Business Analytics and Data Science / Big Data Analytics

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Kothrud, Pune

Course ID: 42525

Kothrud, Pune

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Sonali Kulkarni picture
Sonali Kulkarni

M.Sc. (Statistics)

About Sonali Kulkarni

I am working in the IT industry since last 20+ years and have diverse experience in IT Project Management and IT Training.

I worked for US clients in different domains like Telecom, Healthcare, Reliability and Maintenance and delivered the Business Analytics solutions across clients.

I am conducting this training since last 10+ years and have trained more than 200 students till date.
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About the Course

Course Name: Business Analytics


Pre-requisite: MS-Excel Basic Knowledge


Duration: 40 - 45 Hrs.


Learning Objectives:


At the end of the course, students will be able to:



  1. Understand the concepts of Business Analytics

  2. Understand the analytics applications in different areas like Marketing, Finance, and HR etc.

  3. Apply the data analytics skill using MS Excel

  4. Create visualizations using Tableau


Course Outline



  1. Introduction to Business Analytics

  2. Business Analytics Application Areas

  3. Descriptive Analytics

  4. Predictive Analytics

  5. Statistical Modelling

  6. Introduction to Tableau

  7. Data Visualizations using Tableau

  8. Customer Analytics

  9. Marketing, Finance and HR Analytics

  10. Web and Social Media Analytics

  11. MIS, Business Intelligence and Data Warehousing

  12. Case Studies based on real life scenarios


Prepared by: Sonali Kulkarni


 


Course Name: Business Analytics


Pre-requisite: MS-Excel Basic Knowledge


Duration: 40 - 45 Hrs.


Learning Objectives:


At the end of the course, students will be able to:



  1. Understand the concepts of Business Analytics

  2. Understand the analytics applications in different areas like Marketing, Finance, and HR etc.

  3. Apply the data analytics skill using MS Excel

  4. Create visualizations using Tableau


Course Outline



  1. Introduction to Business Analytics

  2. Business Analytics Application Areas

  3. Descriptive Analytics

  4. Predictive Analytics

  5. Statistical Modelling

  6. Introduction to Tableau

  7. Data Visualizations using Tableau

  8. Customer Analytics

  9. Marketing, Finance and HR Analytics

  10. Web and Social Media Analytics

  11. MIS, Business Intelligence and Data Warehousing

  12. Case Studies based on real life scenarios

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