XLRI Emeritus
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OVERVIEW

It's the era of big data. Companies around the world are eager to expand their data science expertise and advance rapidly by leveraging the power of data analytics. As a business leader, you want to achieve growth and drive business efficiency by analysing data and providing coherent insights. XLRI VIL's Business Analytics for Managers programme responds to this growing need.

This comprehensive 7-month programme, created in collaboration with Eruditus Executive Education, provides insights and best practices of data analytics and artificial intelligence as a strategic lever to make data-driven business decisions.

Joining this programme has proven beneficial for professionals across industries, interested in utilising analytics to help apply organisational data analytics for effective real-time business decision-making.

KEY BENEFITS

  • 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

CERTIFICATE

Business Analytics for Managers - Certificate Click to view certificate

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  • STARTS ON

    27 December 2020

  • DURATION

    7 months
    (Live Online Sessions - 3 Hours/ week
    Sunday 3:30 PM to 6:30 PM)

  • PROGRAMME FEE

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

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Who is this Programme For

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.


Familiarity with and willingness to learn the minimal 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.


  • ELIGIBILITY - Graduate in any discipline with at least 6 years of work experience

Programme Modules & Faculty

syllabus

  • 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, example:
    • 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 of 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
  • The art of storytelling 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
  • When is investment in data science justified and when not
  • Identifying and quantifying benefits of a data science for an organisation
  • Estimating investments in a data science project
  • Estimating return on investment in a data science project
  • 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
  • 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
  • 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 a live data set from their own organisation.

PROGRAMME DIRECTORS

Dr Abhishek Chakraborty
Dr Abhishek Chakraborty

Production, Operations & 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.

Dr Supriya Kumar De
Dr Supriya Kumar De

Production, Operations & Decision Sciences

Dr Supriya Kumar De has an 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
27 December 2020 7 Months Live Online Sessions - 3 Hours/ week
Sunday 3:30 PM to 6:30 PM		 INR 1,52,500 + GST (inclusive of application fee)
Deadline Application Fee
Round 1 Oct 15, 2020 INR 2,500 + GST
Round 2 Nov 16, 2020 INR 2,500 + GST
Round 3 Dec 24, 2020 INR 2,500 + GST
Remarks Instalment Amount
Instalment 1 At the time of application INR 24,500 + GST
Instalment 2 Dec 26, 2020 INR 64,000 + GST
Instalment 3 Mar 15, 2021 INR 64,000 + GST

Student Loan Details

Loan Amount Available Tenure (months) EMI
INR 1,68,150 36 INR 6,217

Note:

  • 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
    Eduvanz: 12/24/36/48
Please visit Students Loans and Financing for details on how to avail a student loan.

SYSTEM REQUIREMENTS

SYSTEM REQUIREMENTS TO ATTEND A LIVE ONLINE CLASSES
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.