Big Data Hadoop Training in Chennai

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2 Months

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Big Data stands as a prominent tech trend, shaping crucial business decisions powered by Hadoop. Embrace a promising future through our Big Data and Hadoop Course in Chennai. Explore realms like Data Science, Machine Learning, and IoT, establishing a robust knowledge base for your journey in big data and Hadoop. Enroll in our Big Data and Hadoop Course in Chennai today to enhance your skill set and dive into the dynamic world of big data technologies.

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Want to Master your Skills in Big Data Hadoop ?

Course Highlights


Big Data with Hadoop combines massive datasets and the Hadoop framework, efficiently managing and processing complex information. Hadoop's distributed architecture tackles Big Data challenges by distributing tasks across computer clusters.

Learning Big Data and Hadoop offers several compelling reasons due to their significance in modern data-driven environments:

  • Scale Mastery: Handle massive datasets efficiently.
  • Career Advancement: Unlock diverse job prospects.
  • Insight Extraction: Extract valuable data-driven insights.
  • Problem Solving: Develop skills to tackle complex challenges.
  • Scalability Edge: Manage expanding data seamlessly.

Enrolling in our Big Data and Hadoop Training in Chennai doesn't require strict prerequisites, yet familiarity with programming concepts can be advantageous.

Our Big Data and Hadoop Course in Chennai is well-suited for individuals of all backgrounds,, including:

  • Students
  • Professionals aspiring to transition careers
  • IT experts aiming to elevate their skills
  • Enthusiasts of data and technology
  • Job seekers looking to expand their prospects in the tech field.

    The fees for our Big Data Hadoop Training in Chennai may vary depending on the program level (basic, intermediate, or advanced) and the course format (online or in-person). On average, Big Data Hadoop Course Fees range around 25, 000 INR and lasts around 2 Months including international certification. For precise and up-to-date information on fees, duration, and certification, please contact our Big Data and Hadoop Training in Chennai directly.

    Big Data and Hadoop provide fascinating career opportunities in a wide range of industries. Some roles include:

    • Big Data Engineer
    • Data Scientist
    • Hadoop Administrator
    • Data Analyst
    • Machine Learning Engineer
    • Solution Architect
    • Business Intelligence Analyst
    • Cloud Data Engineer
    • E-commerce: Personalized Product Recommendations
    • Finance: Real-time Fraud Detection
    • Healthcare: Timely Diagnostics with Patient Data
    • Telecommunications: Seamless Network Optimization
    • Energy Management: Efficient Smart Grids
    • Transportation: Traffic Flow Optimization

    Softlogic offers a comprehensive and industry-focused Big Data and Hadoop Course in Chennai equipping individuals with the skills and expertise required to excel in the field of Data Science. By choosing Softlogic, you can ensure top-notch Big Data and Hadoop Training in Chennai with the following benefits:

    • 100+ Real time trainers
    • Fully hands-on training
    • Technology Training
    • Aptitude Training
    • Learn to Code
    • Real Time Projects
    • Learn to Crack Interviews
    • Panel Mock Interviews
    • Unlimited Interviews Completed 1500+ batches
    • 100% job oriented training
    • Life Long Placement Support
    • 60+ hours course duration
    • Industry expert faculties
    • Completed 1500+ batches
    • Certification Guidance
    • Own course materials
    • Resume editing
    • Affordable fees structure

    Big Data Hadoop Syllabus

    Download Syllabus

    Our Big Data and Hadoop Course in chennai provides a comprehensive understanding of the fundamental concepts of Big Data and Hadoop, equipping you with practical expertise in their principles, tools, and efficient strategies. This Big Data and Hadoop Course in Chennai enables you to develop the skills necessary to expertly design, deploy, and optimize robust database solutions using Hadoop's ecosystem and technologies.

    • What is Big Data
    • Evolution of Big Data
    • Benefits of Big Data
    • Operational vs Analytical Big Data
    • Need for Big Data Analytics
    • Big Data Challenges
    • Master Nodes
      • Name Node
      • Secondary Name Node
      • Job Tracker
    • Client Nodes
    • Slaves
    • Hadoop configuration
    • Setting up a Hadoop cluster
    • Introduction to HDFS
    • HDFS Features
    • HDFS Architecture
    • Blocks
    • Goals of HDFS
    • The Name node & Data Node
    • Secondary Name node
    • The Job Tracker
    • The Process of a File Read
    • How does a File Write work
    • Data Replication
    • Rack Awareness
    • HDFS Federation
    • Configuring HDFS
    • HDFS Web Interface
    • Fault tolerance
    • Name node failure management
    • Access HDFS from Java
    • Introduction to Yarn
    • Why Yarn
    • Classic MapReduce v/s Yarn
    • Advantages of Yarn
    • Yarn Architecture
      • Resource Manager
      • Node Manager
      • Application Master
    • Application submission in YARN
    • Node Manager containers
    • Resource Manager components
    • Yarn applications
    • Scheduling in Yarn
      • Fair Scheduler
      • Capacity Scheduler
    • Fault tolerance
    • What is MapReduce
    • Why MapReduce
    • How MapReduce works
    • Difference between Hadoop 1 & Hadoop 2
    • Identity mapper & reducer
    • Data flow in MapReduce
    • Input Splits
    • Relation Between Input Splits and HDFS Blocks
    • Flow of Job Submission in MapReduce
    • Job submission & Monitoring
    • MapReduce algorithms
      • Sorting
      • Searching
      • Indexing
      • TF-IDF
    • What is Hadoop
    • History of Hadoop
    • Hadoop Architecture
    • Hadoop Ecosystem Components
    • How does Hadoop work
    • Why Hadoop & Big Data
    • Hadoop Cluster introduction
    • Cluster Modes
      • Standalone
      • Pseudo-distributed
      • Fully – distributed
    • HDFS Overview
    • Introduction to MapReduce
    • Hadoop in demand
    • Starting HDFS
    • Listing files in HDFS
    • Writing a file into HDFS
    • Reading data from HDFS
    • Shutting down HDFS
    • Listing contents of directory
    • Displaying and printing disk usage
    • Moving files & directories
    • Copying files and directories
    • Displaying file contents
    • Object oriented concepts
    • Variables and Data types
    • Static data type
    • Primitive data types
    • Objects & Classes
    • Java Operators
    • Method and its types
    • Constructors
    • Conditional statements
    • Looping in Java
    • Access Modifiers
    • Inheritance
    • Polymorphism
    • Method overloading & overriding
    • Interfaces
    • Hadoop data types
    • The Mapper Class
      • Map method
    • The Reducer Class
      • Shuffle Phase
      • Sort Phase
      • Secondary Sort
      •  Reduce Phase
    • The Job class
      • Job class constructor
    • JobContext interface
    • Combiner Class
      • How Combiner works
      • Record Reader
      • Map Phase
      • Combiner Phase
      • Reducer Phase
      • Record Writer
    • Partitioners
      • Input Data
      • Map Tasks
      • Partitioner Task
      • Reduce Task
      • Compilation & Execution


    • What is Apache Pig?
    • Why Apache Pig?
    • Pig features
    • Where should Pig be used
    • Where not to use Pig
    • The Pig Architecture
    • Pig components
    • Pig v/s MapReduce
    • Pig v/s SQL
    • Pig v/s Hive
    • Pig Installation
    • Pig Execution Modes & Mechanisms
    • Grunt Shell Commands
    • Pig Latin – Data Model
    • Pig Latin Statements
    • Pig data types
    • Pig Latin operators
    • CaseSensitivity
    • Grouping & Co Grouping in Pig Latin
    • Sorting & Filtering
    • Joins in Pig latin
    • Built-in Function
    • Writing UDFs
    • Macros in Pig
    • What is HBase
    • History Of HBase
    • The NoSQL Scenario
    • HBase & HDFS
    • Physical Storage
    • HBase v/s RDBMS
    • Features of HBase
    • HBase Data model
    • Master server
    • Region servers & Regions
    • HBase Shell
    • Create table and column family
    • The HBase Client API
    • Introduction to Apache Spark
    • Features of Spark
    • Spark built on Hadoop
    • Components of Spark
    • Resilient Distributed Datasets
    • Data Sharing using Spark RDD
    • Iterative Operations on Spark RDD
    • Interactive Operations on Spark RDD
    • Spark shell
    • RDD transformations
    • Actions
    • Programming with RDD
      • Start Shell
      • Create RDD
      • Execute Transformations
      • Caching Transformations
      • Applying Action
      • Checking output
    • GraphX overview
    • Introducing Cloudera Impala
    • Impala Benefits
    • Features of Impala
    • Relational databases vs Impala
    • How Impala works
    • Architecture of Impala
    • Components of the Impala
      • The Impala Daemon
      • The Impala Statestore
      • The Impala Catalog Service
    • Query Processing Interfaces
    • Impala Shell Command Reference
    • Impala Data Types
    • Creating & deleting databases and tables
    • Inserting & overwriting table data
    • Record Fetching and ordering
    • Grouping records
    • Using the Union clause
    • Working of Impala with Hive
    • Impala v/s Hive v/s HBase
    • Introduction to MongoDB
    • MongoDB v/s RDBMS
    • Why & Where to use MongoDB
    • Databases & Collections
    • Inserting & querying documents
    • Schema Design
    • CRUD Operations
    • Introduction to Apache Oozie
    • Oozie Workflow
    • Oozie Coordinators
    • Property File
    • Oozie Bundle system
    • CLI and extensions
    • Overview of Hue
    • What is Hive?
    • Features of Hive
    • The Hive Architecture
    • Components of Hive
    • Installation & configuration
    • Primitive types
    • Complex types
    • Built in functions
    • Hive UDFs
    • Views & Indexes
    • Hive Data Models
    • Hive vs Pig
    • Co-groups
    • Importing data
    • Hive DDL statements
    • Hive Query Language
    • Data types & Operators
    • Type conversions
    • Joins
    • Sorting & controlling data flow
    • local vs mapreduce mode
    • Partitions
    • Buckets
    • Introducing Sqoop
    • Scoop installation
    • Working of Sqoop
    • Understanding connectors
    • Importing data from MySQL to Hadoop HDFS
    • Selective imports
    • Importing data to Hive
    • Importing to Hbase
    • Exporting data to MySQL from Hadoop
    • Controlling import process
    • What is Flume?
    • Applications of Flume
    • Advantages of Flume
    • Flume architecture
    • Data flow in Flume
    • Flume features
    • Flume Event
    • Flume Agent
      •  Sources
      •  Channels
      •  Sinks
    • Log Data in Flume
    • Zookeeper Introduction
    • Distributed Application
    • Benefits of Distributed Applications
    • Why use Zookeeper
    • Zookeeper Architecture
    • Hierarchial Namespace
    • Znodes
    • Stat structure of a Znode
    • Electing a leader
    • Messaging Systems
      • Point-to-Point
      • Publish – Subscribe
    • What is Kafka
    • Kafka Benefits
    • Kafka Topics & Logs
    • Partitions in Kafka
    • Brokers
    • Producers & Consumers
    • What are Followers
    • Kafka Cluster Architecture
    • Kafka as a Pub-Sub Messaging
    • Kafka as a Queue Messaging
    • Role of Zookeeper
    • Basic Kafka Operations
      • Creating a Kafka Topic
      • Listing out topics
      • Starting Producer
      • Starting Consumer
      • Modifying a Topic
      • Deleting a Topic
    • Integration With Spark
    • Introduction to Scala
    • Spark & Scala interdependence
    • Objects & Classes
    • Class definition in Scala
    • Creating Objects
    • Scala Traits
    • Basic Data Types
    • Operators in Scala
    • Control structures
    • Fields in Scala
    • Functions in Scala
    • Collections in Scala
      • Mutable collection
      • Immutable collection

    Trainer's Profile


    Our Mentors are from Top Companies like

    • Our Big Data Hadoop Trainers are highly experienced professionals with a strong technical background in Big Data and cutting-edge Hadoop technologies.
    • They possess advanced knowledge on various Hadoop components, tools and techniques to help learners understand and recognize data structures.
    • Our trainers have the skills to guide and help learners learn to store and process data from disparate sources.
    • They prepare comprehensive guides to help learners efficiently manage real-time Big Data workloads to derive advanced analytics from multiple sources.
    • Our trainers have deep expertise in Hadoop and Apache Spark and are able to effectively prepare learners for Big Data Hadoop certifications.
    • They conduct teaching through examples and teach students on the components, architecture and engineering of Hadoop technology solutions.
    • Our trainers have the ability to configure and deploy the Hadoop Distributed File System (HDFS), develop and design MapReduce programs that can be used to analyze Big Data.
    • They have the competency to work with big data, analytics, cloud platforms, data processing and storage technologies.
    • Our trainers use high-end testing tools and techniques to evaluate student performance and provide feedback to help them improve their skills.
    • They have excellent communication and interpersonal skills to ensure effective coordination and learning with students.
    • The trainers have a collaborative spirit and positive attitude towards helping students gain the knowledge and get placed in top MNCs with ease.

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    Project Practices

    Network Traffic Analysis
    Network Traffic Analysis
    Analyze network traffic data to identify patterns, detect anomalies, or optimize network performance.
    Clickstream Analysis
    Clickstream Analysis
    Analyze website clickstream data to understand user behavior, optimize website design, or improve user experience.
    Energy Consumption Analysis
    Energy Consumption Analysis
    Analyze energy consumption data to identify usage patterns, optimize energy efficiency, and reduce costs.
    Real-Time Sensor Analytics
    Real-time Sensor Analytics
    Analyze IoT sensor data to monitor equipment performance, detect anomalies, and predict failures.
    Customer Churn Prediction
    Customer Churn Prediction
    Create a model to predict customer churn using historical data for proactive retention.
     Log Analysis
    Log Analysis
    Analyze server, application, or network log files for patterns, anomalies, and performance issues.
    Web Scraping and Data Extraction
    Extract data from web sources using Hadoop for analysis and integration.
    Web Scraping And Data Extraction
    Market Basket Analysis
    Market Basket Analysis
    Analyze transaction data to identify customer purchase patterns for targeted marketing and cross-selling.
    Supply Chain Optimization
    Analyze data to improve supply chain efficiency, inventory management, and lead time reduction.
    Supply Chain Optimization

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    Hadoop works by dividing the task or data into smaller units and then distributes the pieces to multiple systems inside a distributed environment. It processes the data in parallel, managing the data distribution across many servers. It then collects and merges the results back into one large volume to give an answer to the query processed.

    The components of Hadoop include Hadoop Common, Hadoop Distributed File System (HDFS), YARN (Yet Another Resource Negotiator), MapReduce, and Hadoop Ozone.

    The HDFS is the Hadoop Distributed File System which stores data on a cluster of nodes or machines. It is the foundation for reliable, large-scale storage of data.

    Using Hadoop provides many benefits, including improved scalability, higher storage capacity, better data security, and improved data privacy. Additionally, it is cost-effective since it uses commodity hardware.

    Big Data Hadoop technology is becoming increasingly popular because of its ability to quickly process large data-sets, making it applicable in many industries such as healthcare, finance, and retail.

    The future is inseparable from big data, as our lives embrace AI, social media, and trends. In eCommerce, big data's role in effortlessly accessing abundant information underscores its importance, with much more potential yet to unfold.

    Yes, SoftLogic provides career placement services after Big Data Hadoop training to help you find the right job for you. Also, SoftLogic offers personalized career guidance and industry expert mentoring for its Big Data Hadoop students.

    The Big Data Hadoop training covers topics such as the fundamentals of Hadoop, HDFS, YARN, Hadoop data loading, using MapReduce, HBase, Oozie, and Hive.

    The Big Data Hadoop training is delivered via interactive classroom sessions and online sessions with live mentors.

    Additional Information


    Technology changes at a swift rate and also the demands in the job scenario. To keep yourself updated you should be aware of the functioning of Big Data Hadoop; you can also be in pace with the changing trends. Controlling data is a challenging task and companies need skilled people to deal with their data to tackle these challenges.

    There is a great demand for Big Data Hadoop experts in big companies. People who can grasp and ace components of Hadoop ecosystems are much in need. The sooner you learn the skill the greater the chance of getting placed in a top organization. This is the exact reason Softlogic, which is the Best Big Data Hadoop Training Institute in Chennai offers you with a holistic course package from fundamental to high-level Hadoop training.

    The salary provided to Big Data Hadoop trained participants is high; when you possess an experience of six months to a year then you can get lucrative salary. Hence, the scope of progressing and earning is really big. Learn Big Data Hadoop from Softlogic and enter into your desired job.

    The practical experience here at Softlogic will be worth and different than that of other Hadoop training Institutes in Chennai. Practical knowledge of Hadoop can be experienced through our virtual software of Hadoop get installed in your machine.As, the software needs minimum system requirements, with the virtual class room set up learning will be easier. Either with your system or with our remote training sessions you can execute the practical sessions of Hadoop.

    The Big Data domain is rising exponentially with tremendous job opportunities and next-gen innovations. Hadoop is one of the popular technologies used in the Big Data platform and equipping professionals is our primary goal for bridging the skills of global big data industries. If you are passionate to build your career in Big Data Hadoop technology, you must know the roles and responsibilities for various job profiles along with their salary options. Following are the popular job titles that create numerous job openings on famous job portals and we equip every individual according to the requirements of each job profile in our Big Data Hadoop Training Institute in Chennai.

    Big Data Architect: Responsible for the complete lifecycle of Hadoop technology that includes requirement analysis, designing of technical architecture, and platform selection. This role involves application design and development, testing of the developed application, and designing the proposed solution. The candidate should have a strong understanding of the pros and cons of the Hadoop platform along with use cases and recommendations. The average salary of a Big Data Architect with Hadoop skills is around US$145,286 per annum. Equip your big data skills in our Hadoop Training in Chennai with Hands-on Exposure to perform well as Big Data Architect in top companies.

    Hadoop Data Engineer: Responsible for Hadoop Development along with its scope to deliver various big data solutions for global clients. The role is involved in the designing of solutions on high-level architecture. They must know about technical communications between clients and internal systems. They should be experts in Kafka, Cassandra, and Elasticsearch. The Hadoop Data Engineer will earn around US$135,961 per annum as an average. Discover how to build a cloud-based platform for allowing easy development of new applications through our Big Data Hadoop Training in Chennai with Industry-Valued Certification.

    Big Data Analyst: Responsible for implementing Big Data Analytics for evaluating companies as per their technical performance. The role involves proving useful suggestions and recommendations for the system enhancement. They should focus on issues related to the streaming of live data and data migrations and they should collaborate with data scientists and data architects efficiently. The average salary of a Big Data Analyst with Hadoop skills is around US$ 125, 097 per annum. Gain expertise in ensuring the streamlined implementations of services and profiling along with in-depth knowledge in data processing such as parsing, text annotation, and filtering enrichment by learning in our Big Data Hadoop Training in Chennai with 100% Placement Assistance.

    Big Data Scientist: Responsible for analytical and statistical programming to collect and interpret well with big data. The role involves utilizing the information to develop data-driven solutions for complicated business challenges. They should work efficiently and closely with stakeholders and organization leaders to help in their data-driven business solutions. The Big Data Scientist is earning around US$100,560 Per year as an average. Equip yourself with mining and analyzing data from various company databases to empower product development, business strategies, and market techniques through our Best Hadoop Course in Chennai.

    Database Administrator: Responsible for setting up a Hadoop Cluster, Backup and Recovery, and Maintenance of Hadoop Systems. This role involves keeping track of cluster connectivity and security of Hadoop systems. They are responsible for adding up new users, capacity planning, and screening of Hadoop cluster job performances. The database administrator with Big Data Hadoop skills is earning an average of US$131,691 per annum. Learn to maintain and support with Hadoop Cluster for companies through our experiential-based and Best Hadoop Training in Chennai.

    Database Manager: Responsible for strategic thinking of organizational success by developing and managing data-oriented systems for business operations. This role involves ensuring a high level of data quality and accessibility with business intelligence tools and technologies. They are earning around US$ 146,000 per annum as an average. Learn to manage Business Intelligence and Big Data Analytics in our Hadoop Training Institute in Chennai.

    The major responsibility of a Hadoop Engineer is to work in good coordination with the database team, quality analyst team and network team. They supervise the big data applications and also deal with Apache Frameworks, HDFS sites, YARN sites etc When you get training from the Top Big Data Hadoop Training Center in Chennai you will get the confidence to be a skilled Hadoop Engineer.

    When you get Big Data Hadoop certification from Softlogic you can boost your career prospects. You can eventually work in a reputed company. Hadoop is the path to a number of big data technologies and Softlogic prepares you in such a way that you become adept in this revolution solution for Big data. We know what the industries demand and make you confident to handle diverse Hadoop roles and titles. Hadoop is an easy platform to learn and if you have the passion to make it big in Hadoop, then Softlogic is your best educator. We know the value of our certification and have the responsibility to provide quality training. Learn Hadoop with us for a fat paycheck. Several domain are being impacted by Hadoop and gaining comprehensive training from Softlogic will make you ready for any job title in this field.

    Softlogic makes sure that you learn the current technology from efficient trainers. We are here to fulfill your requirements and assist you learn and progress in your professional and personal life.

    Enhance your big data skills by enrolling in our Hadoop Training Institute in Chennai with 100% Placement Assistance and Industry-Accredited Course Completion Certification.

    Want to Master your skills in Big Data Hadoop ?