Monday, 30 March 2020 12:37

Bloomber Market Concepts

Why Study Business Analytics?

Business Analytics: From Data to Insights — arms managers and leaders with the tools needed to break away from the pack. Take the opportunity to turn data into a competitive advantage.

Who Is This Program For?

This course is ideal for managers and leaders who wish to learn how analytics can help improve their decisionmaking processes. Business Analytics: From Data to Insights will give participants an understanding of how to look at data and identify insights, improve their ability to make longterm predictions, and prescribe future actions to help make better business decisions. Participants come from a wide range of industries, job functions, and management levels.

Participants by Job Function Include:

  • Account Managers 
  • Assistant Directors 
  • Business Analysts 
  • CEOs 
  • Chief Marketing Officers
  • CIOs 
  • Executive Directors 
  • Financial Analysts 
  • Investment Directors 
  • Product Managers 
  • Portfolio Managers 
  • Vice Presidents

Your Learning Experience

Orientation Module: Orientation and Introduction to Business Analytics Module

1: Descriptive Analytics: Gathering Insights Module

2: Descriptive Analytics: Describing and Forecasting Future Events Module

3: Predictive Analytics: Making Predictions Using Data Module

4: Predictive and Prescriptive Analytics: Application and Toolkit Module

5: Predictive Analytics: Tools for Decision Making Module

6: Predictive Analytics: Using Data to Predict Employee Performance Module

7: Prescriptive Analytics: Providing Recommendations to Change Behavior Module

8: Prescriptive Analytics: Determining the Most Favorable Outcomes Module

9: Application of Analytics for Business

Methods and Tools:

Data Collection

Methods

  • Descriptive Data Collection: Surveys, Net Promoter Score (NPS), and Self-Reports
  • Passive Data Collection
  • Media Data Collection: Radio, Television, Mobile, etc.

A/B Testing

Correlation and Causation

Forecasting

  • Objective and Subjective
  • Strand or Seasonal Variation
  • Exponential Smoothing
  • Descriptive Statistics
  • Trends and Seasonality
  • New Product

Regression Analysis

 

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