Big Data Fundamentals

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Big Data Fundamentals

Big Data Fundamentals

with Glen Mules

Audience:
Big Data Beginners

Time to complete:
1.5 Hours

Available in:
English

This course presents a holistic approach to Big Data, taking both a top-down and a bottom-up approach to questions such as: What is Big Data? How do we tackle Big Data? Why are we interested in it? What is a Big Data platform?

The course emphasizes that we study Big Data to gain insight that will be used to get  people throughout the enterprise to run the business better and to provide better service to customers. Rather than a implementation of a single open-source systems such as Hadoop, the course recommends that Big Data should be processed in a platform that can handle the variety, velocity, and volume of data by using a family of components that require integration and data governance.  Big Data is NoHadoop (“not only Hadoop”) as well as NoSQL (“not only SQL”).

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By completing this course and passing the assessment, you will earn an IBM Badge! IBM's open badges provide an online representation of skills and achievements, allowing you to share your credential to LinkedIn, Facebook and Twitter. Or download and add to your badge to your e-mails and websites. When someone clicks on your badge, they link to metadata describing your qualifications along with the process required to earn them. This additional level of information helps tell a more complete and compelling story of your achievements!

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This course was tested and validated for v3 of the QSE VM.

Please download the v3 VM to complete the lab exercises.

https://www14.software.ibm.com/webapp/iwm/web/preLogin.do?source=swg-beta-iibob

Course Syllabus

  • Define and describe Big Data and its role in the corporate world
  • Recognize the phases of development of a Big Data strategy within a corporation
  • Explain the rationale underlying a holistic approach to Big Data
  • Give examples of Big Data usage in areas such as sensor data, social media, science, and data warehouse augmentation
  • Understand why a Big Data Platform is required to bring together what would otherwise be separate silos of data and analytics
  • Identify the importance of data governance for managing Big Data
  • Outline the components needed in a Big Data Platform
  • Compare and contrast the roles of: data-at-rest processing, data-in-motion processing, data-warehouse processing, and contextual search

General Information

  • This course is free.
  • It is self-paced.
  • It can be taken at any time.
  • It can be taken as many times as you wish.
  • Students passing the course (by passing the final exam) will have immediate access to printing their online certificate of achievement.
  • Your name in the certificate will appear exactly as entered in your profile in BigDataUniversity.com.
  • If you did not pass the course, you can take it again at any time.

Pre-requisites

None

Recommended skills prior to taking this course

Basic knowledge of operating systems (UNIX/Linux)

Grading Scheme

The minimum passing mark for the course is 60%, where the final test is worth 100% of the course mark. You have 3 attempts to take the test