There is an enormous need for big data analysts in IT industries since information technology handles millions of data every single moment. In order to keep track of and to analyze the data, the contribution of big data analysts is highly appreciated among IT companies.
In that same vein, Hadoop is an open-source software framework which is used to store the data sporadically and to process the datasets of big data. It is done with the aid of MapReduce programming model. With a lot of commodity hardware nodes, Hadoop posits it as possible to run applications on systems.
According to a survey reports, more than 60% of modern corporations are solely depending on big data analytics to raise the organization’s social media marketing abilities. And, more importantly, in another survey conducted by Peer-Research Big Data Survey, they list the benefits of big data for a big company.
Big Data Features
The big data Hadoop certification course offered by Hope Tutors is designed to give you the complete insight into the big data framework by giving you a thorough understanding of HDFS, YARN and MapReduce. We will train you to analyse the data that is collectively stored in HDFS. Using Flume for the digestion of data also is trained in our big data training course.
Processing the data with Spark is a major part of our Hadoop big data training course as you will learn different interactive algorithms and how to use Spark SQL to generate, transform and query the data forms. And during our big data training course, you are going to work out industrial level projects in the sectors of telecommunication and social media for the deeper understanding of big data.
MapReduce is the essential component of Apache Hadoop software framework and MapReduce is notable for its ability to sort out through unstructured data sets. So learning MapReduce will enrich your ability to navigate datasets that is in its primal form.
Our best Hadoop big data training course in Chennai also covers PIG and SQOOP aspects as well. With PIG, its structure is so flexible that it can be substantially parallelized. Its textual language is vital to handle very large datasets. In addition, Sqoop is used to transfer the data from Hadoop to the database servers, vice versa.
YARN – Yet Another Resource Negotiator – is a cluster management program. YARN is a wide-reaching operating system for big data applications. All of these will be covered in Hope Tutors’ big data training course. All these tools are put together and easily integrated with Hadoop and the big data will be processed faster.
We hope this video here will illustrate big data
Hope Tutors Big Data Course Features
Our Hope Tutors Big Data Training Center in Chennai is a distinguished milestone in guiding students in their career path. Situated in the main part of Velachery, Chennai, our best Hadoop Big Data Training Center is offering students the best training they could ever have. Hope Tutors leads you through a step-by-step process to learn the effective force of big data.
Not only Hope Tutors provides classroom sessions, we lead the students through the practical application of what they have just learned. It is one of the many striking features of Hope Tutors. Students are given in-depth and clear understanding of big data and are trained in a good environment.
Our trainers have adequate knowledge and are very experienced experts in big data analysis. They guide you to achieve your career goals with much efficiency.
What will you learn from our Big Data Training?
- First of all, you will understand Flume architecture and its configuration.
- The functionality of RBDMS and its workings in relation to HBase. The differences between them also will be covered.
- Understanding Spark SQL and how to create and run its frameworks.
- With Hive and Impala, you will learn how to create a new database. And learning to use Hive and Impala to partition.
Online Big Data Training
Besides our classroom training, Hope Tutors Big Data Training Institute provides online training sessions to those who want to learn the course easily from their home.
To whom the Big Data is for?
- Analytics professionals
- Data analysts
- Senior IT professionals
- Data management professionals
- Project managers
- Business intelligence professionals
So having a certified training in big data will certainly boost your career opportunities. Our Hope Tutors Big Data Training Centre in Chennai will make your dreams come true to become an assured big data analyst.
Big Data and Hadoop Course Certification
Why is certification in big data important?
- Just being graduated is not enough to equip your future in big data
- Big companies are hiring big data analysts who are extraordinarily trained with Hadoop in best institutes
- You could learn the complete skills that is necessary to be an effective big data analyst
- How big data analysis helps businesses to multiply their revenue?
For a company to speed-up its outcome it has to analyze consumers’ preferences and choices and analyze the data to launch new products and recommendations. Thus this new approach increases the company’s revenue.
- Distinguish structured & unstructured data.
Unstructured data is something that is not established in advance that includes metadata, audio, video, FB posts and Twitter tweets which is not gathered as a whole in a database, while a structured data is well-organized like numbers and dates in order and it can be easily stored, managed and processed.
- What are the major elements of Hadoop application?
- Hadoop Common
- What is HDFS in big data?
Hadoop Distributed File System is the storage component of Hadoop which serves as the data collector which stores varieties of data as blocks.
- What are the major concepts of Hadoop framework?
MapReduce and HDFS are the main concepts found in Hadoop.
- What is the course duration for big data in Hope Tutors?
It takes 30 hours of training in big data.
- Can the course fee be paid in installment?
Of course! We accept the course fee in installment structure.
- Is online training available?
Yes, Hope Tutors provides online sessions.
- Can I attend the training on weekends?
Yes, if you cannot attend classes on weekdays, we’ve arranged weekend sessions.
- I am not sure about if I would join Hope Tutors. What to do?
To know what we are teaching you could request a free demo.
Big Data Interview Questions with Answers
|Hadoop YARN Introduction||00:00:00|
|Hadoop YARN Setup||00:00:00|
|Programming in YARN framework j||00:00:00|
|Understanding big data and Hadoop|
|Limitations and Solutions of existing Data Analytics Architecture||00:00:00|
|Hadoop 2.x core components||00:00:00|
|Hadoop Storage: HDFS||00:00:00|
|Hadoop Storage : Azure Data Lake Introduction||00:00:00|
|Hadoop Processing: MapReduce Framework||00:00:00|
|Hadoop Different Distributions.||00:00:00|
|Hadoop Mapreduce Framework & YARN|
|MapReduce Use Cases||00:00:00|
|Traditional way Vs MapReduce way||00:00:00|
|Hadoop 2.x MapReduce Architecture||00:00:00|
|Hadoop 2.x MapReduce Components||00:00:00|
|YARN MR Application Execution Flow||00:00:00|
|Anatomy of MapReduce Program||00:00:00|
|Demo on MapReduce. Input Splits||00:00:00|
|Relation between Input Splits and HDFS Blocks||00:00:00|
|MapReduce: Combiner & Partitioner||00:00:00|
|Demo on de-identifying Health Care Data set||00:00:00|
|Demo on Weather Data set.||00:00:00|
|Hadoop Architecture and HDFS|
|Hadoop 2.x Cluster Architecture – Federation and High Availability||00:00:00|
|A Typical Production Hadoop Cluster||00:00:00|
|Hadoop Cluster Modes||00:00:00|
|Common Hadoop Shell Commands||00:00:00|
|Hadoop 2.x Configuration Files||00:00:00|
|Single node cluster and Multi node cluster set up Hadoop Administration.||00:00:00|
|Custom Input Format||00:00:00|
|Sequence Input Format||00:00:00|
|Xml file Parsing using MapReduce.||00:00:00|
|MapReduce Vs Pig||00:00:00|
|Pig Use Cases||00:00:00|
|Programming Structure in Pig||00:00:00|
|Pig Running Modes||00:00:00|
|Pig Latin Program||00:00:00|
|Data Models in Pig||00:00:00|
|Pig Data Types||00:00:00|
|Shell and Utility Commands||00:00:00|
|Pig Latin : Relational Operators||00:00:00|
|Joins and COGROUP||00:00:00|
|Specialized joins in Pig||00:00:00|
|Built In Functions ( Eval Function||00:00:00|
|Load and Store Functions||00:00:00|
|Parameter Substitution ( PIG macros and Pig Parameter substitution )||00:00:00|
|Testing Pig scripts with Punit||00:00:00|
|Aviation use case in PIG||00:00:00|
|Pig Demo on Healthcare Data set.||00:00:00|
|Hive Use Case||00:00:00|
|Hive Vs Pig||00:00:00|
|Hive Architecture and Components||00:00:00|
|Metastore in Hive||00:00:00|
|Limitations of Hive||00:00:00|
|Comparison with Traditional Database||00:00:00|
|Hive Data Types and Data Models||00:00:00|
|Partitions and Buckets||00:00:00|
|Hive Tables(Managed Tables and External Tables)||00:00:00|
|Retail use case in Hive||00:00:00|
|Hive Demo on Healthcare Data set.||00:00:00|
|Advanced Hive and Hbase|
|Hive QL: Joining Tables||00:00:00|
|Custom Map/Reduce Scripts||00:00:00|
|Hive Indexes and views Hive query optimizers||00:00:00|
|Hive : Thrift Server||00:00:00|
|User Defined Functions||00:00:00|
|HBase: Introduction to NoSQL Databases and HBase||00:00:00|
|HBase v/s RDBMS||00:00:00|
|Run Modes & Configuration||00:00:00|
|HBase Cluster Deployment.||00:00:00|
|HBase Data Model||00:00:00|
|HBase Client API||00:00:00|
|Data Loading Techniques||00:00:00|
|ZooKeeper Data Model||00:00:00|
|Demos on Bulk Loading||00:00:00|
|Getting and Inserting Data||00:00:00|
|Filters in HBase.||00:00:00|
|Getting started with Sqoop|
|In this module, you will be introduced to Hadoop you will get to know the Traditional database’s application. Also, you will get to know the basics of Sqoop.||00:00:00|
|Sqoop as an Import/Export tool||00:00:00|
|Sqoop Import Process||00:00:00|
|Basic Sqoop Commands||00:00:00|
|Importing Data in HDFS using Sqoop||00:00:00|
|Exporting Data from HDFS||00:00:00|
|:Import /Export Data between RDBMS and Hive/HBase||00:00:00|
|Inceptors, channel ,sink processor||00:00:00|
|Twitter Data in HDFS||00:00:00|
|Telnet as source and HBase as a sink||00:00:00|
|Twitter Data in HBase||00:00:00|
|Oozie and Hadoop project|
|Scheduling with Oozie||00:00:00|
|Demo on Oozie Workflow||00:00:00|
|Oozie Web Console||00:00:00|
|Oozie for MapReduce||00:00:00|
|Hive and Sqoop||00:00:00|
|Combine flow of MR||00:00:00|
|Hive in Oozie||00:00:00|
|Hadoop Project Demo||00:00:00|
|Hadoop Integration with Talend.||00:00:00|
|Understanding Apache Kafka and Kafka Cluster|
|Need for Kafka||00:00:00|
|Core Concepts of Kafka||00:00:00|
|Where is Kafka Used||00:00:00|
|Processing Distributed data with Apache spark|
|What is Apache Spark||00:00:00|
|History of Spark and Spark Versions/Releases||00:00:00|
|Spark a Polyglot||00:00:00|
|What is Scala?||00:00:00|