
• Difference between business analytics and business intelligence
• RPopular tools
Module 2: Data Wrangling using Excel
• Data Manipulation ( Basic functions, If else, date functions, table, filter, Sort etc.)
• Data Cleaning ( Concatenate, left, right, mid, trim, uppercase, lowercase, find, search, Len, replace,
and, or, char, substitute, conditional formatting etc.)
• Data Mapping ( V lookup, H lookup, Index Match, offset, named ranges, dropdowns, etc.)
• Case Study
Module 3: Exploratory Data Analysis using Excel
• Aggregating data using Pivot, Calculated Fields
• Data Visualization
• Slicers
• Case Study
Module 4: Statistics with Excel
• Basic Statistics, Introduction to Measures of Central Tendency, Types of data & variables,
Probability, Distribution Types, Confidence Interval
• Descriptive Statistics
• Sample, Population, Measures of central tendency
• Hypothesis Testing
• Test of proportion, Test of means, T testing, Type 1 and type 2 error
• Correlation and Covariance
• Case Study: Decision making using advanced excel
Module 5: Data Modelling using Excel
• Linear Regression
• Multiple Linear Regression
• Time Series Forecasting
• Case study: Modelling using Excel
Module 6: Data Visualization
• Basic Charts and Reports
• Dimensions and Measures
• Dashboard design and techniques
• Storyboarding
• Case study: Dashboard designing
Course project
Retail Store chain transformation
Business Intelligence (BI) tools are adopted by more and more companies in the current environment that requires companies
to operate as efficiently as possible. The case study investigates a BI adoption in a retail chain. Based on qualitative research methods, it analyses the Business
Intelligence life cycle; it evaluates factors impacting the adoption from the Diffusion of Innovations perspective.
The present study tried to help the upcoming retail store to solve the problem of transformation from traditional way of
doing business to the digital way. Automate the data collection where available and create integrated set of dashboards that
will free up time for the business analysts to get away from some report production time and spend more time on analysis that
will greatly benefit the business in the long-term.
