Big Data Applications

₱ 0.00

AG

Albert Anthony Gavino

English, Filipino ∙ Self-paced (1 hr 18 mins)

Date Published
September 19, 2023
Course Updated
November 22, 2024
Categories:
Analytics
Tags:
#Analytics

About the Course


Big data is the result of our need for distributed computing, which requires us to process a large amount of data while also requiring us to use additional resources, such as computer power and memory. This course will give you an introduction about big data and its application. 


Course Objective


  • To categorize data
  • To discuss 3 V’s.
  • To acquire insight of how to solve the problems with data and what are procedures to do. 
  • To determine whether it is worthwhile to invest in data science.


Course Outline


  • What is Big Data?
  • Why do we need Big Data?
  • What are the 3 V’s?
  • The cost of not using Big Data
  • Big Data Applications


Target Participants


All individuals who are interested in learning more about big data applications.


Certificate Requirements


  • Completion of recorded webinar + quiz
  • Pass the 10 item multiple choice with 80% mark
  • Comment your feedback to the main page of the course


No frequently asked questions for this course yet.
5.0
62 Ratings
98%
1%
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Ezekiel Ramos
11 months

nice

Louie Jean
10 months

"Big Data Applications" is a student's gateway to understanding data's vast potential. It explores practical applications in diverse fields, from healthcare to finance. This course equips me with the knowledge and skills to harness big data, offering valuable insights for academic studies and future professional engagements.

Benjomin Noah
10 months

.

John Jerick
10 months

The session provides a comprehensive overview of data processing, covering methods for acquiring, cleaning, and analyzing data. It emphasizes the significance of adapting to market changes to avoid opportunity costs and discusses the role of behavior analysis in shaping consumer engagement, all while addressing privacy concerns.

Jaymart
10 months

It helps me to understand how data works and how we can handle the large amount of data

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