Advanced Business Analytics

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Overview

Decision-Making undoubtedly is the crux of any managerial activity. Thus any tool or technique that facilitates decision-making acquires paramount importance. Data Analytics and Data Mining over a period of time have acquired this stature and form the pillars of Business Analytics. Primary reason for this is the fact that every aspect of corporate working, across hierarchy to profiles, involves numbers. Thus the ability to fathom numbers and the skill to make numbers speak by itself becomes an absolutely important skill set. Another reason for managers to acquire mastery over quantitative techniques is that it converts decision making from an art to science.

While there is no doubting the role of experience in facilitating decision making, expertise in quantitative techniques enables minimizing the risk involved in decision making by clubbing experience with appropriate tools and techniques. Having stated the importance of quantitative techniques, the unfortunate scenario is that very few managers actually use even the common basic tools and techniques for analyzing data. While we are entering a world of Big Data, and Corporates are waking up to the Competitive Advantage data brings, the analysis of the same is far from desired. This course shall enable participants to learn the basic concepts and introduce contemporary tools and techniques in analytics in a purely practical way that shall enable regular usage.

Every aspect of corporate functioning across hierarchies and domains involves dealing with numbers and making decisions based on them. It is thus imperative that number literacy and ability to fathom data, makes business sense out of them and use them as guiding light for decision making, be a strong weapon in the armour of any executive who intends to scale corporate glory.

The ability to take fact-based, accurate and profitable decisions is imperative to achieve competitive advantage in business at all point in times. This program on Advanced Business Analytics will thus equip the participants with analytical tools and prepare them for corporate roles across industries. The course is suitable for professionals working in analytics to enhance their knowledge as well as for those with analytical aptitude and would like to start new career in analytics. The core strength of this course is a thorough and comprehensive grounding into theoretical and logical understanding of core concepts of statistics.

The course shall help participants to identify, evaluate, and capture business analytic opportunities for value creation. This course will encourage the participants to develop an organizational culture of “passion to manage with facts“. Specifically, they would be able to generate consistent results, anticipate shift in trends and take tactical decisions which would better business results.

Contact Us

Prof. Bhaskar Sinha
Programme Coordinator
Rizvi Institute of Management Studies & Research
Email: bhaskarsinha@rmi.rizvi.edu.in
Mob.: 7045641699
Dr. Kalim Khan
Director
Rizvi Institute of Management Studies & Research
Email: kalim@rmi.rizvi.edu.in
Name of the Institute : Rizvi Institute of Management Studies & Research
Address : New Rizvi Education Complex, Off. Carter Road, Bandra (W), Mumbai – 400 050
Landline : +91 22 26042180 | +91 22 26049710 | +91 22 26044068
Website : www.rmi.rizvi.edu.in
Email ID : businessanalytics@rmi.rizvi.edu.in
Twitter : @RizviManagement

Course Details

Course Deliverables

On completion of the course the participants should be able to:
  • appreciate the emergence of business analytics as a competitive strategy.
  • appreciate that the collection and statistical analysis of data improves business decisions and reduces the risk of implementing solutions that waste resources and effort.
  • understand the foundations of data science; the role of descriptive, diagnostic, predictive and prescriptive analytics in firms.
  • study the art of making the data speak through data visualization.
  • select and deploy the correct statistical method for a given data analysis requirement. In particular, develop expertise in describing data, process management, hypothesis testing and model building.
  • analyze data using statistical and data mining techniques and understand relationships between the underlying business processes of an organization.
  • achieve a practical level of competence in building statistical models that suit business applications.
  • recognise, develop and distinguish between models for cross sectional analysis at a single point in time and models for time series analysis at multiple points in time.
  • increase your capability as a manager to ‘think statistically’ using data and use this capability to support your business intuition.
  • use various packages and softwares that facilitate application of statistical techniques.

Course Advantages

The course shall :
  • give a thorough grounding on theoretical statistical concepts.
  • provide detailed explanation on the rational and application of almost all contemporary statistical and data mining techniques.
  • cover concepts using case studies across spectrum of industries.
  • use various packages and softwares so as to help participants acquire skill sets to use the same.
  • very strongly integrate MS-Excel as a part of the teaching pedagogy.
  • extensively and exhaustively teach tools like SAS, SPSS, R and Tableau.
  • have facilitators who are real time practitioners thus bringing to the class real time applications.
  • be extensively covered and taught through class room sessions only.

Course Structure

The course shall :
  • Be covered using classroom teaching only
  • Be spread over 9 months
  • Be spread over 50 days
  • Have 300 hours of teaching
  • Have sessions only on weekends
  • Each day shall have two sessions of 3 hours each
  • The sessions will be held from 10.00 am – 5.00 pm

Course Eligibility

Applicants interested in the course must :
  • Be at least a graduate from a recognized University
  • Have minimum two years of work experience
  • Comply with the admission procedure as stipulated

Course Essentials

The course mandates :
  • Participants must carry laptops for every session
  • Minimum attendance of 80% to be eligible for the certificate
  • Adhere to the disciplinary norms as laid by the Institute
  • Pay fees as per schedule

Course Completion

Participants shall successfully complete the course on the fulfillment of the following conditions:
  • Mandatory attendance of 80%
  • Completion of all assignments as and when given in the course
  • Appear for an end of the course assessment
  • Score minimum 50% of marks in the end of the course assessment

Course Reward

Participants who successfully complete the programme shall be awarded “Certificate in Advanced Business Analytics” by Rizvi Institute of Management Studies & Research.

Admission and Fees

Interested participants have to fill in the admission form available online. The online form is available on the Institute website www.rmi.rizvi.edu.in. Applicants are requested to download the form and mail the duly filled in form to businessanalytics@rmi.rizvi.edu.in. Forms shall be available online for download and submission from Tuesday 5th April, 2016 to Friday 15th July, 2016.

The institute shall conduct a telephonic interview of the applicants who submit the form. Applicants shall be admitted basis the profile and the telephonic interview. Admitted candidates shall be informed by mail on the email id registered in the form.

The course shall commence from Saturday 6th August, 2016 with the Orientation Programme.

COURSE FEES AND PAYMENT

    • The course fees shall be Rs. 3,00,000/- inclusive of all taxes. The fees can be paid either by
      • Cheque favouring “Rizvi Institute of Management Studies & Research”
      • Through RTGS, the details of which are as below:
        • Name of the Beneficiary : Rizvi Institute of Management Studies & Research
        • Name of the Bank: Abhyudaya Cooperative Bank Ltd.
        • Account No.: 028021100000433
        • Type of Account : Current Account
        • IFSC : ABHY0065028
        • Branch : Sherly Rajan Road, Bandra West
    • The payment schedule is as below:
      • Rs. 1,50,000/- on admission
      • Rs. 1,50,000/- after three months of admission
    • The alumnus of Rizvi Institute of Management Studies & Research shall be given special preference in this course and can avail the course at Rs. 2,50,000/- per participant.
    • In case of corporates sponsoring candidates, the following shall be the fee structure:
Sr. No.
No. of Participants per organisation
Fee Amount per Participant
1.
3-5
Rs. 2,50,000/-
2.
More than 5
Rs. 2,00,000/-

Facilitators

1. Dr. Kalim Khan
Kalim KhanDr. Kalim Khan is a truly multi faceted personality and to say that he adorns each hat with elan and exceptional commitment and credibility would be an understatement. An academician by heart, a management consultant with an eye for detail, an enriching and entertaining trainer, and an author with a penchant for exhibiting thought leadership, Dr. Kalim Khan plays all these roles with class, exuberance and style.

Dr. Kalim Khan is the Director of Rizvi Institute of Management Studies & Research and carries the repute of being amongst the most prominent trainers on analytics in industry as well as academia. A Ph.D. in quantitative techniques, his forte lies in simplifying the most complex concepts of statistics. He has been training and consulting on data analytics and allied areas with some of the best brands. He gets to the team a combination of conceptual clarity and complex applications.

2. Sanjay Gupta
Sanjay GuptaSanjay Gupta is an Assistant Professor at Rizvi Institute of Management Studies & Research. He specializes in Information Technology. Sanjay has an expertise in translating business requirements into structured systems specifications, analyze customer requirements and develop Information Technology solutions. He is proficient in various software technologies involving client server and web based development.

Sanjay Gupta has been in the training profession for more than 20 years focusing on the target groups ranging from fresher to senior technical professionals. Sanjay conducts trainings on various technical subjects in Information Technology. He holds a B.Tech. from IIT-B and is an MBA in Information Systems. He has been regularly conducting training programmes in Programming Languages, Data Base Management and Big Data.

3. Bhaskar Sinha
Bhaskar SinhaBhaskar Sinha has held various academic and corporate positions in a career spanning 12 years. He has substantial experience in application of academic research across industries, designing industry-oriented courseware, organizing academia-industry interfaced guest lectures and training. Bhaskar specializes in the area of Firm Financing Decisions, Financial Intermediation, Market Microstructure, Applied Econometrics Research with a distinct goal to creating a paradigm shift in the strategy and practice of management professionals.

Bhaskar Sinha graduated with Electrical Engineering from Nagpur University with distinction and has a Post Graduate Diploma in Management with Finance & Marketing (dual specialization). Furthermore, he completed his management teachers program (MTP) specializing in Finance. He was awarded Full Scholarship from ICFAI University for the Visiting Scholars Program to Department of Finance, M. J. Whitman School of Management, Syracuse University, New York.

4. Rajesh Jakhotia
E-Brochure - ABA.cdrRajesh is an Analytic Professional with over 15 years of experience. He started his career as a Software Engineer at Aptech Ltd. and then moved out into the Analytics field. He worked with Fractal Analytics, Adventity Global Services, Hansa Cequity in various roles. He last worked with Positive Integers as Director – Analytics before moving full-time in his own founded training company, K2 Analytics.

He has a deep domain expertise in the Retail Banking space. In his career he has worked with HDFC Bank, Axis Bank, Kotak Mahindra Bank. He also worked with some of the big NBFCs in India and financial services clients in Middle East and APAC regions. He was heading the Retail Banking Analytics practice in Fractal and Adventity Global Services. He has also worked with clients in Retail, Telecom and Hospitality sectors. Over his career he has delivered 100+ analytical models and solutions for various companies.

5. Mohd. Osaid Koti
OsaidKotiMohammed Osaid Koti, is associated with Rizvi Institute of Management Studies & Research as Assistant Professor and Course Coordinator for the Post Graduate Programme for more than six years. Mohd. Osaid Koti (Green Belt Six Sigma certified) specializes in the applications of quantitative and statistical techniques to business decision making which include decision analysis, optimization models, simulation, and data mining. He is conversant with spreadsheet modeling and usage of data visualization techniques for report presentations.

He is an accomplished corporate trainer and has successfully trained participants of companies such as Acumen Business Consultancy, Sethia Group, The Wadhwa Group, Shree Shubham Logistics, Rubberwala Builders and also several Non Profit Organisations.

6. Jamil Saudagar
Jamil SaudagarJamil Saudagar is an accomplished trainer in MS Excel and Financial Modelling. He provides consultancy and advisory services to corporate clients on MS Excel, Visual Studio, SQL Server and Oracle for business applications. He has a corporate work experience of 14 years, working across a wide spectrum of Banking and Financial Services verticals. His diverse exposure includes: Corporate Banking, Capital Markets and Fixed Income securities.

Jamil has a passion for writing computer programs that automate business processes and speed up data analysis. His application of various tools, which enhance efficiency and process productivity, has been adopted by his employers – Morgan Stanley, IL&FS and Citigroup.

7. Industry Experts from respective domains for application of Analytics across sectors.

Curriculum

1. Introduction to Business Analytics
   • Business Analytics – An Overview
   • Types of Analytics
      a. Descriptive
      b. Diagnostic
      c. Predictive
      d. Prescriptive
   • Framework of Analytics

2. Application of Business Analytics – An Overview

3. Descriptive Statistics
   • Business Statistics – An Overview
   • Scaling Techniques
   • Frequency Distribution
   • Measure of Central Tendencies
   • Measure of Dispersion

4. Visualising and Exploring Data
   • Graphs, Bar, Charts, Tables and Diagrams
   • Pivot Tables

5. Probability and Probability Distribution
   • Probability – Overview and Concepts
   • Types of Probability
   • Basic Analysis using Probability
   • Probability Distribution
      a. Discrete – Binomial and Poisson with Application
      b. Continuous – Normal Distribution

6. Sampling and Sampling Distribution
   • Sampling – Overview and Concepts
   • Critical understanding of Sampling
   • Sampling Theory
   • Sample Size Estimations
   • Sampling Distribution

7. Inferential Statistics
   • Testing of Hypothesis – Overview and Concepts
   • Testing of Hypothesis – Parametric Test
      a. T-test
      b. Z-test
      c. ANOVA
   • Testing of Hypothesis – Non Parametric Test
      a. Sign Test
      b. Chi Square
      c. Wilcoxon Test
      d. K-S Test
      e. Mann-Whitney U Test

8. Predictive Analysis
   • Forecasting Techniques
   • Time Series Analysis
   • Regression Analysis
      a. Simple Linear Regression
      b. Multiple Linear Regression
      c. Non Linear Regression
   • Probit and Logit Regression

  9. Multivariate Analysis
   • MANOVA
   • Factor Analysis
   • Cluster Analysis
   • Conjoint Analysis
   • Correspondence Analysis
   • Multi Dimensional Scaling

10. Data Mining Techniques
   • Data Mining – Overview and Concepts
   • Types of Data Mining
      a. Supervised Learning
         • Classification
         • Prediction
      b. Unsupervised Learning
   • Affinity Group / Association Rule
   • Clustering
   • Description and Visualisation
   • Structured Techniques in Data Mining
      a. K Nearest Neighbour
      b. Naïve Bayes
      c. Decision Trees
      d. CART
      e. CHAID
      f. Discriminant Analysis
      g. Logistic Regression
      h. Neural Networks
      i. Genetic Algorithms
      j. Support Vector Machine
      k. Market Basket Analysis
   • Unstructured Techniques in Data Mining

11. Data Visualisation
   • Data Visualisation – Overview and Concepts
   • Story Telling using Tableau
   • Dashboard for Analysis

12. Optimisation Techniques
   • Optimisation – Overview and Concepts
   • Linear Programming
   • Variants of Linear Programming

13. Applications of Data Science in select domains
   • Retail
   • Banking
   • Telecom
   • Health Care
   • FMCG
   • Digital Marketing

14. Introduction to Big Data
   • Big Data – Overview and Concepts
   • Big Data – Technology

15. Exhaustive Coverage of following tools with applications
   • R
   • SPSS
   • SAS
   • Tableau

Schedule

Day and Date Topic Faculty
Sat, 6 Aug 16 Orientation Programme
1 Sat, 13 Aug 16 Business Analytics – An Overview Dr. Kalim Khan
2 Sun, 14 Aug 16 Business Analytics – Applied Industry Expert
3 Sat, 20 Aug 16 Descriptive Statistics Dr. Kalim Khan
4 Sat, 27 Aug 16 Introduction to R Rajesh Jakhotia
5 Sun, 28 Aug 16 Business Analytics – Applied Industry Expert
6 Sat, 3 Sept 16 Analytics using R Rajesh Jakhotia
7 Sun, 4 Sept 16 Visualising and Exploring Data using MS Excel Jamil Saudagar
8 Sat, 10 Sept 16 Analytics using R Rajesh Jakhotia
9 Sun, 11 Sept 16 Visualising and Exploring Data using MS Excel Jamil Saudagar
10 Sat, 17 Sept 16 Probability Distribution Bhaskar Sinha
11 Sun, 18 Sept 16 Probability Distribution Bhaskar Sinha
12 Sat, 1 Oct 16 Analytics using R Rajesh Jakhotia
13 Sun, 2 Oct 16 Sampling and Sampling Distribution Dr. Kalim Khan
14 Sat, 8 Oct 16 Inferential Statistics – Concepts Dr. Kalim Khan
15 Sun, 9 Oct 16 Inferential Statistics – Applications Dr. Kalim Khan
16 Sat, 22 Oct 16 Inferential Statistics using tools Dr. Kalim Khan
17 Sun, 23 Oct 16 Predictive Analytics – Forecasting Bhaskar Sinha
18 Sat, 12 Nov 16 Predictive Analytics – Time Series Bhaskar Sinha
19 Sun, 13 Nov 16 Predictive Analytics – Regression Dr. Kalim Khan
20 Sat, 19 Nov 16 Predictive Analytics – Regression Dr. Kalim Khan
21 Sun, 20 Nov 16 Predictive Analytics – Regression Dr. Kalim Khan
22 Sat, 26 Nov 16 Analytics using R Rajesh Jakhotia
23 Sun, 27 Nov 16 Multivariate Analytics Dr. Kalim Khan
24 Sat, 3 Dec 16 Data Mining Techniques Rajesh Jakhotia
25 Sun, 4 Dec 16 Multivariate Analytics Dr. Kalim Khan
26 Sat, 10 Dec 16 Data Mining Techniques Rajesh Jakhotia
27 Sun, 11 Dec 16 Multivariate Analytics Dr. Kalim Khan
28 Sat, 17 Dec 16 Data Mining Techniques Rajesh Jakhotia
29 Sun, 18 Dec 16 Data Visualisation – Tableau Raghav Shyam
30 Sat, 14 Jan 17 Data Mining Techniques Rajesh Jakhotia
31 Sun, 15 Jan 17 Data Visualisation – Tableau Raghav Shyam
32 Sat, 21 Jan 17 Data Mining Techniques Rajesh Jakhotia
33 Sun, 29 Jan 17 Optimisation Techniques – Linear Programming Dr. Kalim Khan
34 Sat, 11 Feb 17 Data Mining Techniques Rajesh Jakhotia
35 Sun, 12 Feb 17 Optimisation Techniques – Linear Programming Mohd. Osaid Koti
36 Sun, 19 Feb 17 Optimisation Techniques – Non Linear Programming Bhaskar Sinha
37 Sat, 25 Feb 17 Data Mining Techniques Rajesh Jakhotia
38 Sun, 26 Feb 17 Data Mining Techniques Anitha Jayaraman
39 Sat, 4 Mar 17 Data Mining Techniques Rajesh Jakhotia
40 Sun, 5 Mar 17 Application of Data Science Industry Expert
41 Sat, 11 Mar 17 Data Mining Techniques Rajesh Jakhotia
42 Sun, 12 Mar 17 Introduction to Big Data Sanjay Gupta
43 Sat, 18 Mar 17 Data Mining Techniques Rajesh Jakhotia
44 Sun, 19 Mar 17 Introduction to Big Data Sanjay Gupta
45 Sat, 25 Mar 17 Introduction to SAS Rajesh Jakhotia
46 Sun, 26 Mar 17 Application of Data Science Industry Expert
47 Sat, 1 Apr 17 Introduction to SAS Rajesh Jakhotia
48 Sun, 2 Apr 17 Application of Data Science Industry Expert
49 Sat, 8 Apr 17 Application of Data Science Industry Expert
50 Sun, 9 Apr 17 Application of Data Science Industry Expert
Sat, 15 Apr 17 End Term Assessment
Sun, 16 Apr 17 Valedictory Function
Rizvi Institute of Management Studies & Research