Business Analytics: Diversity of Practical Applications

This course is designed to open the doors of the world of business analytics. Nowadays a lot of organizations make their decisions based on data-driven approach. How to make the right decision? Which methods are used in multinational companies? This course is about demonstrating the diversity of real cases and applications of methods, techniques, and theories in various areas.

Each week of this course is a piece of a puzzle where you will meet different experts from the industry who will share with you best practices from the market. Bringing together all the pieces you will understand the key definitions used in business analytics and will learn about data analytics techniques which can be applied in marketing, sales, PR, HR, and finance. “Business Analytics: Diversity of Practical Applications” aims to help you to navigate in the variety of career opportunities which are opened for business analysts.

This Course is part of HSE University Master of Data and Network Analytics degree program. Learn more about admission into the program and how your Coursera work can be leveraged if accepted into the program here https://inlnk.ru/WMKM6.

• Introduction to Business Analytics
• What is Business Analysis? What is Business Analyst’s job about? What are the varieties of skills that are needed to be successful on the market? First videos will give you an overview of this course. Then you’ll learn what is the Digital transformation and digital landscape with new trends and technologies. You’ll explore a new way of working and will dive into agility as a new reality. The module ends with classification of key analytical approaches and basics of Data management. This module is taught by Elena Beylina, Analyst at International Laboratory for Applied Network Research
• Performance Evaluation
• In this lecture, we will look at one of the most important, but very often misunderstood, concept in business analytics - efficiency analysis. We will start with definitions of efficiency, effectiveness, and similar terms. Then, we will look at theoretical approaches to understanding efficiency and effectiveness. Next, we'll discuss the common practices of efficiency and effectiveness analysis, focusing on the pros and cons of each. Finally, we will talk about the state-of-the-art data analytics approaches to this important business analytics topic. This module is taught by Valentina Kuskova, Associate Professor, Faculty of Social Sciences
• Social Network Analysis: Applications for Organizations
• It has been commonly accepted in management theory that performance metrics such as productiveness and employee turnover depend on attributes of employees, management units and organization as a whole. However, last two decades raised recognition that many of these outcomes are largely shaped by the informal structure of organization, or its social network. As coined by Rob Cross, organizational network analysis is an X-ray into the actual processes evolving in the organization. It can effectively address various management tasks including creating innovative environment, identifying employees’ organizational roles for targeted interventions, succession planning and support of change initiatives. This week will Introduce you to the basic concepts and tools of Social Network Analysis (SNA) and illustrate its power for organizational management. You will learn how to visualize and analyse networks in Gephi. This module is taught by Lisa Chernenko, lecturer at the HSE International College of Economics and Finance.
• Data Analysis Process: Consumer and Market Research Application
• What kind of tasks are solved in consumer insights and market research departments? What is an insight and how to go through the market research process to achieve the objective? Is there a cross industry data analytical process? And which types of data are most used in market research? This module is fundamental for understanding and exploring key definitions of market research. You will learn the application of CRISP-DM framework in market research and will go through all the steps of analytical process from business problem to final report. In addition to that, we will focus on text data as the most quickly developed source of information and will practice in crapping the data from the Guardian website. This module is taught by Elena Beylina, Analyst at International Laboratory for Applied Network Research
• Contemporary Text Analysis
• Can text mining help in real-life business applications? How to distinguish a promising NLP product from an outdated craft and which tools to use if you have to do everything yourself? First videos will give you an overview of contemporary natural language processing tasks and contemporary models. Then you’ll learn trending models and approaches in NLP and explore the main ideas behind them. The module ends with several practical examples that will help you to perform text mining on your own. This module is taught by Ilya Karpov, Junior Research Fellow at International laboratory for Applied Network Research
• Business Process Management and Financial Modelling
• What is a business process and why process thinking has sometimes a crucial value in decision-making? From which steps does Business Process Management lifecycle consist of? What is the notation BPMN 2.0 and how it can help you to draw the processes? How does the finance-related information be organized in Excel? How to perform an automatically calculated model? Thus, we will introduce you to the fundamentals of process management. At the end of the first part of the module, you will be able to build your own process models. In addition to that, the second part of the module will be devoted to financial modeling and organizing data in clear spreadsheets in a simple and meaningful way. This module is taught by Elena Beylina, Analyst at International Laboratory for Applied Network Research, and Kirill Mikhin, Investment Analyst in Russian Direct Investment Fund.
• Final Project
• This is the last week of the course. And now it is time to apply gained knowledge into real-life problems. This course was a puzzle-based that is why we offer you 5 projects based on the material you have learned. Probably you loved more the topic of text mining, or you are eager to draw the process model. You have a chance to choose one of the offered projects.