Data-Driven Business Intelligence

Welcome to the exciting world of data analysis and unlock its power in today's dynamic business landscape. This course offers a comprehensive guide to mastering data analysis, transforming it into more than just a valuable skill. Gain essential knowledge and tools to convert data into actionable insights, drive informed decisions, and fuel business growth. This course is designed for a wide range of individuals, including business professional data analysts, students or simply a curious learner eager to dive into data. This course will give you data-driven decision-making tools to gain a competitive edge. It will enable leveraging advanced technologies and practical tools like MS Excel, and its application to real-world case studies. Upon completing this course, you will: --Develop proficiency in applying Quantitative Analysis methods in business contexts. --Recognize the significance of accurate data for credible results. --Identify the salient aspects of an undertaking managerial assessment context. In addition, you can get a head start on PGDM Online, an AICTE-approved master’s level program. This MOOC stacks into the PGDM Online program, an AICTE-approved master’s level program offered by SP Jain Institute of Management Research (SPJIMR), India. It's a premium online program catering to the needs of working professionals in India and the rest of the world. Join us to unlock the full potential of data analysis and drive your success in the business-oriented world.

This week we will begin with module 1- Introduction to AI, BIA and Overview of Data Mining. AI (Artificial Intelligence) is an umbrella term, encompassing various technologies and applications, including ML (Machine Learning) (this also included Deep Learning and Generative AI), Robotics, Computer Vision. Artificial intelligence is a machine’s ability to perform some cognitive functions we usually associate with human minds (e.g., perceiving, reasoning, learning and problem solving). BIA (Business Analytics & Analytics) is essentially applying ML for improving business performance. BIA includes various technologies like Data Mining, Business Forecasting, OLAP. This module will give an overview of some of the aspects of AI. It will also talk about various steps involved in BI&A, involving Requirements, Data Warehouse, Exploratory Data Analysis techniques, Detailed techniques, Bench marking so that business performance before and after incorporating analytics can be compared. It will talk about various skill set under “Data Science”. It will then give an overview of various techniques of Data Mining, namely Supervised Learning (Classification and Regression) Unsupervised Learning (Association, Clustering, and Dimension Reduction). This module will also talk about steps for carrying out supervised learning. By the end of this course, students should be able to: 1. Understand the Business Analytics concepts, tools and techniques 2. Understand how organizations can succeed using data 3. Analyse data using techniques like Data Mining 4. Apply techniques in various business situations 5. Apply two tools, namely R and Orange, along with Excel 6. Strategically think about how to improve business performance