Big Data Diploma : Data Management&Analytics

Course details

 Course Overview:
 Interested in increasing your knowledge of the Big Data Systems?
 This course is for those who are new to big data and drive your through hands-on practical experience to learn Apache Hadoop.
 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.
 
 Diploma Duration : 104 Hours
 Audience Profile:
 This course targeted for
 Who are interested in big data management, data engineering and data analysis using Big Data technologies
Database Administrators, Developers & System Administrators which aims to get hands on training about big data and NoSQL

  Course Outcomes:
 Students will be trained as big data Engineers with real world hands-on experience in Hadoop Administration, ETL (Batch/Stream), Sql-On-Hadoop and many other technologies related to Big Data.

 Instructor Bio:
Having more than 7 years building data Integration & Data Warehouse project at different governmental project. Leading many project in Big Data Platform “Design, Implementation & Development”.
Working for National project at “Administrative Control Authority” building data warehouse and data integration.
Working for National project at “Traffic Information Technology Department – Ministry of Interior”.
 
 Course Outline in details: 
 
Beginner Level: 3 Days / 24 Hours
 
 
Introduction to Big Data
Intro to Distributed Systems & HDFS
Exploring Big Data Ecosystem & Distributions iv. 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 iii. 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 13 November, 2019