Big Data Hadoop and Spark

Big Data continues to grow at an exponential rate stretching its wings in almost every other aspect of our lives. With the massive growth in Big Data, it is now the perfect time to launch a career in this promising field. The Big Data Hadoop and Spark course in Dubai train professionals on Hadoop and Spark to help them drive better business decisions and confidently take up any challenges in real-time situations.

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  • 3 weeks | 40 hours Bootcamp
  • Online / Offline / Blended
  • 8 Oct, 2021 / 5 Nov, 2021
  • Additional Program Dates
  • 100K+ Happy Students

(400+ Google Reviews)

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What is this Big Data Hadoop and Spark course all about?

The Big Data Hadoop and Spark course is designed to offer in-depth knowledge of the fundamentals of Spark and the Hadoop ecosystem. This course trains participant on various components of the Hadoop ecosystem that fits into the Big Data processing lifecycle. With the perfect blend of theoretical and practical sessions with industry-based projects, by the end of the course, participants are prepared to take up any challenges while in demanding roles in their workplace.

What is this Big Data Hadoop and Spark course all about?

The Big Data Hadoop and Spark course is designed to offer in-depth knowledge of the fundamentals of Spark and the Hadoop ecosystem. This course trains participant on various components of the Hadoop ecosystem that fits into the B...

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Why is getting trained on Big Data Hadoop and Spark important?

The Big Data Hadoop and Spark course is designed with the perfect blend of strong theoretical and practical training on Hadoop and Spark. By getting trained on Hadoop and Spark, professionals master the concepts and ways to enforce the best practices for Hadoop and Spark development. Through this training, participants get a headstart and are enabled to bag top Hadoop jobs in the Big Data industry.

Why is getting trained on Big Data Hadoop and Spark important?

The Big Data Hadoop and Spark course is designed with the perfect blend of strong theoretical and practical training on Hadoop and Spark. By getting trained on Hadoop and Spark, professionals master the concepts and ways to enforce t...

Read More

Why do companies hire professionals with Big Data Hadoop and Spark certification?

The majority of organizations around the world are now making huge investments in Big Data analytics. This results in increased demand for trained professionals. Companies hire professionals with Hadoop and Spark certification for their expertise in Hadoop cluster architecture and data loading techniques. Their ability to install, set up the Hadoop ecosystem and Spark environment for processing data and performing exploratory queries on data batches make them the need of the hour.

Why do companies hire professionals with Big Data Hadoop and Spark certification?

The majority of organizations around the world are now making huge investments in Big Data analytics. This results in increased demand for trained professionals. Companies hire professionals with Hadoop and Spark c...

Read More

Industry Trends

Hadoop has almost become synonymous with Big Data. The demand for Hadoop technology in the Big Data industry is set to move with an upward curve. The Big Data Hadoop and Spark certification comes with its own set of merits and opportunities in the market. Let us see how.

Market trends Market trends

The Big Data Hadoop market is growing day by day and set for a bright future. As per the Forbes report, the Hadoop and the Big Data market is projected to grow at a CAGR of 28.5% by 2022. With over 97.2% of organizations investing in AI and Big Data, large companies like Cisco, Dell, EY, IBM, Google, Siemens, Twitter, OCBC bank, are looking for Hadoop professionals.

Salary Trend Salary Trends

Big Data is a lucrative career path offering high-paying jobs. Hadoop is the leader in the Big Data category of job postings and Hadoop Developers are among Dubai's most in-demand and highly compensated technical job roles.  Hadoop and Spark are very encouraging in the UAE data analytics sector. The average salary for Big Data professionals with Hadoop skills in Dubai, UAE is AED 224,000 per annum.

Demand & Opportunities

Big Data is growing in its full potential ​resulting in a positive job outlook for professionals with the right skills. Hadoop and Spark have now become the most desired skills in the Big Data industry. The Big Data Hadoop and Spark certification gives an assurance of the necessary competency in related roles, thus making these opportunities easier to avail.

A few of the most-sought Big Data Hadoop and Spark jobs available in the Dubai region (as observed in popular Dubai job portals) follows:

  1. Big Data Hadoop Developers develop and code Hadoop applications to manage and maintain a company's big data
  2. Hadoop Architects create requirement analysis and manage development and deployment across Hadoop applications
  3. Data Analysts analyzes data by creating systems that help users of business to draw out insights and ensure data quality
  4. Spark Big Data Engineers design the architecture of a big data platform and maintain the data pipeline
  5. Spark Developers clean, transform and analyze vast amounts of raw data from various systems using Spark to provide ready-to-use data for developers and business analysts

Course Outcome

Successful completion of the Big Data Hadoop and Spark course will help you to:

  • Gain in-depth knowledge of the Big Data framework using Hadoop and Spark
  • Understand the fundamental concepts of Hadoop and its ecosystem components
  • Understand Spark environment and its data optimization techniques
  • Write programs in the Big Data domain as per system architecture
  • Apply best practices for Hadoop and Spark development

Course Module

Learning objective:

You will get introduced to real-world problems with Big data and will learn how to solve those problems with state-of-the-art tools. Understand how Hadoop offers solutions to traditional processing with its outstanding features. You will get to know Hadoop’s background and different distributions of Hadoop available in the market. Prepare the UNIX Box for the training.

Topics:

Big Data Introduction

  • What is Big Data?
  • Data Analytics
  • Big Data challenges
  • Technologies supported by Big Data

Hadoop Introduction

  • What is Hadoop?
  • History of Hadoop
  • Basic concepts
  • Future of Hadoop
  • The Hadoop distributed file system
  • Anatomy of a Hadoop cluster
  • Breakthroughs of Hadoop
  • Hadoop distributions:
  • Apache Hadoop
  • Cloudera Hadoop
  • Hortonworks Hadoop
  • MapR Hadoop

Hands-On:

  • Installation of a virtual machine using VMPlayer on the host machine
  • Work with some basics UNIX commands needs for Hadoop

Learning objective:

You will get to know how to write and read files in HDFS. Understand how to name node, data node, and secondary name node take part in HDFS architecture. You will also know different ways of accessing HDFS data.

Topics:

  • Blocks and input splits
  • Data replication
  • Hadoop rack awareness
  • Cluster architecture and block placement
  • Accessing HDFS
  • JAVA approach
  • CLI approach

Hands-On:

  • Writes a shell script that writes and reads files in HDFS
  • Changes replication factor at three levels
  • Use Java for working with HDFS
  • Writes different HDFS commands and also admin commands

Learning objective:

Understand different phases in MapReduce including Map, Shuffling, Sorting, and Reduce Phases. Get a deep understanding of the Life Cycle of MR in YARN submission. Learn about the Distributed Cache concept in detail with examples. Write Wordcount MR Program and monitor the Job using Job Tracker and YARN Console. Also, learn about more use cases.

Topics:

  • Basic API concepts
  • The driver class
  • The mapper class
  • The reducer class
  • The combiner class
  • The partitioner class
  • Examining a sample MapReduce program with several examples
  • Hadoop's Streaming API

Hands-On:

  • Learn about writing MR job from scratch, writing different logics in mapper and reducer, and submitting the MR job in standalone and distributed mode
  • Also learn about writing word count MR job, calculating  average salary of the employee who meets certain conditions and sales calculation using MR Hadoop ecosystems

Learning objective:

Understand the importance of Hive in the Big Data world. Different ways of configuring Hive megastore. Learn different types of tables in the hive. Learn how to optimize hive jobs using partitioning and bucketing and passing dynamic arguments to hive scripts. You will get an understanding of Joins, UDFS, Views, etc.

Topics:

  • HIVE concepts
  • HIVE architecture
  • Installing and configuring HIVE
  • Managed tables and external tables
  • Joins in HIVE
  • Multiple ways of inserting data in HIVE tables
  • CTAS, views, alter tables
  • User-defined functions in HIVE
  • HIVE UDF

Hands-On:

  • Executes hive queries in different Modes
  • Creates Internal and External tables
  • Perform query optimization by creating tables with partition and bucketing concepts 
  • Run system-defined and user-defined functions including explode and windows functions

Learning objectives:

Understand different types of NoSQL databases and CAP theorem. Learn different DDL and CRUD operations of HBASE. Understand HBase architecture and Zookeeper Importance in managing HBase. Learns HBase column family optimization and client-side buffering.

Topics:

  • HBase concepts
  • ZOOKEEPER concepts
  • HBase and Region server architecture
  • File storage architecture
  • NoSQL vs SQL
  • Dening Schema and basic operations
  • DDLs
  • DMLs
  • HBase use cases

Hands-On: 

Create HBase tables using shell and perform CRUD operations with JAVA API. Change the column family properties and also perform the sharding process. Also, create tables with multiple splits to improve the performance of the HBase query.

Learning objectives:

Understand flume architecture and its components source, channel, and sinks. Configure flume with socket, file sources, and HDFS and HBase sink. Understand fan in and fan out architecture.

Topics:

  • FLUME concepts
  • FLUME architecture
  • Installation and configurations
  • Executing FLUME jobs

Hands-on:

  • Create flume configuration files and configure with different sources and sinks. Stream twitter data and create a hive table

Learning objective: 

You will see different integrations among the Hadoop ecosystem in a data engineering flow. Also, understand how important it is to create a flow for the ETL process.

Topics:

  • MapReduce and HIVE integration
  • MapReduce and HBASE integration
  • Java and HIVE integration
  • HIVE-HBase Integration

Hands-On:

  • Uses storage handlers for integrating HIVEand HBASE. Integrates HIVE and PIG as well

Learning objective:

You will learn the different daemons and their functionality at a high level.

Topics:

  • Name node
  • Data node
  • Secondary name node
  • Job tracker
  • Task tracker

Hands-On:

  • Creates a UNIX shell script to run all the daemons at one time

Learning objective:

You will learn different modes of Hadoop, understand pseudo mode from scratch and work with configuration. You will learn the functionality of different HDFS operations and visual representation of HDFS read and write actions with their daemons name node and data node.

Topics:

  • Local Mode
  • Pseudo-distributed Mode
  • Fully distributed mode
  • Pseudo Mode installation and congurations
  • HDFS basic operation

Hands-On:

Install virtual box manager and install Hadoop in Pseudo distributed mode. Changes the different configuration files required for pseudo-distributed mode. Performs different file operations on HDFS.

Learning objective:

Understand the importance of PIG in the Big Data world, PIG architecture, and Pig Latin commands for doing different complex operations on relations, and also PIG UDF and aggregation functions with piggy bank library. Learn how to pass dynamic arguments to PIG scripts.

Topics

  • PIG concepts
  • Install and configure PIG on a cluster
  • PIG Vs MapReduce and SQL
  • Write sample PIG Latin scripts
  • Modes of running PIG
  • PIG UDFs

Hands-On:

  • Login to Pig grunt shell to issue PIG Latin commands in different execution modes
  • Different ways of loading and transformation on PIG relations lazily. Registering UDF in grunt shell and perform replicated join operations

Learning objectives:

Learn how to import normally and incrementally data from RDBMS to HDFS and HIVE tables, and also learn how to export the data from HDFS and HIVE tables to RDBMS. Learn the architecture of SQOOP Import and export.

Topics:

  • SQOOP concepts
  • SQOOP architecture
  • Connecting to RDBMS
  • Internal mechanism of import/export
  • Import data from Oracle/MySQL to HIVE
  • Export data to Oracle/MySQL
  • Other SQOOP commands

Hands-On:

  • Triggers shell script to call SQOOP import and export commands
  • Learn to automate SQOOP incremental imports by entering the last value of the appended column 
  • Run SQOOP export from HIVE table directly to RDBMS

Learning objectives: 

Understand oozie architecture and monitor oozie workflow using oozie. Understand how coordinators and bundles work along with workflow in oozie. Also learn oozie commands to submit, monitor, and kill the workflow.

Topics:

  • OOZIE concepts
  • OOZIE architecture
  • Workflow engine
  • Job coordinator
  • Installing and configuring OOZIE
  • HPDL and XML for creating workflows
  • Nodes in OOZIE
  • Action nodes and control nodes
  • Accessing OOZIE jobs through CLI, and web console
  • Develop and run sample workflows in OOZIE
  • Run MapReduce programs
  • Run HIVE scripts/jobs

Hands-on:

  • Create the Workflow to incremental Imports of SQOOP. Create the workflow for Pig, Hive, and SQOOP exports 
  • Execute coordinator to schedule the workflows

Learning objective: 

You will learn Pentaho Big Data best practices guidelines and techniques documents.

Topics:

  • Data Analytics using Pentaho as an ETL tool
  • Big Data Integration with zero coding required

Hands-on:

  • You will use Pentaho as an ETL tool for data analytics

Course Module

Learning objective:

You will get introduced to real-world problems with Big data and will learn how to solve those problems with state-of-the-art tools. Understand how Hadoop offers solutions to traditional processing with its outstanding features. You will get to know Hadoop’s background and different distributions of Hadoop available in the market. Prepare the UNIX Box for the training.

Topics:

Big Data Introduction

  • What is Big Data?
  • Data Analytics
  • Big Data challenges
  • Technologies supported by Big Data

Hadoop Introduction

  • What is Hadoop?
  • History of Hadoop
  • Basic concepts
  • Future of Hadoop
  • The Hadoop distributed file system
  • Anatomy of a Hadoop cluster
  • Breakthroughs of Hadoop
  • Hadoop distributions:
  • Apache Hadoop
  • Cloudera Hadoop
  • Hortonworks Hadoop
  • MapR Hadoop

Hands-On:

  • Installation of a virtual machine using VMPlayer on the host machine
  • Work with some basics UNIX commands needs for Hadoop

Learning objective:

You will learn the different daemons and their functionality at a high level.

Topics:

  • Name node
  • Data node
  • Secondary name node
  • Job tracker
  • Task tracker

Hands-On:

  • Creates a UNIX shell script to run all the daemons at one time

Learning objective:

You will get to know how to write and read files in HDFS. Understand how to name node, data node, and secondary name node take part in HDFS architecture. You will also know different ways of accessing HDFS data.

Topics:

  • Blocks and input splits
  • Data replication
  • Hadoop rack awareness
  • Cluster architecture and block placement
  • Accessing HDFS
  • JAVA approach
  • CLI approach

Hands-On:

  • Writes a shell script that writes and reads files in HDFS
  • Changes replication factor at three levels
  • Use Java for working with HDFS
  • Writes different HDFS commands and also admin commands

Learning objective:

You will learn different modes of Hadoop, understand pseudo mode from scratch and work with configuration. You will learn the functionality of different HDFS operations and visual representation of HDFS read and write actions with their daemons name node and data node.

Topics:

  • Local Mode
  • Pseudo-distributed Mode
  • Fully distributed mode
  • Pseudo Mode installation and congurations
  • HDFS basic operation

Hands-On:

Install virtual box manager and install Hadoop in Pseudo distributed mode. Changes the different configuration files required for pseudo-distributed mode. Performs different file operations on HDFS.

Learning objective:

Understand different phases in MapReduce including Map, Shuffling, Sorting, and Reduce Phases. Get a deep understanding of the Life Cycle of MR in YARN submission. Learn about the Distributed Cache concept in detail with examples. Write Wordcount MR Program and monitor the Job using Job Tracker and YARN Console. Also, learn about more use cases.

Topics:

  • Basic API concepts
  • The driver class
  • The mapper class
  • The reducer class
  • The combiner class
  • The partitioner class
  • Examining a sample MapReduce program with several examples
  • Hadoop's Streaming API

Hands-On:

  • Learn about writing MR job from scratch, writing different logics in mapper and reducer, and submitting the MR job in standalone and distributed mode
  • Also learn about writing word count MR job, calculating  average salary of the employee who meets certain conditions and sales calculation using MR Hadoop ecosystems

Learning objective:

Understand the importance of PIG in the Big Data world, PIG architecture, and Pig Latin commands for doing different complex operations on relations, and also PIG UDF and aggregation functions with piggy bank library. Learn how to pass dynamic arguments to PIG scripts.

Topics

  • PIG concepts
  • Install and configure PIG on a cluster
  • PIG Vs MapReduce and SQL
  • Write sample PIG Latin scripts
  • Modes of running PIG
  • PIG UDFs

Hands-On:

  • Login to Pig grunt shell to issue PIG Latin commands in different execution modes
  • Different ways of loading and transformation on PIG relations lazily. Registering UDF in grunt shell and perform replicated join operations

Learning objective:

Understand the importance of Hive in the Big Data world. Different ways of configuring Hive megastore. Learn different types of tables in the hive. Learn how to optimize hive jobs using partitioning and bucketing and passing dynamic arguments to hive scripts. You will get an understanding of Joins, UDFS, Views, etc.

Topics:

  • HIVE concepts
  • HIVE architecture
  • Installing and configuring HIVE
  • Managed tables and external tables
  • Joins in HIVE
  • Multiple ways of inserting data in HIVE tables
  • CTAS, views, alter tables
  • User-defined functions in HIVE
  • HIVE UDF

Hands-On:

  • Executes hive queries in different Modes
  • Creates Internal and External tables
  • Perform query optimization by creating tables with partition and bucketing concepts 
  • Run system-defined and user-defined functions including explode and windows functions

Learning objectives:

Learn how to import normally and incrementally data from RDBMS to HDFS and HIVE tables, and also learn how to export the data from HDFS and HIVE tables to RDBMS. Learn the architecture of SQOOP Import and export.

Topics:

  • SQOOP concepts
  • SQOOP architecture
  • Connecting to RDBMS
  • Internal mechanism of import/export
  • Import data from Oracle/MySQL to HIVE
  • Export data to Oracle/MySQL
  • Other SQOOP commands

Hands-On:

  • Triggers shell script to call SQOOP import and export commands
  • Learn to automate SQOOP incremental imports by entering the last value of the appended column 
  • Run SQOOP export from HIVE table directly to RDBMS

Learning objectives:

Understand different types of NoSQL databases and CAP theorem. Learn different DDL and CRUD operations of HBASE. Understand HBase architecture and Zookeeper Importance in managing HBase. Learns HBase column family optimization and client-side buffering.

Topics:

  • HBase concepts
  • ZOOKEEPER concepts
  • HBase and Region server architecture
  • File storage architecture
  • NoSQL vs SQL
  • Dening Schema and basic operations
  • DDLs
  • DMLs
  • HBase use cases

Hands-On: 

Create HBase tables using shell and perform CRUD operations with JAVA API. Change the column family properties and also perform the sharding process. Also, create tables with multiple splits to improve the performance of the HBase query.

Learning objectives: 

Understand oozie architecture and monitor oozie workflow using oozie. Understand how coordinators and bundles work along with workflow in oozie. Also learn oozie commands to submit, monitor, and kill the workflow.

Topics:

  • OOZIE concepts
  • OOZIE architecture
  • Workflow engine
  • Job coordinator
  • Installing and configuring OOZIE
  • HPDL and XML for creating workflows
  • Nodes in OOZIE
  • Action nodes and control nodes
  • Accessing OOZIE jobs through CLI, and web console
  • Develop and run sample workflows in OOZIE
  • Run MapReduce programs
  • Run HIVE scripts/jobs

Hands-on:

  • Create the Workflow to incremental Imports of SQOOP. Create the workflow for Pig, Hive, and SQOOP exports 
  • Execute coordinator to schedule the workflows

Learning objectives:

Understand flume architecture and its components source, channel, and sinks. Configure flume with socket, file sources, and HDFS and HBase sink. Understand fan in and fan out architecture.

Topics:

  • FLUME concepts
  • FLUME architecture
  • Installation and configurations
  • Executing FLUME jobs

Hands-on:

  • Create flume configuration files and configure with different sources and sinks. Stream twitter data and create a hive table

Learning objective: 

You will learn Pentaho Big Data best practices guidelines and techniques documents.

Topics:

  • Data Analytics using Pentaho as an ETL tool
  • Big Data Integration with zero coding required

Hands-on:

  • You will use Pentaho as an ETL tool for data analytics

Learning objective: 

You will see different integrations among the Hadoop ecosystem in a data engineering flow. Also, understand how important it is to create a flow for the ETL process.

Topics:

  • MapReduce and HIVE integration
  • MapReduce and HBASE integration
  • Java and HIVE integration
  • HIVE-HBase Integration

Hands-On:

  • Uses storage handlers for integrating HIVEand HBASE. Integrates HIVE and PIG as well

Program Dates

18 Oct
  • 07:00 PM
  • Mon
  • Online Live
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28 Oct
  • 11:00 AM
  • Thu
  • Classroom
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5 Nov
  • 11:00 AM
  • Fri
  • Classroom
Enquire Now

Expert Instructors & Teaching Methods

Our trainer is a Solution Architect with 15years of hands on experience in design and implementation of complex projects in large enterprises. Data scientist with good experience in Hadoop, HBase, Hive, Spark, Crunch, HBase, Zookeeper, Sqoop, Flume, Oozie, SolR,Cassandra, Map Reduce, Kafka, Kite, R. He is an expertise in design and development of webservices and API development / Deployment also application development using Java, Spring, Hibernate, Struts, Angular, HTML, CSS, SQL. He successfully Implemented the Project on Big Data Platform(Cloudera) and using technologies like Spark, Hive, Pig, Oozie, Sqoop, Impala. Possess very strong Exposure to CI/CD tools including maven, Git, Jenkins. Exposure to Integration using JMS/REST, IBM MQ, WMB, Websphere ESB and Apache Kafka. Also experienced in all the phases of SDLC including Agile(Scrum), Waterfall, TDD and Iteration. He is an IIT’an and certified Software Architect and Sun Certified Java programmer.

Trainer

Learners Point Certificate

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KHDA Certificate

Earn a KHDA attested Course Certificate. The Knowledge and Human Development Authority (KHDA) is the educational quality assurance and regulatory authority of the Government of Dubai, United Arab Emirates.

Why Count on Learners Point?

Being the leading providers of the Big Data Hadoop and Spark course in Dubai, at Learners Point we help professionals master the necessary skill sets to successfully complete the Big Data Hadoop and Spark certification.

Following are the USPs our Big Data Hadoop and Spark training course offers you:

  • We look at real-world scenarios organizations face and formulate our Big Data Hadoop and Spark training course evaluating practical requirements
  • Apart from theoretical knowledge, we also focus on practical case studies to give you a reality check and insight into what exactly will be asked of you while delivering in a demanding role
  • Our bespoke Big Data Hadoop and Spark course also equips you with hands-on experience by offering assignments related to the actual work environment .
  • Apart from organizing group sessions, we also offer a guided learning experience to enhance the quality of our Big Data Hadoop and Spark training program
  • We also take a discrete approach to career guidance so that one can be successfully placed as a professional

Learners Experience

"The instructor was pretty good and provided a lot of knowledge on the matter with good examples and demos. I loved this session and believe that it could not be better than this"

"The instructor was pretty good and provided a lot of knowledge on the matter with good examples and demos. I loved this [...]

Julio A

IT Professional

"The course is all about the activities conducted in each phase of the life cycle of a contract, methodologies used to manage each one of these activities and the best practices used in contract management"

"The course is all about the activities conducted in each phase of the life cycle of a contract, methodologies used to [...]

Ram

student

Our Graduates

Our graduates are from big companies, small, companies, they are founders, career changers and life long learners. Join us and meet your tribe!

Frequently Asked Questions

Hadoop is the leader in the Big Data category of job postings and as well offers high-paying jobs. With the ever-growing demand for the profession and substantial salary packages, Big Data Hadoop is a lucrative career with tremendous opportunities for advancement in the future. This sector attracts millions of professionals across the globe with the right skill set to have a futuristic career.
Big Data is becoming more and more valuable to the workplace and to the global economy. The Big Data Hadoop and Spark course offers a deep understanding of the fundamentals of Spark and the Hadoop ecosystem. This course trains participants on various components of the Hadoop ecosystem that fits into the Big Data processing lifecycle. This course enhances your Big Data Hadoop and Spark knowledge to help you land great job opportunities elevating your professional value and stand out in today’s competitive world.
The Big Data Hadoop and Spark course in Dubai is a perfect fit for anyone looking to gain expertise in the Big Data Hadoop ecosystem and Spark environment. It is ideal for:
1) IT, Data Management, and Analytics professionals
2) Software Developers and Architects
3) Business Intelligence professionals
4) Project Managers
5) Aspiring Data Scientists
6) Graduates looking to begin a career in Big Data Analytics
The training sessions at Learners Point are interactive, immersive, and intensive hands-on programs. We offer 3 modes of delivery and participants can choose from instructor-led classroom-based group coaching, one-to-one training session, or high-quality live and interactive online sessions as per convenience.
Due to high-tech infrastructure and the implementation of several smart initiatives, Dubai is now named as the Middle East’s leading smart city. With the rising demand for Big Data in the global business market, professionals with significant knowledge and skills in Hadoop and Spark can bring their careers one level up. The demand for Big Data professionals is projected to grow positively in the UAE making it the ideal location for a promising career.
This Big Data Hadoop and Spark course in Dubai offers a foundational understanding of the Hadoop ecosystem and Spark environment. This training trains you to master the concepts and enforce the best practices for Hadoop and Spark development to transform data into actionable insights. This Big Data Hadoop and Spark course also approves of your expertise in Hadoop architecture and data loading techniques using Spark.
For participants to enroll in this Big Data Hadoop and Spark course, it is highly recommended for participants to have familiarity with Core Java and SQL.
At Learners Point, if a participant doesn’t wish to proceed with the training after the registration due to any reason, he or she is entitled to a 100% refund. However, the refund will be issued only if we are notified in writing within 2 days from the date of registration. The refund will be processed within 4 weeks from the day of exit.

Frequently Asked Questions

Hadoop is the leader in the Big Data category of job postings and as well offers high-paying jobs. With the ever-growing demand for the profession and substantial salary packages, Big Data Hadoop is a lucrative career with tremendous opportunities for advancement in the future. This sector attracts millions of professionals across the globe with the right skill set to have a futuristic career.
Due to high-tech infrastructure and the implementation of several smart initiatives, Dubai is now named as the Middle East’s leading smart city. With the rising demand for Big Data in the global business market, professionals with significant knowledge and skills in Hadoop and Spark can bring their careers one level up. The demand for Big Data professionals is projected to grow positively in the UAE making it the ideal location for a promising career.
Big Data is becoming more and more valuable to the workplace and to the global economy. The Big Data Hadoop and Spark course offers a deep understanding of the fundamentals of Spark and the Hadoop ecosystem. This course trains participants on various components of the Hadoop ecosystem that fits into the Big Data processing lifecycle. This course enhances your Big Data Hadoop and Spark knowledge to help you land great job opportunities elevating your professional value and stand out in today’s competitive world.
This Big Data Hadoop and Spark course in Dubai offers a foundational understanding of the Hadoop ecosystem and Spark environment. This training trains you to master the concepts and enforce the best practices for Hadoop and Spark development to transform data into actionable insights. This Big Data Hadoop and Spark course also approves of your expertise in Hadoop architecture and data loading techniques using Spark.
The Big Data Hadoop and Spark course in Dubai is a perfect fit for anyone looking to gain expertise in the Big Data Hadoop ecosystem and Spark environment. It is ideal for:
1) IT, Data Management, and Analytics professionals
2) Software Developers and Architects
3) Business Intelligence professionals
4) Project Managers
5) Aspiring Data Scientists
6) Graduates looking to begin a career in Big Data Analytics
For participants to enroll in this Big Data Hadoop and Spark course, it is highly recommended for participants to have familiarity with Core Java and SQL.
The training sessions at Learners Point are interactive, immersive, and intensive hands-on programs. We offer 3 modes of delivery and participants can choose from instructor-led classroom-based group coaching, one-to-one training session, or high-quality live and interactive online sessions as per convenience.
At Learners Point, if a participant doesn’t wish to proceed with the training after the registration due to any reason, he or she is entitled to a 100% refund. However, the refund will be issued only if we are notified in writing within 2 days from the date of registration. The refund will be processed within 4 weeks from the day of exit.
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