Big Data Analysis

Big Data Analysis

Learn to manage and analyze Big Data with this course. Covering Hadoop, HDFS, MapReduce, data loading, Hive for SQL queries, real-time querying with HBase, and data processing with Spark. Theory and practical exercises provided.

About the course

Each of us produces an ever-increasing amount of data every day, albeit sometimes unconsciously: learning how to manage and analyze the massive amounts of data in circulation today has consequently become essential.

Course participants will gain knowledge regarding the concepts basic theory, tools and techniques for the design and implementation of procedures for the advanced analysis of large quantities of data (Big Data).

The course aims to lead participants to understand the architecture and modules of the Hadoop framework, use the HDFS distributed filesystem, write and run MapReduce jobs (java), load data (bulk load) on HDFS, Query Hadoop using SQL-like syntax through Hive, Use HBase for real-time queries and use Spark for data processing.

All topics are covered from a theoretical perspective and accom paid by a lot of demonstration exercises that will be developed and described during the course.

Course Length: 160 hrs

Prerequisites: Basic coding knowledge

Big Data Analysis card image

What you'll learn:

  • Fundamentals of big data concepts and technologies
  • Techniques for processing and analyzing large-scale datasets
  • Advanced data manipulation and transformation methods
  • Introduction to distributed computing frameworks like Apache Hadoop

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Supercharge Your Insights: Dive into Big Data Analysis Today

Supercharge Your Insights: Dive into Big Data Analysis Today

Discover the secrets of Big Data Analysis. Extract, process, and uncover insights from massive datasets. Make data-driven decisions with confidence. Join our transformative course and master the art of impactful data analysis.

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Big Data Analysis course program:

Introduction

  • Introduction to Scala
  • Differences between Scala and Java
  • Lambda functions
  • Anonymous classes in Java
  • Implementation of lambdas in Java8

Big Data

  • Definition of Big Data
  • SQL vs. NoSQL approach
  • Analysis of the main types of NoSQL databases
  • Introduction to the Hadoop framework
  • Using the HDFS filesystem
  • YARN and MapReduce
  • Writing MapReduce jobs using the Java language
  • Data ingestion using Sqoop
  • Querying Hadoop using SQL-like syntax with Hive
  • Querying Hadoop using Pig scripts
  • Introduction to HBase
  • Architecture and basic data operations in HBase
  • Introduction to the Scala language and basic syntax
  • Data processing with Spark and main differences with MapReduce
  • Analysis of data with Spark RDD (part 1)
  • Analyzing data with Spark RDD (part 2)
  • Using Spark SQL

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