Big Data: Hadoop Administrator, Spark Developer

Course details

 
This course is essential to all software engineers, programmers, Data analysts, database administrators and anyone looking to become great at big data.

• You will learn how to use the most popular software in the Big Data industry at moment, using batch processing as well as realtime processing.
• This course will give you enough background to be able to talk about real problems and solutions with experts in the industry.
• You will gain an experience with Ingesting data into Hadoop file system, working with data in batch and Stream processing, Deliver visualization and insights of Data and too many technical skills.

Beginner Level 3 Days / 24 Hours
Fundamentals of Big Data

• Intro to Distributed Systems & HDFS
• Exploring Big Data Ecosystem & Distributions
• Basic Intro to NoSQL

Hadoop Fundamentals

• Intro to Hadoop
• Introduction to MapReduce
• Intro to YARN
• Basic Hadoop Cluster Implementation

SQL-On-Hadoop

• Intro to SQL-On-Hadoop
• Intro to Hive
• Basic Implementation of Hive & Hive Server 2
• Ingesting Data into Hadoop
• Intro to Sqoop
• Concept of Stream Processing
• Into to Kafka

Advanced Level: 5 Days / 40 Hours
 
MapReduce In Depth

• Hadoop Architecture In Depth
• Intro to Apache Zookeeper
• Advanced Cluster Implementation

SQL-On-Hadoop

• Advanced Hive Architecture
• Ingesting Data Into Hive Using Sqoop
• HiveQL
• Intro to Apache HBase

Ingesting Data into Hadoop

• Intro to ETL Concepts
• Intro to Data Flow using Apache Nifi
• Implementing Apache Nifi Cluster
• Simple Integration Project with Apache Nifi

Intro to Python Programming

• Ingesting Data into Hadoop
• Implementing Kafka Cluster
• Building Simple Kafka Producer & Consumer Using Python

Intro to Apache Spark

• Spark Implementation
• Simple Data Analysis with Apache Spark

Big Data Workshop: 5 Days / 40 Hours
  Project 1: Data Ingestion from RDBMS into HIVE (ORC File)

• Using Sqoop to Connect to RDBMS(Oracle / SQL Server)
• Creating Hive Table on ORC File
• Hive Table Performance Tuning

Project 2: Data Ingestion Streaming Data Using Kafka into Hadoop/Hive

• Using Kafka to Connect to RDBMS(Oracle / SQL Server)
• Kafka Advanced Cluster Configuration
• Ingesting Data into Hadoop/Hive

Project 3: Data Analysis & Stream Processing using Spark 1

• Spark Cluster Implementation
• Using PySpark
• Processing Data With Spark
• Stream Processing With Spark

Project 4: Data Analysis & Stream Processing using Spark & Hive 2

•  Integrating Spark with Hive
• Ingesting Data with Spark into Hive
• Using Spark SQL

Project 5: Data Visualization Using Apache

• Implementing Apache Zeppelin
• Integrating Apache Zeppeling With Spark
• Visualize Data With Zeppeling

Updated on 20 July, 2020