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Big Data Analytics Course Training

Big Data Analytics course is one of the topmost words which has come into the limelight since the demand for new and creative jobs grew in the IT sector. As Data Next has always been the top pioneer in fulfilling learners' needs for the demanded courses, having an eye over the demand. So, Data Next entered into catering students with Big data analytics training.

Big Data Analytics course training enables the students to acknowledge themselves with the major big data concepts including Hadoop and spark. Despite big data being a part of data science, big data has also got various courses in it that a student can choose as per their profession.

What is Big Data?

Generally, big data is useful for analyzing and processing all the structured and unstructured data at maximum speed. Big data, the term itself generates the meaning viz, the data which is vast and big in size, which is infinite. Say, monthly transactions by a giant supermarket D-mart is huge in number when seen or google generating websites every year globally, whose data is infinite in number and hard to maintain. Here comes the need for big data, which customized and processes everything in a systematic way and at a faster pace.

Why Big Data Course?

Usually, the gathering of data and generating it has become a huge task and also a topmost priority for all the industries. This is why, the most renowned companies like IBM, Infosys, TCS are hiring a vast number of data analytics every year. Also, the IBM report says that by 2020 there would be uncountable jobs for big data analysts globally.

 

Demand for Big Data Analytics Course in Market

And, when it comes to the job market for big data analytics as well as professionals, this segment in the IT sector has got endless demand and huge hype over the market industrialists. As these big data analysts and professionals are a package of skills including business acumen, math and statistics, professional communication skills, and also programming and collaborative skills, this has created the most hype for the big data analysts and professionals in almost every company.

Understanding of big data analytics

Let's keep it simple. There are 5 zettabytes of data in the world and 90% of the data was generated in the past 2 years. Moreover, there might be 1075 zettabytes of data by 2025. There is data on everything and everywhere. Increasing digital components are generating huge amounts of data. Your mobile devices leave a trace and there are trillions of photographs stored across the world in the digital form as data. The text file documents, sensor data, server data, website data, email data, social media data, audio and video files are the sources of unstructured data. It is also segregated in structured form and semi-structured form as well. Big data is dynamic by itself.

Firstly, the data need to be captured from different sources that could be structured or unstructured or semi-structured. Secondly, the gathered data needs to be aggregated according to its cluster. Later, the clustered groups are analyzed for further separation into logical components to communicate, which means business decisions.

What is the use of this enormous data?

Huge data = huge business. These large sets of data help to understand the customers from different perspectives and help to make better decisions by predicting the purchasings and activities of the customers that can happen in the near future. The collected data used to develop strategies and optimized processes to enhance business, as data is an asset that you can sell or monetize. Big data analytics enables to invent new smart products and services with the dynamics in the technology according to time and space. Social media platform provides customer insights that are transparent and simpler to analyze the behavior of the customer.

Importance of Informatics Research Labs in Big Data Analytics Training

Data Next intends to produce the best and finest professionals from our institute as Big data Developer, Big data Architect, Big data Engineer, Admin and so on. The significance of big data meets the demand for skillful experts and we apprehend the desire of many professionals as well as industries who are keen to be part of the big data business, as we produced nearly 200 certified professionals within few years and accommodated them in top industries. Our industry expert trainers can train professionals and beginners with flexibility, dedication towards every individual. 

Data Next with peculiar training methods of its own and 100% job assurance with huge success rate, destined to be the best software institute for Big Data Analytics training across the world. Apart from Big Data Analytics training, we offer ADVANCED DATA SCIENCE training, AMAZON WEB SERVICES (AWS) training, ROBOTIC PROCESS AUTOMATION (RPA) course training and DIGITAL MARKETING course training programs with certification from Innomatics research labs and other top MNCs.

 

 

 

 

 

 

Advanced Data Science Course Curriculum

  • Introduction to Big Data & Challenges
  • Limitations & Solutions of Big Data Architecture 
  • Hadoop: Features, Ecosystem, 2.x Core Components, Distributions 
  • Hadoop Storage: HDFS (Hadoop Distributed File System) 
  • Hadoop Processing: MapReduce Framework 

  • Hadoop: 2.x Cluster Architecture, Cluster Modes, 2.x Configuration Files 
  • Federation and High Availability Architecture
  • Hadoop Production Cluster
  • Common Hadoop Shell Commands
  • Single & Multi Node Cluster set up 
  • Basic Hadoop Administration

  •  MapReduce: Need, Anatomy of Program, Combiner & Partitioner 
  • YARN: Components, Architecture, MapReduce Application Execution Flow, Workflow 
  • Input Splits, Relation between Input Splits and HDFS  Blocks 

  • Introduction to Apache Hive, Hive vs Pig
  • Hive: Architecture and Components, Metastore, Limitations of Hive, Partition, Bucketing, Tables (Managed Tables and External Tables) 
  • Traditional Database vs Hive Data Types and Data Models, Importing Data, Querying Data & Managing outputs .

  • Introduction to Apache Pig
  • Pig: MapReduce vs Pig, Components, Execution, Data Types & Models, Latin Programs, UDF, Streaming, Shell & Utility commands, Testing Pig sscripts with Punit 

  • Sqoop Installation
  • Import Data.(Full table, Only Subset, Target Directory, protecting Password, file format other than CSV, Compressing, Control Parallelism,  All tables Import) 
  • Incremental  Import(Import only New data, Last Imported data, storing Password in Metastore, Sharing Metastore between Sqoop Clients) 
  • Free Form Query Import
  • Export data to RDBMS,HIVE and HBASE 
  • Hands on Exercises

  • ACID in RDBMS and BASE in NoSQL
  • CAP Theorem and Types of Consistency
  • Types of NoSQL Databases in detail
  • Columnar Databases in Detail (HBASE and CASSANDRA) 
  • TTL, Bloom Filters and Compensation

 

  • Introduction to Flume
  • Flume Agents: Sources, Channels and Sinks
  • Log User information using Java program in to HDFS using LOG4J and Avro Source, Tail Source 
  • Log User information using Java program in to HBASE using LOG4J and Avro Source, Tail Source 
  • Flume Commands
  • Use case of Flume: Flume the data from twitter in to HDFS and HBASE 
  • Analysis using HIVE and PIG 

  • Workflow (Action, Start, Action, End, Kill, Join and Fork), Schedulers, Coordinators and Bundles.,to show how to schedule Sqoop Job, Hive, MR and PIG 

  • Spark Overview,  Linking with Spark, Initializing Spark, Basics, Passing Functions to Spark 
  • Using the Shell, Resilient Distributed Datasets (RDDs), RDD Operations , Parallelized Collections, External Datasets, Working with Key Value Pairs 
  • Transformations, Actions, RDD Persistence,  Storage Level choice, Removing Data, Shared Variables, Broadcast Variables, Accumulators, Deploying to a Cluster 

Why Choose Data Next

  • 18+ Industry experts
  •  Learn with highly qualified academic institutions and tutors with huge experience.
  •  Rigorous efforts taken to make a student to be a job qualified both skillfully as well as subject wise
  •  Also conducting of various assignments, workshops and meet ups for collaborations
  •  Certified and guaranteed placements for both IT and NON-IT
  •  700+ people got trained since the period of establishment
  •  100% Placement Assistance
  •  Handouts, Exercises and Assignments on subject
  •  In house Internship on our projects & products

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