Organisations face a new challenge today - how to effectively navigate the maze of large amounts of data for effective decision-making. This is where business analytics and data scientists come to the fore. With the growing number of data scientists and organisational investment in analytics initiatives, it has become an imperative for managers to manage teams of data analytics and make effective investments in analytics initiatives to help data-driven organisations make effective decisions.

The Business Analytics for Managers programme is designed to equip managers with an understanding of basic principles of data analytics and artificial intelligence to aid them in driving organisational initiatives for effective analytics. To be in a position to do this, managers of analytics teams need to be in a position to understand the language of data scientists for asking the right questions of them and applying the results of organisational data analytics exercises to aid effective business decision-making.

Enrol in the programme to equip yourself with the right tools to decipher, structure, and utilise data to make future-ready business decisions.


  • Gain a robust understanding of the tools and techniques used in analytics, data science and artificial intelligence
  • Take the lead in building a data-driven organisation and facilitate its growth
  • Develop expertise in managing teams adept in data analytics
  • Evaluate investment decisions for analytics projects in your organisation
  • Identify areas in your organisation where business analytics can be productively and seamlessly applied
  • Understand data privacy and ethical concerns around data management, along with strategies on how to mitigate them


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    28 June 2020


    7 months
    (Live Online & In-class Sessions - 1 visit – 3 days at XLRI campus, Jamshedpur)


    INR 1,52,500 + GST (inclusive of application fee)

Who is this Programme For

Transform the latent potential of data into revenue-making insights and valuable business decisions through the Business Analytics for Managers programme from XLRI VIL. The programme is specially designed for professionals across industries, looking to utilise analytics help them make and enrich real-time and data-driven business decisions. This programme will benefit Managers, Senior Managers, Executives, Entrepreneurs and Consultants from a variety of backgrounds who:

Seek to drive effective data-driven decision-making for their organisations or clients

Seek to structure, decipher, and interpret big data for deriving high quality and nuanced data-driven insights

Drive and manage organisational initiatives towards becoming a data-driven organisation

Prerequisite – Data Analytics is essentially the application of specialised statistical and mathematical techniques for obtaining better quality insights into the vast amounts of data available in today’s world. Hence, this programme necessarily delves into statistical concepts which may not be familiar to most applicants.

While the programme does cover the basic statistical and mathematical concepts required for effective use of data analytics, it is strongly recommended that applicants should display some basic degree of familiarity (not expert knowledge) in statistical concepts such as probability, probability distributions, correlation, and basic regression as these are the foundations for the techniques of analytics.

A bit of familiarity with and willingness to learn the minimalist amount of basic programming would also help in appreciating the mechanics of the tools and techniques of analytics for improved analysis of their results for decision-making.

  • Applicants should be graduates in any discipline with at least 6 years of work experience.

Programme Modules & Faculty


  • Data and data literacy in organisations
  • Types of analytics – descriptive, predictive and prescriptive
  • Use cases of Analytics – An introduction
  • Good and bad Analytics
  • Deriving organisation’s data science objectives from strategic business objectives
  • Building hypothesis for organisational decision-making: use cases from different verticals
  • Limitation of analytics – where intuition still wins!
  • Case Study: Harvard article on “Data Science and Art of Persuasion”
  • Describing and presenting data
  • Applying measures of central tendency in business metrics
  • Probability and its application in business
  • Sampling theories and their application in business
  • Hypothesis testing, use cases in business
  • Analysis of variance, use cases in business
  • Correlation and regression, use cases in business
  • Principal types of algorithms
  • Application of Bivariate and Multiple linear regression models
  • Classification algorithms – concepts and use cases
  • Clustering algorithms – concepts and use cases
  • Design of recommendation systems
  • Modelling approach to decision-making
  • Linear Programming approach to solving a business problem, e.g.
    • a. Make-Buy decision
    • b. Investment decision
    • c. Blending problem
    • d. Production and inventory planning problem
    • e. Multi-period cash flow problem
  • Sensitivity Analysis and Simplex Method
  • Data management and querying
  • Data extraction, transformation and
    loading (ETL) techniques
  • Fundamentals of data warehouse
  • Overview of the technology stack to
    support analytics
  • Scope and benefits of digital media analytics
  • Types of digital media analytics
  • Consumer insights using web and mobile app analytics
  • Social media analytics
  • Overview Text mining and sentiment analysis
  • Online reputation management
  • Understanding Big Data
  • Understanding applications of Big Data
  • Big Data application tools – Hadoop, MapReduce
  • Exploiting Big Data for business decision
  • Examples from Facebook & Google
  • Fundamentals of Deep Learning
  • Deep, Convolution and Recurrent Neural Network – concept
  • Use cases of Deep Learning in different industry verticals
  • Fundaments of Reinforcement Learning
  • Use cases of Reinforcement Learning in industry use cases
  • The art of story-telling with data
  • Data visualisation – concept and application
  • Using self-service data visualisation tools (e.g. Tableau) to generate management reports and dashboards
  • Visualising data using infographics
  • Evaluating an Analytics report
  • Data Science project management methods
    and governance
  • Application of Agile
  • Managing organisational change
  • Developing and managing a data science
    project contract
  • Ethical Concern on data privacy and trust in Analytics
  • Methods to preserve the privacy of sensitive data
  • Legal issues on data privacy
  • Recent case studies
  • New organisation roles and governance for a data-driven organisation
  • Recruiting and retaining data science talent pool
  • Scaling a data team
  • Vendor eco-system for data science services
  • When is an investment in data science
    justified and when not
  • Identifying and quantifying the benefits
    of data science for an organisation
  • Estimating investments in a data science project
  • Estimating return on investment in a
    data science project
  • The participants will be asked to work on a Capstone Project for an industry domain of their preference. It is expected that the participants will work on live data set from their own organisation.


Dr. Abhishek Chakraborty
Dr. Abhishek Chakraborty

Productions, Operations and Decision Sciences

Dr. Chakraborty has an M.Sc. in Applied Mathematics and is a Fellow of IIM Calcutta. He has previously worked with TCS and JDA Software. His research interests include Inventory Management; Supply Chain Coordination; Game Theory in Supply Chain; Operations Research in Sports; Analytics in Supply Chain Management and Forecasting. He has presented award-winning papers in M.Sc. – Applied Mathematics, University of Calcutta.

Dr. Supriya Kumar De
Dr. Supriya Kumar De

Productions, Operations and Decision Sciences and Information Systems

Dr. Supriya Kumar De has a M.Sc. and Ph.D. from IIT Kharagpur. He has worked with IDRBT and XLRI. His research interests include Product Design and Development, Business Intelligence, Data Warehouse and Data and Knowledge Engineering etc.

Programme Fee

Dates Length Location Tuition Fees
June 28, 2020 7 Months Live Online & In-class Sessions - 1 visit – 3 days at XLRI campus, Jamshedpur INR 1,52,500 + GST (inclusive of application fee)
Deadline Application Fee
Round 1 Apr 15, 2020 INR 2,500 + GST
Round 2 May 15, 2020 INR 2,500 + GST
Round 3 Jun 25, 2020 INR 2,500 + GST
Application Deadline Extended
*Accepting Late Applications
Jul 10, 2020* INR 2,500 + GST
Remarks Instalment Amount
Instalment 1 At the time of application INR 24,500 (Programme Fee) + GST
Instalment 2 Jun 30, 2020 INR 64,000 (Programme Fee) + GST
Instalment 3 Sep 10, 2020 INR 64,000 (Programme Fee) + GST

Student Loan Details

Loan Amount Available Tenure (months) EMI
INR 1,42,500 18 INR 10,777


  • The above EMI’s are indicative. The EMI’s offered by each of the loan providers might vary from the above figures, depending upon tenure and loan amount to be disbursed.
  • Other EMI tenures available (Months):
    Propelld: 6/12/18/24/30/36/42/48
Please visit Students Loans and Financing for details on how to avail a student loan.


This programme includes live online classes. To attend a live online class you will need to have a PC/Laptop/Mac with

  • Speakers and microphone: built-in or a USB plug-in or wireless Bluetooth
  • Webcam: built-in or USB plug-in
  • Processor: with Dual Core 2Ghz or higher (i3/i5/i7 or AMD equivalent)
  • RAM: 4 GB or higher
  • OS: Either MacOS 10.7 or higher OR Windows 8 or higher
  • An internet connection: Minimum bandwidth of 3.0 Mbps (up/down)
  • Browser: IE 11+, Edge 12+, Firefox 27+, Chrome 30+
  • Zoom software client installed on your PC/Laptop/Mac

We use the Zoom software application to conduct live online classes. Zoom works on a variety of PCs/Laptops/Mac systems and also on phones and tablets. You can join your live online class from a phone or tablet if it supports the Zoom client. We recommend that you attend classes from a PC/Laptop/Mac.