Big Data Analytics

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Data is everywhere and it is transforming our world. Almost all industries are bracing big data and using different data analysis techniques to dig out valuable insights, and create data-driven solutions for their challenges. More and more companies are hiring professionals who can analyse and visualise data, uncover insights to make better decisions.

The Star Big Data Analytics program introduces the learners to the most popular data analytics language, R and one of the most common frameworks, Hadoop. The program helps the learners acquire a fundamental understanding of big data and machine learning, data mining concepts, data visualization and mobile analytics. The purpose of the SBDA is to help the learners master the skills they need to establish a successful career as a data analyst.

Audience

Intermediate

Big Data Analytics Course Objectives

In this course, you will learn about:

• Big Data and its impact on businesses
• Data analysis using R programming and visualization tools
• Different data mining techniques
• Big Data and Hadoop
• Machine learning concepts and Hadoop

Course Outcome

After completing this course, you will be able to:

• Describe Big Data and its importance
• Analyse the unstructured data and apply R programming concepts on it
• Uncover key insights and create data-driven solutions for business challenges
• Generate predictions based on the analysed data
• Implement Machine Learning concepts and data visualization techniques on data
• Work as a successful Data Analyst

Table of Contents Outline

1. Introducing Data and Big Data
2. Application of Big Data in Commercial Areas
3. Big Data and Hadoop
4. Exploring Analytics
5. Exploring R – Data Analytics Language
6. Performing Statistics Concepts with R
7. Introduction to Machine Learning
8. Machine Learning and Hadoop
9. Data Mining and the Web
10. Text Mining and Analytics
11. Pattern Discovery in Data Mining
12. Analysing Clusters in Data Mining
13. Data Visualisation and Tools
14. Exploring Mobile Analytics
15. Exploring Real-world Analytical Organisations
16. Big Data in Different Industries

Labs

1. Setting Up the Required Environment for Apache Hadoop Installation
2. Installing the Single-Node Hadoop Configuration on the System
3. Implementing Clara Algorithm in R
4. Implementing K-Means Algorithm in R
5. Implementing KNN Algorithm in R Language
6. Implementing MapReduce Program for Word Count

Exam Details

Exam Codes	Big Data Analytics S08-510 (Academy customers use the same codes)
Number of Questions	75
Type of questions	Multiple Choice
Length of Test	150 mins
Passing Score	70%
Recommended Experience	Beginner to Advance, Learner should have basic Knowledge of Statistics and Mathematics or Learners should be from Finance background.
Languages	English
Registration link	Closed