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    Big Data Hadoop

      Home » Courses » Project Based Big Data Hadoop Training in Noida & Best Big Data Hadoop Course in Noida

    Project Based Big Data Hadoop Training in Noida & Best Big Data Hadoop Course in Noida

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    python and ml training courses
    Big Data Hadoop, Technology
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    Big data Hadoop

    Project Based Big Data Hadoop Training in Noida & Best Big Data Hadoop Course in Noida


    4.9 Star Rating: Very Good  5.0 out of 5  based on 1065 ratings.213 user reviews.
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    We deliver Big data Hadoop Training in Noida for students as well as professionals who want to make career in this field. Hadoop is the open-source framework used for running applications and storing data on clusters of commodity hardware. It offers enormous storage for all kinds of data, massive processing power and the capability to manage virtually limitless concurrent job or task.

    We are the best option for students who are looking for Best Big data Hadoop Training in Noida. Our object-oriented &amp; live project based Big data Hadoop Training Course in Noida is designed according to the requirements of the corporate world so that learners are prepared for their job after completion of the training.</p.

    Big data simply means enormous big data; it is a group of large datasets that can’t be dealt with using traditional computing methods. Big data is not just a data; to be more precise it has become a comprehensive subject, which involves various techniques, tools, and frameworks. Thus Big  Data includes high velocity, huge volume, and extensible variety of data. The data can be of three types.</p.

    • Structured data: Relational data.
    • Semi Structured data: XML data.
    • Unstructured data: Word, PDF, Text, Media Logs.

    Our Advantage

    We have more than 15 years of Industrial experience in providing training and hence delivers high quality Big Data Hadoop Certification Training in Noida. Our academic curriculum is designed in such a way that it includes basic as well as advanced topics of Big Data Hadoop & full focus is placed in imparting practical training to students. We have the group of Industry experts to help students with their training program so that they get full guidance and support in completing their live projects.

    Our Big Data Training Institute in Noida has world-class infrastructure and labs to offer the best learning experience to our students. Furthermore, we provide them with international certification after the completion of the training. Our training program is available in classroom mode, weekend training, fast track training as well as Online Big Data Hadoop Training in Noida.

    Why choose us?

    We are the excellent Big data Hadoop Training Course provider offers you following benefits:

    • No.1 Big Data Hadoop training center in Noida
    • More than 15 year of industry experience
    • Big Data Hadoop classes in Noida as per industrial norms
    • World-class labs and equipment
    • International vendor certified trainer
    • Full-time, weekend, as well as customized training
    • Free personality development course and interview tips
    • Course completion certificate which is recognized globally
    • Free study materials
    • Highly affordable fees

    Placement Assistance

    Apart from providing the best industrial Training in Big Data Hadoop, we are also the pioneer in providing the assured placement assistance to our students after completing of the training. Our Big Data Hadoop placement training in Noida have an enthusiastic and committed placement cell which assist the students in every step of their placement process and helps them in obtaining the job at reputed companies. Right from designing the remarkable resume, we also give free session on mock interviews, personality development, seminars, &amp; group discussions so that our students are fully prepared to bag the job at top rated MNC. Till date, we have placed hundreds of our students in some of the biggest MNCs including Wipro, Infosys, TCS, HCL, Accenture, etc.

    Our enormous experience in the field allows us to comprehend the current market requirements of the corporate world. We apply this knowledge while planning the course curriculum for basic and advanced topics. Big Data Hadoop placement training in Noida makes sure that our students have the potential of getting selected at the best of MNCs with handsome packages. By combining the best of infrastructure, faculty, curriculum which focuses on practical knowledge, and affordable fees, CETPA ensures that each of our students get to realize their dream of working in the IT industry.

    To know more about our Summer Training in Big Data Hadoop  other courses we offer, get in touch with us or simply visit our training center!

    We Serve the Best Big Data Hadoop Course at Multiple Locations

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    Course Features

    • Lectures 97
    • Quizzes 0
    • Duration 50 hours
    • Skill level All levels
    • Language English
    • Students 2
    • Assessments Yes
    CoursesTechnologyBig Data HadoopProject Based Big Data Hadoop Training in Noida & Best Big Data Hadoop Course in Noida
    •  Introduction to Big Data 0/10

      • Lecture1.1
        What is RDBMS?
      • Lecture1.2
        What is Big Data?
      • Lecture1.3
        Problems with the RDBMS and other existing systems
      • Lecture1.4
        Requirement for the new approach
      • Lecture1.5
        Solution to the problem with huge
      • Lecture1.6
        Difference between relational databases and NoSQL type databases
      • Lecture1.7
        Need of NoSQL type databases
      • Lecture1.8
        Problems in processing of Big Data with the traditional systems
      • Lecture1.9
        How to process and store Big Data?
      • Lecture1.10
        Where to use Hadoop?
    •  Hadoop Basic Concepts 0/10

      • Lecture2.1
        What is Hadoop?
      • Lecture2.2
        Why to use Hadoop?
      • Lecture2.3
        Architecture of Hadoop
      • Lecture2.4
        Difference between Hadoop 1.x and Hadoop 2.x
      • Lecture2.5
        What is YARN?
      • Lecture2.6
        Advantage of Hadoop 2.x over Hadoop 1.x
      • Lecture2.7
        Use cases for using Hadoop
      • Lecture2.8
        Components of Hadoop
      • Lecture2.9
        Hadoop Distributed File System (HDFS)
      • Lecture2.10
        Map Reduce
    • Hadoop Distributed File System 0/7

      • Lecture3.1
        Components of HDFS
      • Lecture3.2
        What was the need of HDFS?
      • Lecture3.3
        Data Node, Name Node, Secondary name Node
      • Lecture3.4
        High Availability and Fault Tolerance
      • Lecture3.5
        Command Line interface
      • Lecture3.6
        Data Ingestion
      • Lecture3.7
        Hadoop Commands
    • Hadoop Cluste 0/7

      • Lecture4.1
        Installation of Hadoop
      • Lecture4.2
        Understanding the Configuration of Hadoop
      • Lecture4.3
        Starting the Hadoop related Processes
      • Lecture4.4
        Visualization of Hadoop in UI
      • Lecture4.5
        Writing the files to the HDFS
      • Lecture4.6
        Reading the files from the Hadoop Cluster
      • Lecture4.7
        Work flow of the JoB
    • HBASE 0/5

      • Lecture5.1
        What is HBASE?
      • Lecture5.2
        Why HBASE is needed?
      • Lecture5.3
        HBASE Architecture and Schema Design
      • Lecture5.4
        Column Oriented and Row Oriented Databases
      • Lecture5.5
        HBASE Vs RDBMS
    • Map Reduce Programming 0/9

      • Lecture6.1
        Overview of the Map Reduce
      • Lecture6.2
        History of Map Reduce
      • Lecture6.3
        Flow of Map Reduce
      • Lecture6.4
        Working of Map Reduce with simple example
      • Lecture6.5
        Difference Between Map phase and Reduce phase
      • Lecture6.6
        Concept of Partition and Combiner phase in Map Reduce
      • Lecture6.7
        Submission of a Map Reduce job in Hadoop cluster and it’s completion
      • Lecture6.8
        File support in Hadoop
      • Lecture6.9
        Achieving different goals using Map R educe programs
    • Sqoop 0/7

      • Lecture7.1
        What is Sqoop ?
      • Lecture7.2
        Use Case for Sqoop?
      • Lecture7.3
        Configuring Sqoop
      • Lecture7.4
        Importing and Exporting Data using Sqoop
      • Lecture7.5
        Importing data into Hive using Sqoop
      • Lecture7.6
        Code Generation using sqoop
      • Lecture7.7
        Using Map Reduce with the Sqoop
    • PIG 0/9

      • Lecture8.1
        Introduction to Apache Pig
      • Lecture8.2
        Architecture of Apache Pig
      • Lecture8.3
        Why Pig?
      • Lecture8.4
        RDBMS Vs Apache PIG
      • Lecture8.5
        Loading data using PIG
      • Lecture8.6
        Different Modes of execution of PIG Commands
      • Lecture8.7
        PIG Vs Map Reduce coding
      • Lecture8.8
        Diagnostic operations in Pig
      • Lecture8.9
        Combining and Filtering Operations in Pig
    • Flume 0/8

      • Lecture9.1
        What is Flume?
      • Lecture9.2
        Architecture of Flume
      • Lecture9.3
        Why we need Flume?
      • Lecture9.4
        Problem with traditional export method
      • Lecture9.5
        Configuring Flume
      • Lecture9.6
        Different Channels in Flume
      • Lecture9.7
        Importing data using Flume
      • Lecture9.8
        Using Map Reduce with the Flume
    • HIVE 0/11

      • Lecture10.1
        Introduction to HIVE
      • Lecture10.2
        Architecture of HIVE
      • Lecture10.3
        Why HIVE?
      • Lecture10.4
        RDBMS Vs HIVE
      • Lecture10.5
        Introduction to HiveQL
      • Lecture10.6
        Loading data using HIVE
      • Lecture10.7
        HIVE Vs Map Reduce Coding
      • Lecture10.8
        Different functions supported in HIVE
      • Lecture10.9
        Partitioning, Bucketing in HIVE
      • Lecture10.10
        Hive Built – In Operators and Functions
      • Lecture10.11
        Why do we need Partitioning and Bucketing in HIVE?
    • MongoDB 0/7

      • Lecture11.1
        What is MongoDB?
      • Lecture11.2
        Difference between MongoDB and RDBMS
      • Lecture11.3
        Advantages of MongoDB over RDBMS
      • Lecture11.4
        Installing MongoDB
      • Lecture11.5
        What are Collections and Documents?
      • Lecture11.6
        Creating Databases and Collection s.
      • Lecture11.7
        Working with Databases and Collections
    • Analysis Using R Language 0/7

      • Lecture12.1
        Introduction to R Language
      • Lecture12.2
        Introduction to R Studio
      • Lecture12.3
        Why to use R?
      • Lecture12.4
        R Vs Other Languages
      • Lecture12.5
        Using R to analyze the data extracted using Map Reduce
      • Lecture12.6
        Introduction to ggplot package
      • Lecture12.7
        Plotting the graphs of the extracted data from Map Reduce using R
    • Mini Project to Use Hadoop and Related Technologies on a Dataset 0/0

      No items in this section

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