Get the coupon in the end of description.
Description
Description
Take the next step in your career! Whether you’re an up-and-coming professional, an experienced executive, aspiring manager, budding Professional. This course is an opportunity to sharpen your Sentiment analysis. Image Analytics. Video analytics. Voice analytics. Monte Carlo simulations., increase your efficiency for professional growth and make a positive and lasting impact in the business or organization.
With this course as your guide, you learn how to:
All the basic functions and skills required key business analytics.
Transform the Key Business Analytics including the raw material – data. Business experiments/experimental design/AB testing. Visual analytics. Correlation analysis. Scenario analysis. Forecasting or Time. Data mining. Regression analysis. Text analytics. Text analytics.
Get access to recommended templates and formats for the detail’s information related to key business analytics.
-
Learn to Qualitative surveys. Focus groups (. Interviews and ethnography. Test capture. Image capture. Sensor date. Machine data capture. Financial analytics. Customer profitability analytics. Product Profitability. are presented as with useful forms and frameworks
Invest in yourself today and reap the benefits for years to come
The Frameworks of the Course
Engaging video lectures, case studies, assessment, downloadable resources and interactive exercises. This course is created to learn the Introduction to the Key Business Analytics including the raw material – data. Business experiments/experimental design/AB testing. Visual analytics. Correlation analysis. Scenario analysis. Forecasting or Time. Data mining. Regression analysis. Text analytics. Text analytics. Sentiment analysis. Image Analytics. Video analytics. Voice analytics. Monte Carlo simulations. Linear programming. Cohort analysis. Factor analysis. Neural network analysis. Meta analytics literature analysis. Analytics inputs tools or data collection methods
-
The details Test capture. Image capture. Sensor date. Machine data capture. Financial analytics. Customer profitability analytics. Product Profitability. Cash flow analysis. Value driver analytics. Shareholder value analytics. Market analytics. Market size analytics. Demand forecasting. Market trends analytics. Non- customer analytics.
The course includes multiple Case studies, resources like formats-templates-worksheets-reading materials, quizzes, self-assessment, film study and assignments to nurture and upgrade your of Competitor analytics. Pricing analytics. Pricing analytics. Marketing channel. Brand analytics. Customer analytics in details.
In the first part of the course, you’ll learn the details of Introduction to the Key Business Analytics including the raw material – data. Business experiments/experimental design/AB testing. Visual analytics. Correlation analysis. Scenario analysis. Forecasting or Time. Data mining. Regression analysis. Text analytics. Text analytics. Sentiment analysis. Image Analytics. Video analytics. Voice analytics. Monte Carlo simulations. Linear programming.
In the middle part of the course, you’ll learn how to develop a knowledge of The , Test capture. Image capture. Sensor date. Machine data capture. Financial analytics. Customer profitability analytics. Product Profitability. Cash flow analysis. Value driver analytics. Shareholder value analytics. Market analytics. Market size analytics. Demand forecasting. Market trends analytics. Non- customer analytics.
In the final part of the course, you’ll develop the Competitor analytics. Pricing analytics. Pricing analytics. Marketing channel. Brand analytics. Customer analytics.
Course Content:
Part 1
Introduction and Study Plan
· Introduction and know your Instructor
· Study Plan and Structure of the Course
1. Introduction
1.1 Details of Introduction
1.2. The raw materials -Data
1.3. Data types and format
1.4. How to use this
1.5. Who is this for?
2. Business experiments or experimental design or AB testing
2.1. What is it?
2.2. What business questions is it helping me to answer
2.3. Create a hypothesis
2.4. Design the experiment
2.5. Tips and traps
3. Visual analytics
4. Correlation analysis
5. Scenario analysis
6. Forecasting or Time
7. Data mining
8. Regression analysis
9. Text analytics
10. Sentiment analysis
11. .Image Analytics
12. Video analytics
13. .Voice analytics
14. Monte Carlo simulations
15. . Linear programming
16. Cohort analysis
17. Factor analysis
18. Neural network analysis
19. Meta analytics literature analysis
20. Analytics inputs tools or data collection methods
21. Qualitative surveys
Part 2
22. Focus groups
23. Interviews
24. Ethnography
25. Test capture
26. . Image capture
27. Sensor date
28. Machine data capture
29. Financial analytics
30. Customer profitability analytics
31. Product Profitability
32. Cash flow analysis
33. Value driver analytics
34. Shareholder value analytics
35. Market analytics
36. Market size analytics
37. Demand forecasting
38. Market trends analytics
39. Non- customer analytics
40. Competitor analytics
41. Pricing analytics
42. Marketing channel
43. Brand analytics
44. Customer analytics
45. Customer lifetime