Business Analytics and Digital Media

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Description

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About this course: The explosion in digital media - web, social and now mobile - represents a departure from how things were like in the last century. This proliferation of digital media is both a threat and an opportunity for many businesses. Business Analytics can be leveraged to process data, sentiment, buzz, contacts, context and other aspects of business interest in real time, for business performance and impact. 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.

Created by:  Indian School of Business
  • Taught by:  Sudhir…

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When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: The explosion in digital media - web, social and now mobile - represents a departure from how things were like in the last century. This proliferation of digital media is both a threat and an opportunity for many businesses. Business Analytics can be leveraged to process data, sentiment, buzz, contacts, context and other aspects of business interest in real time, for business performance and impact. 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.

Created by:  Indian School of Business
  • Taught by:  Sudhir Voleti, Assistant Professor and ISB Research Fellow

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Basic Info Course 2 of 6 in the Business Technology Management Specialization Level Beginner Language English How To Pass Pass all graded assignments to complete the course. User Ratings 4.0 stars Average User Rating 4.0See what learners said 课程作业

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Indian School of Business The Indian School of Business has successfully put India on the global map of management education by nurturing young leaders with an understanding of developing economies and the society at large. Through innovations in curricula and pedagogy to reflect the shifting business landscape, the ISB is committed to providing the best venue for management education to meet the growing need to develop young leaders who can manage global challenges.

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.


7 videos, 2 readings expand


  1. Video: Introductory Business Analytics and Digital Media
  2. 讨论提示: Learner Introduction
  3. Video: Conceptual Preliminaries
  4. Video: Framework for Problem Formulation
  5. Video: Transformative Problem Formulation
  6. 讨论提示: Share examples of D.Ps and R.O.s
  7. Video: Data Types and Psychometric Scaling
  8. 阅读: Introduction to Business Analytics and Psychometrics
  9. Video: Exploratory Vs Confirmatory Dichotomy
  10. Video: Revisiting Problem Formulation
  11. 阅读: In Video Reading for Lecture "Revisiting Problem Formulation"
  12. 讨论提示: Share examples of Predictive analytics in action

Graded: Summative Assessment

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.


7 videos, 2 readings expand


  1. Video: Toolscape for Business Analytics
  2. Video: A primer on Business Experimentation
  3. 讨论提示: Share examples of Business experimentation
  4. Video: Conceptual Preliminaries
  5. Video: Software for this Course
  6. 阅读: Instructions for Running the Analytics Desktop Apps using RStudio and GitHub
  7. Video: Training Machines A People-Analytics Use Case
  8. Video: The Exponential Learning Curve of the Machines
  9. 讨论提示: Share some machine learning examples
  10. Video: Toolscape Summary and Warp-up
  11. 讨论提示: What principle drives Evolv’s approach?
  12. 阅读: Additional links and reading material

Graded: Summative Assessment

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.


5 videos, 3 readings expand


  1. Video: Motivating Customer Analytics
  2. Video: preliminaries for Customer Analytics
  3. Video: Factorizing Data
  4. 讨论提示: Share examples of Factor-An application
  5. Video: Clustering Data
  6. 讨论提示: Share examples of Cluster-An or Joint Space Mapping
  7. Video: Visualising Data
  8. 阅读: Data sets and slides as reference material for Perceptual mapping
  9. 阅读: How to Run Analytics Apps in R
  10. 阅读: Analytics Apps - Examples & Intro

Graded: Summative Assessement

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.


6 videos, 2 readings expand


  1. Video: Motivating Technology for Brands
  2. Video: Setting the Context: Digital Advertising
  3. Video: The App Era in Digital Social Media
  4. Video: Social Graphs and Hyper-Segmentation
  5. 讨论提示: What is a 'social graph'?
  6. Video: Non-Social Digital Media for the Enterprise
  7. Video: Formulating and Analytics Problem
  8. 讨论提示: What is the main take-away from the GE reading? Why do you think so?
  9. 阅读: Additional Reading for Module "Digital Media"
  10. 阅读: GE caselet: In-video Reading

Graded: Summative Assessment
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There are no frequently asked questions yet. Send an Email to info@springest.co.uk