Big Data Hadoop Certification | Hadoop Online Training by Vinsys

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big data hadoop certification

Course includes 40 hours of Virtual or Instructor-led Training

Real-life industry projects using Hadoop Training on Yarn, MapReduce, Pig, Hive, Impala, HBase, and Apache Spark

Getting hands-on practice on CloudLab through <em>Big Hadoop Data Training</em> camp

Big Data Hadoop Certification is globally accepted

Overview Learning Objectives Who Should Attend Prerequisite Outline

Course Overview

This Big Data Hadoop course training is designed to equip participants with comprehensive knowledge and practical skills in handling big data effectively. The course begins with an introduction to big data concepts, exploring the challenges and opportunities it presents in contemporary data-driven environments. Participants will delve into the fundamentals of Hadoop, understanding its architecture, ecosystem components, and distributed computing principles.

Throughout the course, emphasis is placed on hands-on learning, with practical exercises and real-world case studies to reinforce theoretical concepts. Participants will learn to install, configure, and manage Hadoop clusters, gaining proficiency in utilizing Hadoop Distributed File System (HDFS) for storage and MapReduce for parallel processing of large datasets.

Furthermore, the course covers advanced topics such as Hadoop ecosystem tools like Apache Hive, Apache Pig, Apache Spark, and Apache HBase for data processing, querying, and analysis. Participants will explore techniques for optimizing Hadoop performance, troubleshooting common issues, and implementing security measures to safeguard big data infrastructure.

By the end of the course, participants will have the skills and expertise to harness the power of Hadoop for managing and analyzing big data efficiently, enabling them to make informed business decisions and drive innovation in their organizations.

Course Objectives

Upon completing the course, you will be able to:

●   Develop a comprehensive understanding of foundational Big Data concepts and principles.
●   Explore the intricate architecture and diverse components comprising the Hadoop ecosystem.
●   Master the intricacies of the MapReduce programming paradigm for efficient data processing.
●   Delve into the intricacies of HDFS (Hadoop Distributed File System) and its role in data storage and retrieval.
●   Gain practical insights into data processing techniques using Hive and Pig for analytics and query processing.
●   Acquire proficiency in data import/export operations through Sqoop for seamless data integration.
●   Cultivate the skills necessary to effectively manage and analyze large-scale datasets in a distributed computing environment.
●   Develop expertise in Hadoop administration and troubleshooting to ensure smooth operation and performance optimization.
●   Understand the seamless integration possibilities of Hadoop with complementary technologies and frameworks.
●   Prepare to tackle real-world Big Data challenges and projects with confidence and competence.

Audience

This beginner’s course is for those who are interested in Big Data. You'll gain insights into the nature of Big Data, its components, and why Hadoop stands out as a key tool. Explore various elements of the Hadoop ecosystem, including MapReduce, HDFS, Hive, Pig, Sqoop, and more.

●   IT professionals
●   Mainframe professionals
●   Data professionals
●   Project managers
●   Software architects
●   Programming developers
●   Experienced working professionals
●   Mainframe professionals
●   Architects
●   Testing professionals
●   Business intelligence professionals
●   Data warehousing professionals
●   Analytics professionals
●   Graduates
●   Undergraduates eager to learn the latest Big Data technology

Prerequisite

Candidates aspiring to learn Big Data need to have prior knowledge of SQL and Core Java.

Course Outline

Data Ingest

The skills to transfer data between external systems and your cluster
Import and export data between an external RDBMS and your cluster, including the ability to import specific subsets, change the delimiter and file format of imported data during ingest, and alter the data access pattern.
Ingest real-time and near-real time (NRT) streaming data into HDFS, including the ability to distribute to multiple data sources and convert data on ingest from one format to another
Load data into and out of HDFS using the Hadoop File System (FS) commands

Transform, Stage, Store

Convert a set of data values in a given format stored in HDFS into new data values and/or a new data format and write them into HDFS or Hive/HCatalog
Convert data from one file format to another
Convert data from one set of values to another
Change the data format of values in a data set
Partition an existing data set according to one or more partition keys

Data Analysis

Filter, sort, join, aggregate, and/or transform one or more data sets in a given format stored in HDFS to produce a specified result. The queries will include complex data types. The implementation of external libraries, partitioned data and require the use of metadata from Hive/HCatalog.
Write a query to aggregate multiple rows of data
Write a query to calculate aggregate (e.g., average or sum)
Write a query to filter data
Write a query that produces sorted data
Write a query that joins multiple data sets
Read and/or create a Hive or an HCatalog table from existing data in HDFS

Workflow

The ability to create and execute various jobs and actions that move data towards greater value and use in a system
Create and execute a linear workflow with actions that include Hadoop jobs, Hive jobs, Pig jobs, custom actions, etc
Create and execute a branching workflow with actions that include Hadoop jobs, Hive jobs, Pig jobs, custom action, etc
Orchestrate a workflow to execute regularly at predefined times, including workflows that have data dependencies

Mr. Jayvant Desale

SME

Hortonworks Certified Apache Hadoop 2.0 Developer,certified MapR Developing Hadoop Applications

Course Advisor

SME with an uncanny ability to slide into any domain/technology and quickly carve out workable IT solutions that create value. Has 13 years of proven track record in Enterprise-class Product Development for complex verticals, such Banking (FI and Payment Gateways), IT Governance & Management, Manufacturing, and Pharmaceuticals. Currently engaged in the field of Big Data Solutions - Committed to enabling IT teams in the deployment of Big Data Technologies, by the way of training, consulting, and architecting solutions on Apache stack: Hadoop and No-SQL

Choose Your Preferred Mode

Online Training

5-days Instructor-led Online Training
Experienced Subject Matter Experts
Approved and Quality Ensured Training Material
24*7 Leaner Assistance And Support

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Corporate Training

Customized Training Across Various Domains
Instructor-Led Skill Development Program
Ensure Maximum ROI for Corporates
24*7 Learner Assistance and Support

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FAQ’s

What is Big Data Hadoop?

Big Data Hadoop is an open-source framework designed to store, process, and analyze large volumes of structured and unstructured data across distributed computing clusters.

Why should I learn Hadoop?

Learning Hadoop opens doors to opportunities in big data analytics, data engineering, and data science roles. It enables you to work with vast amounts of data efficiently and gain insights that drive business decisions.

Do I need programming experience to enroll in the Big Data Hadoop Course?

While programming experience, particularly in languages like Java and Python, can be beneficial, it's not a strict requirement. The course covers the fundamentals of programming within the Hadoop ecosystem, making it accessible to learners with varying levels of programming expertise.

What topics are covered in the Big Data Hadoop Course?

The course covers essential concepts such as Hadoop architecture, HDFS (Hadoop Distributed File System), MapReduce programming paradigm, Apache Hive, Apache Pig, Apache Spark, HBase, and YARN (Yet Another Resource Negotiator).

How will the Big Data Hadoop Course benefit my career?

By completing the course, you'll acquire valuable skills in handling big data technologies, which are in high demand across industries. This certification can significantly enhance your career prospects in fields such as data engineering, data analysis, and machine learning.

Is hands-on experience included in the course?

Yes, the Big Data Hadoop Course includes practical exercises and projects that allow you to apply your knowledge in real-world scenarios. Hands-on experience is crucial for mastering the concepts and preparing for practical challenges in the field.

What are the prerequisites for enrolling in the Big Data Hadoop Course?

While there are no strict prerequisites, a basic understanding of database concepts and familiarity with Linux environments can be advantageous. Additionally, having a fundamental grasp of programming concepts will facilitate your learning journey.

How long does it take to complete the Big Data Hadoop Course?

The duration of the course is 5-days

Will I receive a certification upon completion of the course?

Yes, upon successful completion of the Big Data Hadoop Course and associated assessments, you will receive a certification that validates your proficiency in Hadoop and related technologies.

How can I enroll in the Big Data Hadoop Course?

To enroll in the course, visit our website or contact our enrollment team. You'll receive guidance on registration, course fees, and upcoming batches. Don't hesitate to reach out if you have any further inquiries or require assistance with the enrollment process.