Learn how to use analytics to improve the performance of your organization. In this 2-day course, you will learn how to analyze data, build models and communicate results to create business value.
The course is designed for managers and decision makers who want to use analytics to improve the performance of their organizations. Anyone with a degree in Science, Engineering or Business Administration can attend this course.
You may belong to one of the following categories:
Manager who wants to get an orientation of what can be achieved through analytics. Using the experience from the course you can begin build analytics capabilities in your organization.
Decision maker or specialist who is going to use business analytics in your own work.
The course will make you familiar with a standard flow of steps to analyze data. The course will help you to analyze data using software tools, such as Microsoft Excel and Rattle (R package). Using a case-based approach with authentic data you will learn how to approach problems where you have plenty of data and you need to extract the information you need to make fact-based decisions that create value for your organization.
"Our goal is that you will get familiar with practical tools for analyzing data using various machine learning algorithms. You will learn how to use Excel and Rattle (R package) to extract information from data. After the course you will be able to tackle own analytics tasks in your organization."
Professor Dinesh Kumar, Indian Institute of Management Bangalore, India
This is an interactive course and you will make calculations on your laptop using Excel and the Rattle (R package) open-source statistical software package.
About the course
Business Analytics is an integration of science, technology and processes that can be used to analyze data to improve business performance through fact-based decision making. Business analytics and business intelligence create capabilities for companies to compete in the market effectively.
Analytics is emerging as a competitive strategy across many sectors of business that sets apart high performing companies.
- What is the right price for a product/service?
- Which products should be recommended to an existing customer?
- What will be the demand for a product?
- How to identify the most profitable customers
- How to improve business processes
- How to gain insights about products and services using the social media data
Finding right answers to these questions can be challenging yet rewarding. Predictive analytics aims to predict the probability of occurrence of a future event such as customer churn, loan defaults, and stock market fluctuations – leading to effective business management.
The primary objective of this course is to help you understand how various companies are using analytics to analyze real-life business problems such as prediction, classification, discrete choice problems and optimization problems.
Three weeks before the course, you will receive background articles, data sets and an assignment to allow you to get prepared for the course sessions. You will also get instructions of how to prepare your laptop for the course.
DAY 1 – INTRODUCTION TO DATA-DRIVEN DECISION MAKING USING PREDICTIVE ANALYTICS
On Day 1, we will introduce the emergence of business analytics using examples from organizations such as Amazon, Capital One, Netflix, Procter and Gamble, Target and Walmart. These companies are using Analytics to improve their business performance.
The process of data-driven decision making requires managers to know how to summarize, analyze, interpret and communicate data using data visualization techniques to facilitate decision making. We will focus on predictive analytics using supervised learning algorithms.
DAY 2 – ANALYTICS TO CLASSIFY EVENTS AND OPTIMIZE PROCESSES
Classification problems such as credit risk, customer churn and employee attrition are encountered by many companies. The primary objective of this day is to understand how machine learning algorithms, such as supervised learning and reinforcement learning, can be used to analyze real-life business problems such as prediction, classification and discrete-choice problems. The focus will be case-based, practical problem solving using predictive analytics techniques to interpret model outputs.
We will discuss how unstructured data such as social media data and machine generated data can be analyzed using analytics for gaining insights.
Full refund of educational program/course fees will be made for reservations cancelled no later than eight weeks prior to the start of the program/course. Later cancellations incur a cancellation fee as follows:
- 2 weeks or less prior to program start 100% of the educational program/course fee
- 2-4 weeks prior to program start 50% of the educational program/course fee
- 4-8 weeks prior to program start 25% of the educational program/course fee, for educations in the Shipping area: 0% of the educational program/course fee
We are always willing to consider a colleague as a substitute for the original applicant. Cancellation and postponement must be made in writing. Cancellation of accommodation is subject to the cancellation policies of the hotels.