Big Data Hadoop Training in Kalyan Nagar

Best Big Data Hadoop Training in Kalyan Nagar Bangalore

Big Data Training in Kalyan Nagar

It is an undeniable fact that today the IT industry is completely data have driven which is why Big data analytics are gradually becoming the crux of every reputed organization. This has created exquisite career opportunities for various data analysts. Taking a Big Data Hadoop training in Kalyan Nagar may, therefore, seek great career prospects for the aspirants.

Hadoop Training in Kalyan Nagar

Besant Technologies, one of the most renowned institutes in Bangalore Kalyan Nagar offers excellent Big Data Hadoop courses which let the students learn the techniques from Beginners level and Advanced level. The course is taught by professional tutors having a strong past teaching background.

Big data Hadoop training in Kalyan Nagar Bangalore

If you are clear about your career choice and have finally decided to take up Big Data Hadoop training in Kalyan Nagar, then Besant Technologies is your ultimate training destination. Bid Data Hadoop training isn’t just any other concept which can be learned overnight. It is rather a complex set of technologies which require rigorous training sessions. The tutors at Besant technologies focus on concept clarity and ensure that the students get personal attention.

Besant Technologies has many branches across the country and its Bangalore Kalyan Nagar branch is amongst the oldest ones. Kalyan Nagar is counted amongst the easiest to reach areas of Bangalore and therefore is much convenient for the students. Strong bus connectivity, frequent metros, and readily available cabs help the student in reaching the institute at any time of day. Also, there are several eateries and food-joints around the institute which lets the students take a short snack break.

So, if you have made up your mind to take Big Data Hadoop training at Bangalore Kalyan Nagar at Besant Technologies, then commuting is just not a problem.

Upcoming Batch Schedule for Big Data Hadoop Training in Kalyan Nagar Bangalore

Besant Technologies provides flexible timings to all our students. Here are the Hadoop Training in Kalyan Nagar Bangalore Schedule in our branches. If this schedule doesn’t match please let us know. We will try to arrange appropriate timings based on your flexible timings.

• 14-04-2025 Mon (Mon - Fri)Weekdays Batch 08:00 AM (IST)(Class 1Hr - 1:30Hrs) / Per Session Get Fees
• 17-04-2025 Thu (Mon - Fri)Weekdays Batch 08:00 AM (IST)(Class 1Hr - 1:30Hrs) / Per Session Get Fees
• 12-04-2025 Sat (Sat - Sun)Weekend Batch 11:00 AM (IST) (Class 3Hrs) / Per Session Get Fees

Can’t find a batch you were looking for?

Request a Batch

Big Data Hadoop Training Syllabus

Apache Hadoop

• Introduction to Big Data & Hadoop Fundamentals
• Dimensions of Big data
• Type of Data generation
• Apache ecosystem & its projects
• Hadoop distributors
• HDFS core concepts
• Modes of Hadoop employment
• HDFS Flow architecture
• HDFS MrV1 vs. MrV2 architecture
• Types of Data compression techniques
• Rack topology
• HDFS utility commands
• Min h/w requirements for a cluster & property files changes

Module 2   (Duration :03:00:00)

MapReduce Framework

Goal : In this module, you will understand Hadoop MapReduce framework and the working of MapReduce on data stored in HDFS. You will understand concepts like Input Splits in MapReduce, Combiner & Partitioner and Demos on MapReduce using different data sets.

Objectives – Upon completing this Module, you should be able to understand MapReduce involves processing jobs using the batch processing technique.

• MapReduce can be done using Java programming.
• Hadoop provides with Hadoop-examples jar file which is normally used by administrators and programmers to perform testing of the MapReduce applications.
• MapReduce contains steps like splitting, mapping, combining, reducing, and output.

Topics:

Introduction to MapReduce

• MapReduce Design flow
• MapReduce Program (Job) execution
• Types of Input formats & Output Formats
• MapReduce Datatypes
• Performance tuning of MapReduce jobs
• Counters techniques

Module 3   (Duration :03:00:00)

Apache Hive

Goal : This module will help you in understanding Hive concepts, Hive Data types, Loading and Querying Data in Hive, running hive scripts and Hive UDF.

Objectives – Upon completing this Module, you should be able to understand Hive is a system for managing and querying unstructured data into a structured format.

• The various components of Hive architecture are metastore, driver, execution engine, and so on.
• Metastore is a component that stores the system catalog and metadata about tables, columns, partitions, and so on.
• Hive installation starts with locating the latest version of tar file and downloading it in Ubuntu system using the wget command.
• While programming in Hive, use the show tables command to display the total number of tables.

Topics:

Introduction to Hive & features

• Hive architecture flow
• Types of hive tables flow
• DML/DDL commands explanation
• Partitioning logic
• Bucketing logic
• Hive script execution in shell & HUE

Module 4   (Duration :03:00:00)

Apache Pig

Goal : In this module, you will learn Pig, types of use case we can use Pig, tight coupling between Pig and MapReduce, and Pig Latin scripting, PIG running modes, PIG UDF, Pig Streaming, Testing PIG Scripts. Demo on healthcare dataset.

Objectives – Upon completing this Module, you should be able to understand Pig is a high-level data flow scripting language and has two major components: Runtime engine and Pig Latin language.

• Pig runs in two execution modes: Local mode and MapReduce mode. Pig script can be written in two modes: Interactive mode and Batch mode.
• Pig engine can be installed by downloading the mirror web link from the website: pig.apache.org.

Topics:

• Introduction to Pig concepts
• Pig modes of execution/storage concepts
• Pig program logics explanation
• Pig basic commands
• Pig script execution in shell/HUE

Module 5   (Duration :03:00:00)

Goal : This module will cover Advanced HBase concepts. We will see demos on Bulk Loading, Filters. You will also learn what Zookeeper is all about, how it helps in monitoring a cluster, why HBase uses Zookeeper.

Objectives – Upon completing this Module, you should be able to understand  HBasehas two types of Nodes—Master and RegionServer. Only one Master node runs at a time. But there can be multiple RegionServersat a time.

• The data model of Hbasecomprises tables that are sorted by rows. The column families should be defined at the time of table creation.
• There are eight steps that should be followed for installation of HBase.
• Some of the commands related to HBaseshell are create, drop, list, count, get, and scan.

Topics:

Apache Hbase

• Introduction to Hbase concepts
• Introdcution to NoSQL/CAP theorem concepts
• Hbase design/architecture flow
• Hbase table commands
• Hive + Hbase integration module/jars deployment
• Hbase execution in shell/HUE

Module 6   (Duration :02:00:00)

Goal : Sqoop is an Apache Hadoop Eco-system project whose responsibility is to import or export operations across relational databases. Some reasons to use Sqoop are as follows:

• SQL servers are deployed worldwide
• Nightly processing is done on SQL servers
• Allows to move certain part of data from traditional SQL DB to Hadoop
• Transferring data using script is inefficient and time-consuming
• To handle large data through Ecosystem
• To bring processed data from Hadoop to the applications

Objectives – Upon completing this Module, you should be able to understand Sqoop is a tool designed to transfer data between Hadoop and RDBs including MySQL, MS SQL, Postgre SQL, MongoDB, etc.

• Sqoop allows the import data from an RDB, such as SQL, MySQL or Oracle into HDFS.

Topics:

Apache Sqoop

• Introduction to Sqoop concepts
• Sqoop internal design/architecture
• Sqoop Import statements concepts
• Sqoop Export Statements concepts
• Quest Data connectors flow
• Incremental updating concepts
• Creating a database in MySQL for importing to HDFS
• Sqoop commands execution in shell/HUE

Module 7   (Duration :02:00:00)

Goal : Apache Flume is a distributed data collection service that gets the flow of data from their source and aggregates them to where they need to be processed.

Objectives – Upon completing this Module, you should be able to understand Apache Flume is a distributed data collection service that gets the flow of data from their source and aggregates the data to sink.

• Flume provides a reliable and scalable agent mode to ingest data into HDFS.

Topics:

Apache Flume

• Introduction to Flume & features
• Flume topology & core concepts
• Property file parameters logic

Module 8   (Duration :02:00:00)

Goal : Hue is a web front end offered by the ClouderaVM to Apache Hadoop.

 Objectives – Upon completing this Module, you should be able to understand how to use hue for hive,pig,oozie.

Topics:

Apache HUE

• Introduction to Hue design
• Hue architecture flow/UI interface

Module 9   (Duration :02:00:00)

Goal : Following are the goals of ZooKeeper:

• Serialization ensures avoidance of delay in reading or write operations.
• Reliability persists when an update is applied by a user in the cluster.
• Atomicity does not allow partial results. Any user update can either succeed or fail.
• Simple Application Programming Interface or API provides an interface for development and implementation.

Objectives – Upon completing this Module, you should be able to understand ZooKeeper provides a simple and high-performance kernel for building more complex clients.

• ZooKeeper has three basic entities—Leader, Follower, and Observer.
• Watch is used to get the notification of all followers and observers to the leaders.

Topics:

Apache Zookeeper

• Introduction to zookeeper concepts
• Zookeeper principles & usage in Hadoop framework
• Basics of Zookeeper

Module 10   (Duration :05:00:00)

Goal:

Explain different configurations of the Hadoop cluster

• Identify different parameters for performance monitoring and performance tuning
• Explain configuration of security parameters in Hadoop.

Objectives – Upon completing this Module, you should be able to understand  Hadoop can be optimized based on the infrastructure and available resources.

• Hadoop is an open-source application and the support provided for complicated optimization is less.
• Optimization is performed through xml files.
• Logs are the best medium through which an administrator can understand a problem and troubleshoot it accordingly.
• Hadoop relies on the Kerberos based security mechanism.

Topics:

Administration concepts

• Principles of Hadoop administration & its importance
• Hadoop admin commands explanation
• Balancer concepts
• Rolling upgrade mechanism explanation

Trainer Profile of Big Data Hadoop Training in Kalyan Nagar Bangalore

We understand the fact that Big Data Hadoop training needs dedicating and committed tutors having great teaching skills apart from having vast knowledge about the concepts. They don’t just rush to finish up the course and rather focus on clearing the concepts so that the students have a strong base.

The tutors are experienced enough to handle live projects and therefore provide practical knowledge to the students as well. They provide support to the students whenever required and ensure that the aspirants are completely industry ready.

Choosing Big Data Hadoop training in Kalyan Nagar Bangalore is the best choice for those aspiring to chase their dream job opportunities at IT MNC’s.

Big Data Hadoop Exams & Certification

Besant Technologies Certification is Accredited by all major Global Companies around the world. We provide after completion of the theoretical and practical sessions to fresher’s as well as corporate trainees.

Our certification at Besant Technologies is accredited worldwide. It increases the value of your resume and you can attain leading job posts with the help of this certification in leading MNC’s of the world. The certification is only provided after successful completion of our training and practical based projects.

The majority of Big Data Hadoop trainees are either programmers or have an engineering background. Attaining certification is important as it fulfills their futuristic goal and allows them to crack great job opportunities.

At Besant Technologies, the students get a course completion certificate once they are through with the course. However, its not just the end for the students as complete placement assistance is also offered to them so that they are placed with companies of their choice. The placement cell is well-aware about various rounds of interviews which the students may need to face and therefore groom them accordingly.

Aspirants living in and around HRBR layout, kammanahalli, Nagawara, banaswadi, babusapalya, Ramamurthy Nagar, hebbal, hennur, HBR layout, ulsoor, rt Nagar, yelahanka have excellent conveyance facilities to reach the institute at any time of the day. The buses, autos, and taxis have great frequency and are also safe for female commuters.

Besant Technologies, over the past few years, have grown as one of the premium institutes for offering best Big Data Hadoop training in Kalyan Nagar which provides live Hands-on experience to the students in specially designed LAB classrooms. The institute also provides Free Software (META disc) to the students.

Key Features of Big Data Hadoop Training in Kalyan Nagar Bangalore

Training Courses Reviews

Frequently Asked Questions