Business Analytics and Digital Media (Coursera)

The course picks and uses use-cases from a variety of industries and geographies, to showcase the potential and impact that business analytics done properly (or not) can have on business performance.

Course 2 of 6 in the Business Technology Management Specialization.

Syllabus

WEEK 1

Introduction to Business Analytics

An overview of the what and the why Learning outcomes by the end of week 1 should normatively be that (a) Students grasp what is business analytics from the perspective of a business manager, (b) identify areas of interest, overlap, co-ordination and conflict with other business functions and processes in the firm, (c) and, develop an appreciation for the value of data, of analyses and of the components of analytics.

WEEK 2

Toolscape

An overview of the broad tools available for business analytics and the leveraging of digital media. Learning outcomes by the end of week 2 should normatively be that (a) Students have an understanding of the broad classes of analytics tools and platforms that currently dominate the market, (b) and, develop an appreciation for the pros and cons of the major groups of tools.

WEEK 3

Customer Analytics

Introduction to and the application of some important analytical processes in Marketing Analytics Learning outcomes by the end of week 3 should normatively be that (a) Students have an understanding of the major processes and procedures typically used in a customer analytics setting, in particular factor and cluster analyses (b) and, develop an appreciation for the possibilities that emerge from recombining procedures, data, algorithms and problem formulation perspectives in open source environments.

WEEK 4

Digital Media

An overview of the big questions, possibilities and challenges. Learning outcomes by the end of week 4 should normatively be that (a) Students have an understanding of the major types of digital media in use currently by people and firms, (b) and, develop an appreciation for the types of problem solving, data collection, prediction and optimization that can be enabled using digital media tools.