Big Data and Hadoop Course Training in Tampa, FL, United States

Big Data Analysis with Hadoop

  • 30 hours of Instructor-led training classes
  • Immersive hands-on learning
  • Get experiential knowledge of big data concepts and tools
  • Learn to extract information with Hadoop MapReduce using HDFS, Pig, Hive, etc.
Group Discount

Who should attend

  • Architects and developers who design, develop and maintain Hadoop-based solutions
  • Data Analysts, BI Analysts, BI Developers, SAS Developers
  • Others who analyze Big Data in Hadoop environment
  • Consultants who are actively involved in a Hadoop Project
  • Java software engineers who develop Java MapReduce applications for Hadoop 2.0.

KnowledgeHut Experience

Instructor-led Live Classroom

Interact with instructors in real-time— listen, learn, question and apply. Our instructors are industry experts and deliver hands-on learning.

Curriculum Designed by Experts

Our courseware is always current and updated with the latest tech advancements. Stay globally relevant and empower yourself with the latest training!

Learn through Doing

Learn theory backed by practical case studies, exercises and coding practice. Get skills and knowledge that can be effectively applied.

Mentored by Industry Leaders

Learn from the best in the field. Our mentors are all experienced professionals in the fields they teach.

Advance from the Basics

Learn concepts from scratch, and advance your learning through step-by-step guidance on tools and techniques.

Code Reviews by Professionals

Get reviews and feedback on your final projects from professional developers.

Curriculum

Learning objectives:

This module will introduce you to the various concepts of big data analytics, and the seven Vs of big data—Volume, Velocity, Veracity, Variety, Value, Vision, and Visualization. Explore big data concepts, platforms, analytics, and their applications using the power of Hadoop 3.

Topics:

  • Understanding Big Data
  • Types of Big Data
  • Difference between Traditional Data and Big Data
  • Introduction to Hadoop
  • Distributed Data Storage In Hadoop, HDFS and Hbase
  • Hadoop Data processing Analyzing Services MapReduce and spark, Hive Pig and Storm
  • Data Integration Tools in Hadoop
  • Resource Management and cluster management Services

Hands-on: No hands-on

Learning Objectives:

Here you will learn the features in Hadoop 3.x and how it improves reliability and performance. Also, get introduced to MapReduce Framework and know the difference between MapReduce and YARN.

Topics:

  • Need of Hadoop in Big Data
  • Understanding Hadoop And Its Architecture
  • The MapReduce Framework
  • What is YARN?
  • Understanding Big Data Components
  • Monitoring, Management and Orchestration Components of Hadoop Ecosystem
  • Different Distributions of Hadoop
  • Installing Hadoop 3

Hands-on: Install Hadoop 3.x

Learning Objectives: Learn to install and configure a Hadoop Cluster.

Topics:

  • Hortonworks sandbox installation & configuration
  • Hadoop Configuration files
  • Working with Hadoop services using Ambari
  • Hadoop Daemons
  • Browsing Hadoop UI consoles
  • Basic Hadoop Shell commands
  • Eclipse & winscp installation & configurations on VM

Hands-on: Install and configure eclipse on VM

Learning Objectives:

Learn about various components of the MapReduce framework, and the various patterns in the MapReduce paradigm, which can be used to design and develop MapReduce code to meet specific objectives.

Topics:

  • Running a MapReduce application in MR2
  • MapReduce Framework on YARN
  • Fault tolerance in YARN
  • Map, Reduce & Shuffle phases
  • Understanding Mapper, Reducer & Driver classes
  • Writing MapReduce WordCount program
  • Executing & monitoring a Map Reduce job

Hands-on :Use case - Sales calculation using M/R

Learning Objectives:

Learn about Apache Spark and how to use it for big data analytics based on a batch processing model. Get to know the origin of DataFrames and how Spark SQL provides the SQL interface on top of DataFrame.

Topics:

  • SparkSQL and DataFrames
  • DataFrames and the SQL API
  • DataFrame schema
  • Datasets and encoders
  • Loading and saving data
  • Aggregations
  • Joins

Hands-on:

Look at various APIs to create and manipulate DataFrames and dig deeper into the sophisticated features of aggregations, including groupBy, Window, rollup, and cubes. Also look at the concept of joining datasets and the various types of joins possible such as inner, outer, cross, and so on

Learning Objectives:

Understand the concepts of the stream-processing system, Spark Streaming, DStreams in Apache Spark, DStreams, DAG and DStream lineages, and transformations and actions.

Topics:

  • A short introduction to streaming
  • Spark Streaming
  • Discretized Streams
  • Stateful and stateless transformations
  • Checkpointing
  • Operating with other streaming platforms (such as Apache Kafka)
  • Structured Streaming

Hands-on: Process Twitter tweets using Spark Streaming

Learning Objectives:

Learn to simplify Hadoop programming to create complex end-to-end Enterprise Big Data solutions with Pig.

Topics:

  • Background of Pig
  • Pig architecture
  • Pig Latin basics
  • Pig execution modes
  • Pig processing – loading and transforming data
  • Pig built-in functions
  • Filtering, grouping, sorting data
  • Relational join operators
  • Pig Scripting
  • Pig UDF's

Learning Objectives:

Learn about the tools to enable easy data ETL, a mechanism to put structures on the data, and the capability for querying and analysis of large data sets stored in Hadoop files.

Topics:

  • Background of Hive
  • Hive architecture
  • Hive Query Language
  • Derby to MySQL database
  • Managed & external tables
  • Data processing – loading data into tables
  • Hive Query Language
  • Using Hive built-in functions
  • Partitioning data using Hive
  • Bucketing data
  • Hive Scripting
  • Using Hive UDF's

Learning Objectives:

Look at demos on HBase Bulk Loading & HBase Filters. Also learn what Zookeeper is all about, how it helps in monitoring a cluster & why HBase uses Zookeeper.

Topics:       

  • HBase overview
  • Data model
  • HBase architecture
  • HBase shell
  • Zookeeper & its role in HBase environment
  • HBase Shell environment
  • Creating table
  • Creating column families
  • CLI commands – get, put, delete & scan
  • Scan Filter operations

Learning Objectives:

Learn how to import and export data between RDBMS and HDFS.

Topics:

  • Importing data from RDBMS to HDFS
  • Exporting data from HDFS to RDBMS
  • Importing & exporting data between RDBMS & Hive tables

Learning Objectives:

Understand how multiple Hadoop ecosystem components work together to solve Big Data problems. This module will also cover Flume demo, Apache Oozie Workflow Scheduler for Hadoop Jobs.

Topics:

  • Overview of Oozie
  • Oozie Workflow Architecture
  • Creating workflows with Oozie
  • Introduction to Flume
  • Flume Architecture
  • Flume Demo

Learning Objectives:

Learn to constantly make sense of data and manipulate its usage and interpretation; it is easier if we can visualize the data instead of reading it from tables, columns, or text files. We tend to understand anything graphical better than anything textual or numerical.

Topics:

  • Introduction
  • Tableau
  • Chart types
  • Data visualization tools

Hands-on: Use Data Visualization tools to create a powerful visualization of data and insights.

Learning Objectives:

Learn a simple way to access servers, storage, databases, and a broad set of application services over the internet.

Topics:

  • Cloud computing basics
  • Concepts and terminology
  • Goals and benefits
  • Risks and challenges
  • Roles and boundaries
  • Cloud characteristics
  • Cloud delivery models
  • Cloud deployment models

Hands-on: Implement Cloud computing and deploy models.

Meet your instructors

Tarun

Tarun Sukhani

Director

TarunSukhani is an IT executive, educator, author, speaker, data scientist, security expert, agile coach, polyglot coder, and entrepreneur with over 20 years of combined professional experience both in the U.S. and internationally. As a seasoned veteran, his expertise lies in leading teams and being a counsellor and mentor in the design and delivery of highly scalable, concurrent, and performant enterprise software solutions with budgets of up to $100 million. 
He is adept at building productive, self-managing agile teams with predictable velocities and delivery timeframes. Particularly skilled in all phases of the SDLC/ALM, Tarun specializes in Agile (XP, SAFe, Lean, Scrum, Kanban, and Scrumban) and traditional (PMI and PRINCE2) project management frameworks and methodologies and is an expert tutor who brings out the best in his students. He is a much sought-after corporate trainer  for many organizations, with many niche certifications under his belt, including Raspberry Pi IoT with Node-Red, Hydroponics and Aquaponics, R Statistics and several others.

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Project

Analysis of Aadhar

DESCRIPTION- Aadhar card Database is the largest biometric project of its kind currently in the world. The Indian government needs to analyse the database, divide the data state-wise and calculate how many people are still not registered, how many cards are approved and how they can bifurcate it according to gender, age, location, etc. 

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Analyzing in Banking Sector (CITI Bank)

DESCRIPTION- The Citi group of banks is one of the world’s largest providers of financial services, In recent years, they adopted a fully Big Data-driven approach to drive business growth and enhance the services provided to customers because traditional systems are not able to handle the huge amount of data pouring in. Using Hadoop, they will be storing and analyzing banking data to come up with multiple insights. 

Read More

E-commerce Website based Analysis (Clickstream Analysis)

DESCRIPTION- On Ecommerce Web sites, clickstream analysis is the process of collecting, analyzing and reporting aggregate data about which pages a website visitor visits and in what order. With increasing number of ecommerce businesses, there is a need to track and analyse clickstream data. When using traditional databases to load and process clickstream data, there are several complexities in storing and streaming customer information and it also requires a huge amount of processing time to analyse and visualize it. 

Read More

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FAQs

The Course

Hadoop has now become the de facto technology for storing, handling, evaluating and retrieving large volumes of data. Big Data analytics has proven to provide significant business benefits and more and more organizations are seeking to hire professionals who can extract crucial information from structured and unstructured data. KnowledgeHut brings you a full-fledged course on Big Data Analytics and Hadoop development that will teach you how to develop, maintain and use your Hadoop cluster for organizational benefit.

This course will prepare you for everything you need to learn about Big Data while gaining practical experience on Hadoop.

After completing our course, you will be able to understand:

  • What is Big Data, its need and applications in business
  • The tools used to extract value from Big data
  • The basics of Hadoop including fundamentals of HDFs and MapReduce
  • Navigating the Hadoop Ecosystem
  • Using various tools and techniques to analyse Big Data
  • Extracting data using Pig and Hive
  • How to increase sustainability and flexibility across the organization’s data sets
  • Developing Big Data strategies for promoting business intelligence

There are no restrictions but participants would benefit if they have elementary computer knowledge.

Yes, KnowledgeHut offers this training online.

Your instructors are Hadoop experts who have years of industry experience.

Finance Related

Any registration cancelled within 48 hours of the initial registration will be refunded in FULL (please note that all cancellations will incur a 5% deduction in the refunded amount due to transactional costs applicable while refunding) Refunds will be processed within 30 days of receipt of written request for refund. Kindly go through our Refund Policy for more details: http://www.knowledgehut.com/refund

KnowledgeHut offers a 100% money back guarantee if the candidate withdraws from the course right after the first session. To learn more about the 100% refund policy, visit our Refund Policy.

The Remote Experience

In an online classroom, students can log in at the scheduled time to a live learning environment which is led by an instructor. You can interact, communicate, view and discuss presentations, and engage with learning resources while working in groups, all in an online setting. Our instructors use an extensive set of collaboration tools and techniques which improves your online training experience.

Minimum Requirements:

  •   Operating system such as Mac OS X, Windows or Linux
  •   A modern web browser such as FireFox, Chrome
  •   Internet Connection

What You Will Learn

Prerequisites

Basic programming knowledge is desired though not a prerequisite for attending this course

Have More Questions?

Big Data and Hadoop Course Course in Tampa, FL

Big Data and Hadoop

Business organizations depend on Big Data for effective planning and decision making. A popular technology for managing, storing, handling and retrieving huge volumes of data is Hadoop. Hadoop is a framework that aids in deep analytics of Big Data. Big Data and Hadoop platform help in storing, handling and retrieving a huge amount of data from a variety of applications. It is also a powerful tool that aids in deep analytics. KnowledgeHut is the for the Big Data and Hadoop course in Tampa.

Learn the Major concepts of Hadoop

If the aspirant is looking forward to a brilliant career option, then enrol with the academy for Big Data and Hadoop classes in Tampa and enjoy the privilege of high-quality infra and access to knowledge. World class tutors and certified trainers are appointed to provide the candidate with complete knowledge. The classrooms for Big Data and Hadoop course in Tampa are well equipped for the regular candidates, but for those who are working people, online facility ensures their need. You may look up for the details of Big Data and Hadoop online in Tampa on the website.

All the major concepts of Hadoop are covered in the workshop and practice sessions during the Big Data and Hadoop training in Tampa. The associated frameworks of Hadoop like ApachePig™, ApacheHive™, Sqoop, Flume, Oozie, et al. are also included in the lectures. The students gain a practical understanding of the concepts of Big Data and Hadoop training in Tampa by solving the demo exercises under the guidance of the instructor.

There is a growing demand for Hadoop professionals as business organizations discover the need for Big Data and deep analytics. This is why the Big Data and Hadoop certification in Tampa is very popular. Register for the course today.