Business Analytics and Big Data Analytics

What is BI?

Business intelligence (BI) is a broad category of applications and technologies for gathering, storing, analyzing, and providing access to data to help enterprise users make better business decisions. BI applications include the activities of decision support systems, query and reporting, online analytical processing (OLAP), statistical analysis, forecasting, and data mining.

Thus, BI has three components:

• Requirements: Information System Model describing requirements
• Storage: Data Warehouse and Data Mart describing storage of data
• Business Analytics: Analytical Methods like Reports, OLAP, Business Forecasting, Data Mining to analyze data

 What is Business Analytics?

Business analytics is how organizations interpret data in order to make better business decisions and to optimize business processes. Analytical activities are expanding fast in businesses, government agencies and not-for-profit organizations.

Analytics involve use of data, statistical and quantitative analysis, explanatory and predictive modeling, and fact-based decision-making. Analytics may be used as input for human decisions; however, in business there are also examples of fully automated decisions that require minimal human intervention.

Decisions based on data provide a competitive edge to today’s business. Taking the cognizance of the fact that this field is growing very rapidly, many large domestic IT consultancy and service companies have already established a separate “BI” practice.

 Objective of the Workshop

This program is designed to develop a thorough understanding of following Data Analysis Techniques:

• OLAP
• Business Forecasting
  • Time Series Forecasting
  • Causal Techniques (Linear Regression)
• Data Mining (including Text Mining, Sentiment Analysis)

 Target audience 

Business executives (Marketing, Finance, Operations, HR, IT, etc.) preferably with a few years of experience. IT knowledge is not required.

 Takeaway

At the end of the workshop participants will be able to understand the concepts and how to use certain Data Analysis Techniques. Armed with the concepts, demonstration and hands-on on various tools, participants will be able to use various Data Analysis Techniques for Decision Support

 Pedagogy

The workshops will be business case centric, namely, will concentrate on the issues involved in the business, and then discuss the concepts and Data Analysis techniques that will address those issues. The workshop will be an optimal mix of classroom discussions, group discussions amongst the participants, demonstration and hands-on.

The program will have interactive sessions, including:

• Presentation on concepts
• Cases discussion on application
• Paper exercises / demonstration using tool
• Hands-on

 Tools:  Excel, R, Tableau

Faculty: Mr. Sunil Lakdawala, Mr. Niteen Bhagwat, Mr. R Radhakrishnan.

Business Analytics and Big Data Analytics

                             Learning Plan for a Two-Day Workshop

DAY 1

Session	Topic
1	Introduction to Business Analytics and Big Data Analytics ·    Objective ·    Normal and Big Data ·    Requirements ·    Data Warehouse ·    Data Analytics ·    Big Data Analytics ·    Business Analytics ·    Metrics ·    Maturity Models ·    Key Roles
2	OLAP Analysis – Case: Sales Analysis Dimension Modeling – Facts and Dimension What is OLAP Analysis Drill / Slice & Dice Demonstration & hands-on: Case – Sales Analysis
3 & 4	Business Forecasting Overview Why Forecasting Categories of Forecasting Qualitative Time Series Causal Time Series Components Trend Seasonal Cyclic Irregular Evaluating Methods Time Series Techniques for Forecasting (Demonstration and Hands-On using various cases) Naïve Moving Average Exponential Smoothing

 

DAY 2

Session	Topic
1	Simple Linear Regression What is Linear Regression Demonstration & Hands-On: Various Cases
2	Multiple Linear Regression What is Multiple Linear Regression Demonstration & Hands-On: Various Cases
3	Data Mining Techniques I – Classification using Decision Tree – Case: Whom to give car loan? Methodology for Supervised technique Applications Hands-on How to evaluate classification method
4.	Data Mining Techniques II – Market Basket Analysis –  Case: Departmental Store What is Market Basket Analysis? Hands-on Applications
5	Data Mining Concepts, Techniques, Applications: Big Data Analytics Text Mining Introduction to Sentiment Analysis, Social Network Analysis, WEB Mining

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