Big Data Training
Become a Master on Implementing Big Data Solutions With Best Practices
THE GOAL OF COURSE
The purpose of the Big Data Training Program is to enable participants to consolidate their knowledge in the their minds with experience sharing, example implementations and case studies, while providing detailed information on key concepts and techniques in the Big Data Ecosystem.
WHAT YOU WILL LEARN
- Learn the terminology and basic concepts behind the Big Data Systems with the best solution designs
- Develop technical knowledge and competencies with workshops,
- Apart from the information in the books, listen to real world examples and experiences that you will not even find on the internet,
- Understand which technology and architectural design you need to advance in which case
- Make a significant contribution to your development in Big Data,
- Be able to find answers to your questions at the points where your head is installed while developing after the program.
WHO BENEFITS
- Employees who are doing or planning to make a career in the Big Data place
- Leading teams in technology / IT functions
- Leaders responsible for Digital Transformation.
- Data Scientists and Data Analysts
- New Graduates and University Students
Those Who Want To Transform Theoretical Knowledge Into Practice In A Big Data Place And Make A Difference In Career Development
Theories and practices you will see throughout the program will answer your questions on the Big Data, also you will learn key techniques to develop the right strategy while implementing your projects
COURSE OUTLINE
- Module-1: Introduction To Big Data
- History of Big Data
- Characteristics of Big Data
- Processing Big Data
- Tools and Techniques for Analyzing Big Data
- Implementing Big Data Solutions
- Case Study – Social Media Analytics
- Module-2 The Hadoop Ecosystem
- Hadoop Architecture and Components
- HDFS Distributed File System
- Using HDFS Command Line
- YARN Architecture and Features
- Understanding MapReduce and Using It
- Using HBase Database
- Lab: Hadoop Cluster Installation
- Lab: Writing MapReduce algorithm with Java
- Hadoop Cluster Best Practices
- Module-3: The Big Data Analysis
- Pig Programming
- Pig Data Formats
- Lab: Using Pig with Examples
- Querying Data with Hive
- Hive Data Formats
- Lab: Using Hive with Examples
- Module-4 : NoSQL Databases
- The History of NoSQL Databases
- What are the Advantages of NoSQL Systems?
- The Constraints of NoSQL Databases
- The Types of NoSQL Databases
- Lab: Using MongoDB
- Lab: Using Cassandra
- Lab: Using Redis
- Lab: Usign Neo4j
- Module-5 : Real-Time Data Processing
- Use Cases for Real-Time Data Processing
- Messaging Systems
- Apache Zookeeper: Distributed Coordination Service
- Zookeeper Installation and Management Basics
- Apache Kafka: Scalable Messaging System
- Kafka Installation and Management Basics
- Apache Spark Architecture and Components
- Data Processing with Spark Streaming
- Lab: Real-Time Data Processing with Java
- Module-6 : Scalable Search Techniques on Big Data
- The Comparison of Search Technologies
- Important Factors for Scalable Search
- Using Elasticsearch
- Understanding Data Modelling
- Elasticsearch Best Practices
- Lab: Data Indexing and Search Examples