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Big Data & Hadoop Certified Training

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Big Data & Hadoop Certified Training

Deciphering raw data to come up with actionable insights lie at the crux of data analysis. According to the latest research, nearly 2.5 quintillion bytes of data is created, and the number is slowly edging upwards. The storage and processing power needed to handle these large volumes of data cannot be handled in an efficient manner with traditional frameworks and platforms. To understand and make sense of these large volumes or big data, there arose a need to explore distributed storages and parallel processing operations. Hadoop by Apache provides the much-needed power that is required to manage such situations.

Why Should You Choose Big Data & Hadoop Certification?

  • McKinsey predicts that by 2018 there will be a shortage of 1,500,000 data experts
  • McKinsey predicts that by 2018 there will be a shortage of 1,500,000 data experts
  • The Hadoop Big Data analytics market is projected to grow to USD 40.69 Billion by 2021 - MarketsandMarkets
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Big Data & Hadoop Certification - Instructor Led Training

15 th  October
Sat&Sun (4 Weeks) Weekends Batches
Timings: 07:00 AM - 11:30AM(IST)
Sold Out
25 th  October
Sat&Sun (4 Weeks) Weekends Batches
Timings: 07:00 AM - 11:30AM(IST)
Filling Fast
1 st  November
Sat&Sun (4 Weeks) Weekends Batches
Timings: 07:00 AM - 11:30AM(IST)
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Big Data & Hadoop Curriculum

  • Introduction to Big Data & Big Data Challenges
  • Limitations & Solutions of Big Data Architecture
  • Hadoop & its Features
  • Hadoop Ecosystem
  • Hadoop 2.x Core Components
  • Hadoop Storage: HDFS (Hadoop Distributed File System)
  • Hadoop Processing: MapReduce Framework
  • Different Hadoop Distributions
  • Scrum Principles
  • Scrum Aspects
  • Scrum Process
  • Scrum Advantages
  • Hadoop 2.x Cluster Architecture
  • Federation and High Availability Architecture
  • Typical Production Hadoop Cluster
  • Hadoop Cluster Modes
  • Common Hadoop Shell Commands
  • Hadoop 2.x Configuration Files
  • Hadoop 2.x Configuration Files
  • Basic Hadoop Administration
  • Traditional way vs MapReduce way
  • Why MapReduce
  • YARN Components
  • YARN Architecture
  • YARN MapReduce Application Execution Flow
  • YARN Workflow
  • Anatomy of MapReduce Program
  • Input Splits, Relation between Input Splits and HDFS Blocks
  • MapReduce: Combiner & Partitioner
  • Demo of Health Care Dataset
  • Demo of Weather Dataset
  • Counters
  • Distributed Cache
  • MRunit
  • Reduce Join
  • Custom Input Format
  • Sequence Input Format
  • XML file Parsing using MapReduce
  • Introduction to Apache Pig
  • MapReduce vs Pig
  • Pig Components & Pig Execution
  • Pig Data Types & Data Models in Pig
  • Pig Latin Programs
  • Shell and Utility Commands
  • Pig UDF & Pig Streaming
  • Testing Pig scripts with Punit
  • Aviation use-case in PIG
  • Pig Demo of Healthcare Dataset
  • Introduction to Apache Hive
  • Hive vs Pig
  • Hive Architecture and Components
  • Hive Metastore
  • Limitations of Hive
  • Comparison with Traditional Database
  • Hive Data Types and Data Models
  • Hive Partition
  • Hive Bucketing
  • Hive Tables
  • Importing Data
  • Querying Data & Managing Outputs
  • Hive Script & Hive UDF
  • Retail use case in Hive
  • Hive Demo on Healthcare Dataset
  • Hive QL: Joining Tables, Dynamic Partitioning
  • Custom MapReduce Scripts
  • Hive Indexes and views
  • Hive Query Optimizers
  • Hive Thrift Server
  • Hive UDF
  • Apache HBase: Introduction to NoSQL Databases and HBase
  • HBase v/s RDBMS
  • HBase Components
  • HBase Architecture
  • HBase Run Modes
  • HBase Configuration
  • HBase Cluster Deployment
  • HBase Data Model
  • HBase Shell
  • HBase Client API
  • Hive Data Loading Techniques
  • Apache Zookeeper Introduction
  • ZooKeeper Data Model
  • Zookeeper Service
  • HBase Bulk Loading
  • Getting and Inserting Data
  • HBase Filters
  • What is Spark
  • Spark Ecosystem
  • Spark Components
  • Spark Components
  • Why Scala
  • What is Scala
  • SparkContext
  • Spark RDD
  • Oozie
  • Oozie Components
  • Oozie Workflow
  • Scheduling Jobs with Oozie Scheduler
  • Demo of Oozie Workflow
  • Oozie Coordinator
  • Oozie Commands
  • Oozie Web Console
  • Oozie for MapReduce
  • Combining flow of MapReduce Jobs
  • Hive in Oozie
  • Hadoop Project Demo
  • Hadoop Talend Integration

About Big Data & Hadoop Training

Hadoop is an Apache project (i.e. an open source software) to store & process Big Data. Hadoop stores Big Data in a distributed & fault tolerant manner over commodity hardware. Afterwards, Hadoop tools are used to perform parallel data processing over HDFS (Hadoop Distributed File System).
As organisations have realized the benefits of Big Data Analytics, so there is a huge demand for Big Data & Hadoop professionals. Companies are looking for Big data & Hadoop experts with the knowledge of Hadoop Ecosystem and best practices about HDFS, MapReduce, Spark, HBase, Hive, Pig, Oozie, Sqoop & Flume.
Hadoop Training is designed to make you a certified Big Data practitioner by providing you rich hands-on training on Hadoop Ecosystem. This Hadoop developer certification training is stepping stone to your Big Data journey and you will get the opportunity to work on various Big data projects

  • In-depth knowledge of Big Data and Hadoop including HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator) & MapReduce
  • Comprehensive knowledge of various tools that fall in Hadoop Ecosystem like Pig, Hive, Sqoop, Flume, Oozie, and HBase
  • The capability to ingest data in HDFS using Sqoop & Flume, and analyze those large datasets stored in the HDFS
  • Projects which are diverse in nature covering various data sets from multiple domains such as banking, telecommunication, social media, insurance, and e-commerce
  • Rigorous involvement of a Hadoop expert throughout the Big Data Hadoop Training to learn industry standards and best practices

Big Data Hadoop Certification Training will help you to become a Big Data expert. It will hone your skills by offering you comprehensive knowledge on Hadoop framework, and the required hands-on experience for solving real-time industry-based Big Data projects. During Big Data & Hadoop course you will be trained by our expert instructors to:

  • Master the concepts of HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator), & understand how to work with Hadoop storage & resource management.
  • Understand MapReduce Framework
  • Implement complex business solution using MapReduce
  • Learn data ingestion techniques using Sqoop and Flume
  • Perform ETL operations & data analytics using Pig and Hive
  • Implementing Partitioning, Bucketing and Indexing in Hive
  • Understand HBase, i.e a NoSQL Database in Hadoop, HBase Architecture & Mechanisms
  • Integrate HBase with Hive
  • Schedule jobs using Oozie
  • Implement best practices for Hadoop development
  • Understand Apache Spark and its Ecosystem
  • Software Developers, Project Managers
  • Software Architects
  • ETL and Data Warehousing Professionals
  • Data Engineers
  • Data Analysts & Business Intelligence Professionals
  • DBAs and DB professionals
  • Senior IT Professionals
  • Testing professionals
  • Mainframe professionals
  • Hadoop Market is expected to reach $99.31B by 2022 at a CAGR of 42.1% -Forbes
  • McKinsey predicts that by 2018 there will be a shortage of 1.5M data experts
  • Average Salary of Big Data Hadoop Developers is $97k

Frequently Asked Question's

Big Data Hadoop is one of the new age technological frameworks that is being widely used in the industry wherever there is a demand to hold, process and store large volumes of data. It is being looked at as one of the hottest technologies to up-scale with for any technology professional. Data is indeed the new oil. Learning and getting certified in Hadoop will make your resume stand out and help you in discovering better job opportunities.

Big Data Hadoop Certification training is meant to help you learn and master the entire hadoop ecosystem. With our industry relevant course catalog, we make sure that the learning is in line with how the technology is being used in the market today. We also have real-time projects for our learners to work on for better hands-on. With our cloud lab implementation, we provide the perfect environment for all learners to gain as much practical experience possible.

Please send us an email to info@transgemini.com, and we will answer any queries you may have!.