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Hadoop Training in Bhubaneswar

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04- Jul - 2022
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06- Jul - 2022
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09- Jul - 2022
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09- Jul - 2022
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  • You will learn much more than Hadoop after taking this course, such as Big Data. You will become an expert in big data installation, configuration, and handling with our course.
  • This tutorial will not only teach you how these technologies work together, but also demonstrate how they can be used to solve real-world business problems! The only prerequisite is knowledge of UNIX and Java. You will gain theoretical knowledge, as well as confidence, needed to apply this knowledge to your career.
  • You will be prepared for big data projects quickly after taking this course. You will learn how to set up HDFS, Map Reduce, Apache Pig, and Hive during this course .
  • Create and configure EC2 instances and Hadoop instances.
  • Students at all levels will be able to understand all subjects using simple examples, applications, and explanations.
  • Theory as well as practical sessions are beneficial to students. After graduating from our programs, students are prepared to obtain jobs in top companies.
  • During this course, you will learn Hadoop in depth, and you will be able to apply Hadoop to real-world problems. Additionally, you will receive a valuable certificate of completion upon completion!
  • Concepts: High Availability, Big Data opportunities, Challenges, Hadoop Distributed File System (HDFS), Map Reduce, API discussion, Hive, Hive Services, Hive Shell, Hive Server and Hive Web Interface, SQOOP, H Catalogue, Flume, Oozie.
  • START YOUR CAREER WITH HANDOOP CERTIFICATION COURSE THAT GETS YOU A JOB OF UPTO 5 TO 12 LACS IN JUST 60 DAYS!
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Course Objectives

Hadoop is a Java-based open-source platform for storing and analyzing large amounts of data. The data is stored on low-cost commodity servers that are clustered together. Concurrent processing and fault tolerance are enabled via the distributed file system.
Hadoop, as a Big Data platform, enables companies to spread data storage, perform parallel processing, and handle data at increased volumes, speeds, variety, value, and veracity. The three primary components of this Hadoop lesson are HDFS, MapReduce, and YARN.
Hadoop is an open-source software framework that is used for storing massive amounts of data and has enormous processing power along with the capability to parallelly handle and process an unlimited number of tasks/jobs.
There are several advantages of using big data to inform new product development. Firms may create goods that connect with customers, give more value to them, and reduce the risks associated with launching a new product. Firms can also use data mining to discover requirements that they would not have seen otherwise.
  • The Most Important Parts Of Big Data Machine Learning It is the science of teaching computers to learn on their own.
  • Natural Language Processing (NLP) refers to a computer's capacity to comprehend spoken human language.
  • Business intelligence is a term that refers to the study of data.
  • Cloud computing is a term that refers to its use.
If you have the requirements, you can quickly master Hadoop in a matter of days. If you want to learn Hadoop from the ground up, it will take you two to three months. We strongly advise you to enroll in an industry-recognized Big Data Hadoop Training to assist you in your quest.
  • The titles knowledge Scientists, knowledge Engineers, and knowledge Analysts are provided to certified Hadoop Developers since the task involves studying knowledge.
  • Jobs are in high demand all around the world; according to a report by the, there is a projected shortfall of 190,000 data scientists in North America alone.
  • Do the math and calculate the world figures if you're curious about numbers.

What will you learn through this Big Data Hadoop Certification Training Course?

  • Learn the fundamentals of Hadoop and YARN, as well as how to develop applications that use them.
  • HDFS, MapReduce, Hive, Pig, Sqoop, Flume, and ZooKeeper are some of the tools available.
  • Spark applications include Spark SQL, Streaming, Data Frame, RDD, GraphX, and MLlib.
  • Avro data formats are being used.
  • Examining real-world Hadoop and Apache Spark projects.
  • Big Data Hadoop Certification will be given.

Why should I learn Hadoop to create my career?

One of the most important driving factors to study big data Hadoop's apparent benefit is that it provides a plethora of chances for you to advance your profession. As more companies tackle big data, they're increasingly looking for specialists who can understand and use knowledge.

What are the provisions of a Hadoop Training Course?

Before attempting a Hadoop course, a contestant should have a fundamental grasp of programming languages such as Python, Scala, and Java, as well as a much greater understanding of SQL and RDBMS.

How could I be a Big Data Engineer?

This course provides data on the Hadoop environment as well as extensive learning tools and techniques to help you become a big data engineer and complete your work. The course confirmation demonstrates your Big Data abilities and hands-on ability. Hadoop certification will teach you how to use biological system tools like Hadoop, HDFS, MapReduce, Flume, Kafka, Hive, and HBase, among others.

What are the performing goals of the Big Data and Hadoop Certification Training Course?

Hadoop is an Apache project for storing and processing large amounts of data. Hadoop stores Big Data in an appropriate and forgiving manner over item equipment. As a result, Hadoop's instruments are utilized to simulate HDFS data processing. Because businesses recognize the value of Big Data Analytics, Big Data and shadow specialists are in high demand. Organizations want Big Data and Hadoop experts with knowledge of the Hadoop Ecosystem and best practices on HDFS, MapReduce, Spark, HBase, Hive, Pig, Oozie, Sqoop, and Flume.
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Overview of Hadoop Training in Bhubaneswar

In our Big Data Hadoop Course, we cover the many tools and frameworks in the Hadoop Cluster and how to utilise them effectively. You will be taught by industry professionals how to identify, analyse, and resolve problems in the framework. Achieve certification as an expert in Big Data Hadoop testing. Experienced working experts offer our Big Data Training in Bhubaneswar. In addition to personal skill development, CV building, and updating the newest trends and employment possibilities in India, we give 100 percent placement promise.

 

Additional Info

Why Is Big Data Important?

The value of big data does not lie in how much your organization has, but rather what it does with that data. Using any data source, you can get answers that can help 1) lower costs, 2) reduce time spent on tasks, 3) develop new products and optimize offerings, and 4) make smarter decisions. Business-related tasks can be accomplished with the use of big data and high-powered analytics, including:

  • In near-real time, determine root causes of failures, issue, and defect.
  • Coupons generated at point of sale based on the purchasing habits of customers.
  • Quickly recalculate your entire risk portfolio.
  • Preventing fraud from affecting your organization by detecting it early.
  • Challenges of Big Data:

    The initial stages of Big Data projects can be very challenging for companies. They do not understand the challenges faced by Big Data nor are they equipped to deal with them.

    1. Inadequate understanding of Big Data:- Due to insufficient understanding of Big Data, companies fail to adopt them. There may be a lack of understanding by employees about data, its storage, processing, importance, and source. Others may not be aware of what's going on, even if data professionals do.

    2. Growth issues in data:- Storing all these huge sets of data properly is one of the biggest challenges of Big Data. It is becoming increasingly common for companies to store data in their servers and databases. It becomes extremely difficult to deal with these large data sets as they grow exponentially over time. Documents, videos, audios, text files, and other types of data are the most typical sources of unstructured data. Databases do not contain them, so you are unable to locate them. Different storage tiers can be used by companies for data tiering. In doing so, the data will be stored in a more suitable location. Depending on the data size and significance, public cloud, private cloud, or flash storage can be used. Additionally, companies are embracing Big Data technologies, including Hadoop, NoSQL, and others.

    3. Big Data tool selection can be confusing:- Many companies have trouble choosing the right tool for analyzing and storing Big Data. What is the best technology for storing data? HBase or Cassandra? Data analytics and storage can be achieved with Hadoop MapReduce or Spark is a better choice? There are questions like these that bother companies, and sometimes the answers are difficult to find. As a result, they choose an inappropriate technology and make poor decisions. The result is a waste of time, money, efforts, and work hours.

    4. Lack of data professionals:- A company's data professionals are essential to operate these modern technologies and Big Data tools. Professionals who specialize in working with big data sets will include data scientists, data analysts, and data engineers. Despite the huge demand for Big Data professionals, companies face a shortage. Most data handling professionals, on the other hand, have not changed with the tools. This gap must be closed by taking actionable steps.

    5. Securing data:- Big Data poses a number of daunting challenges, including the need to secure these massive sets of data. Data security is often pushed to the back burner when companies are so busy analyzing, storing, and understanding their data sets. It would be a good idea to protect data repositories, as they can serve as breeding grounds for malicious hackers.

    6. The integration of data from various sources:- An organization collects data through various channels, such as social media, ERP applications, financial reports, e-mails, presentations and the reports created by its employees. Reports are difficult to prepare when all these data have to be combined. The area is often neglected by firms. Data integration, however, is essential for analysis, reporting, and business intelligence, so it needs to be perfect.

    What are the challenges of using Hadoop?

    Not all problems are well-suited to MapReduce programming. For iterative and interactive analytical tasks, it is best suited for simple requests for information and problems that can be divided into independent units. The MapReduce algorithm requires a lot of files. Consequently, iterative algorithms must go through multiple phases of map-shuffle/sort-reduce since nodes cannot communicate except through sorts and shuffles. For analytic computing, this leads to multiple files created between MapReduce phases. It's widely acknowledged that there is a talent gap. There is a problem with finding entry-level programmers with Java skills who can be productive with MapReduce. Among the reasons distribution companies are rushing to integrate relational (SQL) technology with Hadoop is this. The availability of SQL programmers is much greater than that of MapReduce programmers. Moreover, Hadoop administration appears to be an art and a science that requires basic understanding of operating systems, hardware and Hadoop kernel settings.

    Data security:- New tools and technologies have been developed to address the fragmented data security issues. Hadoop environments can be made more secure with Kerberos authentication. Management and governance of data on a full scale. For data management, data cleaning, governance and metadata, Hadoop does not provide easy-to-use, full-featured tools.

    Major features of Hadoop:

    1. Scalable:- Because hadoop stores and distributes very large data sets across thousands of inexpensive servers, it is highly scalable. It doesn't scale to support large amounts of data, as do traditional relational databases (RDBMS).

    2. Cost-effective:- Businesses with exploding data sets can also use Hadoop to store data more efficiently. Due to the complexity of traditional relational databases, scaling to an extent that allows massive amounts of data to be processed is extremely costly. Many companies in the past would have down-sampled data and classified it based on what they believed was most valuable to cut costs. We would delete the raw data, because storing it would be unprofitable.

    3. Flexible:- In order to generate value from data, businesses can tap into diverse types of data (structured and unstructured) using Hadoop. As a result, businesses can gain valuable insights from social media, email conversations, and other data sources using Hadoop.

    4. Fast:- Rather than store data in a specific location on a cluster, Hadoop's storage method uses a distributed file system that map data to any location on the cluster. Because the tools for analyzing the data reside on the same servers as the data, the data is processed much faster.

    5. Resilient to failure:- Hadoop offers fault tolerance as one of its main advantages. In addition to being replicated to all other nodes in the cluster, when data is sent to one node in a cluster, there is also another copy that can be used in the event of a failure.

    Advantages of Big Data:

    Consumers today have high expectations. On social media, he interacts with potential customers and considers different options before making a purchase. Upon purchasing a product, customers want to be treated as individuals and thanked. Your company can use big data to get actionable data in real-time that enables direct engagement with your customers. A way big data can help you do this is that you can check the profile of a complaining customer in real-time and get information about the product/s he/she is complaining about. Afterwards, reputation management can be done. Using big data, you can redevelop the products and services you sell. You can use unstructured text from social networking sites, for example, to find out what other people think about your products. The success of your business can be measured by studying how minor variations in CAD (computer-aided design) images affect your processes and products. As a result, manufacturing processes can benefit greatly from big data. Keep your competitors at bay with predictive analysis. Big data can be useful for this by, for example, scanning and analyzing social media feeds and newspaper articles. Furthermore, big data assists in running health-tests on your customers, suppliers, and other stakeholders in order to help you avoid defaults.

    In terms of data security, big data is beneficial. The use of big data tools helps you map the data landscape of your organization, which helps in analyzing threats within. By comparing the protected information with the unsecured information, you will know if it is protected. In addition, you will be able to identify the emailing or storing of 16 digit numbers (which may contain credit card information). Diversifying revenue streams is possible with big data. You can use big data analytics to find trends that can help you come up with a completely new source of revenue. It is imperative that your website be dynamic if you wish to succeed in the crowded online market. By studying big data, you can customize your website to suit the needs of each visitor by taking into account their gender and nationality, for example. Amazon's IBCF feature (item-based collaborative filtering) drives the "People you may know" and "Frequently bought together" sections.The advantages of big data for factories are that machines will not need to be replaced based on how long they have been used. Compared to maintaining the same wear rate on the same parts, this is rather expensive and impractical. It is vital for healthcare to use big data, which creates a more personalized and effective experience.

    Career Path in Role of Big Data:

    Data Analyst:- As a data analyst, you are responsible for processing big data using various tools. Data analysts often work with unstructured or semi-structured sources of data, and to process these sources, they use tools like hive, pig, and NoSQL databases, as well as frameworks such as Hadoop and spark. By using the hidden data potential of data and making wise decisions, their main job is to help companies increase their revenue. It is essential that someone with good arithmetic and problem-solving skills become a data analyst. Analysts generate reports, analyze past trends, and produce analysis of past data.

    Programmer:- Programmers create codes for repetitive and conditional actions on available data sets. An individual ought to possess good analytical, mathematical, logical, and statistical skills in order to write good and efficient code. Programmers working with big data mostly use Shell scripts, Java, Python, R, and so on. A programmer contends with flat files or databases as the data with which they work is typically stored, so an understanding of file systems and databases is also critical.

    Admin:- In the big data ecosystem, an admin is responsible for managing the infrastructure that manages data and analytics-related tools. Also included in their role is the management of all nodes and the configuration of their networks. For big data operations, administrators make sure that infrastructure is always available. Admins handle the installation of various tools and manage the hardware of clusters. One should have a thorough understanding of the file system, operating system, hardware, and networking in order to be an admin.

    Solution Architect:- Solution architects study real-world problems and develop proper strategies to solve them using their expertise and the capabilities of big data. Choosing which software/programming language should be used to develop the solution is the responsibility of the solution architect. For the position of Solution Architect, a person must have solid problem-solving skills along with knowledge of the frameworks and tools that are available to process big data, their licensing costs, and alternative open source solutions.

    Software Developer(Programmer):- Developing Hadoop data abstraction SDKs and extracting value from data is the job of a Hadoop Data Developer.

    Data Analyst:- Having a good understanding of SQL makes working with Hadoop's SQL engines such as Hive or Impala an exciting prospect

    Business Analyst:- Organizations looking to become more profitable are utilizing massive amounts of data, and a business analyst's role is crucial in achieving this.

    ETL Developer:- Using Spark tools for ETL can be a relatively easy transition if you're working with traditional ETL tools.

    Testers:- In the Hadoop world, testing is in high demand. The transition to this role is possible for testers who understand Hadoop and data profiling.

    BI/DW professions:- Hadoop Data architecture can easily be adapted to data modelling.

    Senior IT professionals:- The right senior professional can become a consultant by gaining insight how Hadoop tries to solve these data challenges with deep domain knowledge and familiarity with existing challenges.It's possible to find generic roles, such as Data Engineers or Big Data Engineers, that are responsible for implementing solutions mostly on cloud platforms. It will prove to be a rewarding role as you gain experience with the cloud's data components.

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    Key Features

    ACTE Bhubaneswar offers Hadoop Training in more than 27+ branches with expert trainers. Here are the key features,
    • 40 Hours Course Duration
    • 100% Job Oriented Training
    • Industry Expert Faculties
    • Free Demo Class Available
    • Completed 500+ Batches
    • Certification Guidance

    Authorized Partners

    ACTE TRAINING INSTITUTE PVT LTD is the unique Authorised Oracle Partner, Authorised Microsoft Partner, Authorised Pearson Vue Exam Center, Authorised PSI Exam Center, Authorised Partner Of AWS and National Institute of Education (nie) Singapore.
     

    Curriculum

    Syllabus of Hadoop Course in Bhubaneswar
    Module 1: Introduction to Hadoop
    • High Availability
    • Scaling
    • Advantages and Challenges
    Module 2: Introduction to Big Data
    • What is Big data
    • Big Data opportunities,Challenges
    • Characteristics of Big data
    Module 3: Introduction to Hadoop
    • Hadoop Distributed File System
    • Comparing Hadoop & SQL
    • Industries using Hadoop
    • Data Locality
    • Hadoop Architecture
    • Map Reduce & HDFS
    • Using the Hadoop single node image (Clone)
    Module 4: Hadoop Distributed File System (HDFS)
    • HDFS Design & Concepts
    • Blocks, Name nodes and Data nodes
    • HDFS High-Availability and HDFS Federation
    • Hadoop DFS The Command-Line Interface
    • Basic File System Operations
    • Anatomy of File Read,File Write
    • Block Placement Policy and Modes
    • More detailed explanation about Configuration files
    • Metadata, FS image, Edit log, Secondary Name Node and Safe Mode
    • How to add New Data Node dynamically,decommission a Data Node dynamically (Without stopping cluster)
    • FSCK Utility. (Block report)
    • How to override default configuration at system level and Programming level
    • HDFS Federation
    • ZOOKEEPER Leader Election Algorithm
    • Exercise and small use case on HDFS
    Module 5: Map Reduce
    • Map Reduce Functional Programming Basics
    • Map and Reduce Basics
    • How Map Reduce Works
    • Anatomy of a Map Reduce Job Run
    • Legacy Architecture ->Job Submission, Job Initialization, Task Assignment, Task Execution, Progress and Status Updates
    • Job Completion, Failures
    • Shuffling and Sorting
    • Splits, Record reader, Partition, Types of partitions & Combiner
    • Optimization Techniques -> Speculative Execution, JVM Reuse and No. Slots
    • Types of Schedulers and Counters
    • Comparisons between Old and New API at code and Architecture Level
    • Getting the data from RDBMS into HDFS using Custom data types
    • Distributed Cache and Hadoop Streaming (Python, Ruby and R)
    • YARN
    • Sequential Files and Map Files
    • Enabling Compression Codec’s
    • Map side Join with distributed Cache
    • Types of I/O Formats: Multiple outputs, NLINEinputformat
    • Handling small files using CombineFileInputFormat
    Module 6: Map Reduce Programming – Java Programming
    • Hands on “Word Count” in Map Reduce in standalone and Pseudo distribution Mode
    • Sorting files using Hadoop Configuration API discussion
    • Emulating “grep” for searching inside a file in Hadoop
    • DBInput Format
    • Job Dependency API discussion
    • Input Format API discussion,Split API discussion
    • Custom Data type creation in Hadoop
    Module 7: NOSQL
    • 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
    <strongclass="streight-line-text"> Module 8: HBase
    • HBase Installation, Concepts
    • HBase Data Model and Comparison between RDBMS and NOSQL
    • Master & Region Servers
    • HBase Operations (DDL and DML) through Shell and Programming and HBase Architecture
    • Catalog Tables
    • Block Cache and sharding
    • SPLITS
    • DATA Modeling (Sequential, Salted, Promoted and Random Keys)
    • Java API’s and Rest Interface
    • Client Side Buffering and Process 1 million records using Client side Buffering
    • HBase Counters
    • Enabling Replication and HBase RAW Scans
    • HBase Filters
    • Bulk Loading and Co processors (Endpoints and Observers with programs)
    • Real world use case consisting of HDFS,MR and HBASE
    Module 9: Hive
    • Hive Installation, Introduction and Architecture
    • Hive Services, Hive Shell, Hive Server and Hive Web Interface (HWI)
    • Meta store, Hive QL
    • OLTP vs. OLAP
    • Working with Tables
    • Primitive data types and complex data types
    • Working with Partitions
    • User Defined Functions
    • Hive Bucketed Tables and Sampling
    • External partitioned tables, Map the data to the partition in the table, Writing the output of one query to another table, Multiple inserts
    • Dynamic Partition
    • Differences between ORDER BY, DISTRIBUTE BY and SORT BY
    • Bucketing and Sorted Bucketing with Dynamic partition
    • RC File
    • INDEXES and VIEWS
    • MAPSIDE JOINS
    • Compression on hive tables and Migrating Hive tables
    • Dynamic substation of Hive and Different ways of running Hive
    • How to enable Update in HIVE
    • Log Analysis on Hive
    • Access HBASE tables using Hive
    • Hands on Exercises
    Module 10: Pig
    • Pig Installation
    • Execution Types
    • Grunt Shell
    • Pig Latin
    • Data Processing
    • Schema on read
    • Primitive data types and complex data types
    • Tuple schema, BAG Schema and MAP Schema
    • Loading and Storing
    • Filtering, Grouping and Joining
    • Debugging commands (Illustrate and Explain)
    • Validations,Type casting in PIG
    • Working with Functions
    • User Defined Functions
    • Types of JOINS in pig and Replicated Join in detail
    • SPLITS and Multiquery execution
    • Error Handling, FLATTEN and ORDER BY
    • Parameter Substitution
    • Nested For Each
    • User Defined Functions, Dynamic Invokers and Macros
    • How to access HBASE using PIG, Load and Write JSON DATA using PIG
    • Piggy Bank
    • Hands on Exercises
    Module 11: SQOOP
    • 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
    Module 12: HCatalog
    • HCatalog Installation
    • Introduction to HCatalog
    • About Hcatalog with PIG,HIVE and MR
    • Hands on Exercises
    Module 13: Flume
    • Flume Installation
    • 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. Do some analysis using HIVE and PIG
    Module 14: More Ecosystems
    • HUE.(Hortonworks and Cloudera)
    Module 15: Oozie
    • Workflow (Action, Start, Action, End, Kill, Join and Fork), Schedulers, Coordinators and Bundles.,to show how to schedule Sqoop Job, Hive, MR and PIG
    • Real world Use case which will find the top websites used by users of certain ages and will be scheduled to run for every one hour
    • Zoo Keeper
    • HBASE Integration with HIVE and PIG
    • Phoenix
    • Proof of concept (POC)
    Module 16: SPARK
    • Spark Overview
    • Linking with Spark, Initializing Spark
    • Using the Shell
    • Resilient Distributed Datasets (RDDs)
    • Parallelized Collections
    • External Datasets
    • RDD Operations
    • Basics, Passing Functions to Spark
    • Working with Key-Value Pairs
    • Transformations
    • Actions
    • RDD Persistence
    • Which Storage Level to Choose?
    • Removing Data
    • Shared Variables
    • Broadcast Variables
    • Accumulators
    • Deploying to a Cluster
    • Unit Testing
    • Migrating from pre-1.0 Versions of Spark
    • Where to Go from Here
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    Need customized curriculum?

    Hands-on Real Time Hadoop Projects

    Project 1
    Real-time Analysis of Log-entries Project

    Computers, networks, and other IT systems generate records called audit trail records or logs that document system activities. Log analysis is the evaluation of these records.

    Project 2
    Health Status Prediction Project

    The aimed to build a fully functional system in order to achieve a efficiency in faster health treatment and online consultations system.

    Project 3
    Generating Image Caption Project

    Image caption generator is a task that involves computer vision and natural language processing concepts to recognize the context of an image and describe them.

    Project 4
    GIS Analytics for Better Waste Management Project

    GIS can add value to waste management applications by providing outputs for decision support and analysis in a wide spectrum of projects such as route planning.

    Our Engaging Placement Partners

    ACTE Bhubaneswar give positions Backing. We have committed situation Official dealing with the Understudies arrangement. Far beyond we have tie-ups with such countless IT Organizations where the imminent HRs and Bosses reach us for situations.
    • Our Big Data and Hadoop Training in Bhubaneswar class is intended to remember every one of these to guarantee that you will be agreeable, equipped, and certain about every such meeting.
    • The preparing fundamentally centers around contextual analyses and venture work on the innovation which empowers a contender to comprehend the mechanical direction of the innovation.
    • Our understudies get recruited and set from different top and MNCs like Wipro, Google, Accenture, IBM, Microsoft, Conscious and some more.
    • Our enough push is assigned in improving the show abilities/persuading power alongside other specialized contributions to make our leaners solid competitors in any enlistment.
    • For ACTE, we are a one-quit enlisting accomplice. Thus we allude them to our completely cleaned and gifted leaners who are useful.
    • We offer over 40 hours of involved preparing to our understudies so they can comprehend the subjects instructed to them exhaustively.

    Get Certified By MapR Certified Hadoop Developer (MCHD) & Industry Recognized ACTE Certificate

    Acte 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 Acte 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.

    Complete Your Course

    a downloadable Certificate in PDF format, immediately available to you when you complete your Course

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    a physical version of your officially branded and security-marked Certificate.

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    About Adequate Hadoop Instructor

    • Our Big Data and Hadoop Training in Bhubaneswar have trainers are entirely educated in their separate spaces of work and have the potential and the abilities that are needed to convey their substance.
    • Training and improvement of resources at ACTE Bhubaneswar assist our understudies with overhauling their scholastic abilities as well as their relational and information sharing abilities, so study hall guidance can turn out to be more intuitive.
    • Our Specialists have mechanical just as down to earth insight with Big Data and Hadoop Training as they show our leaners as well as work in corporates as well.
    • ACTE Big Data and Hadoop Training similarly dedicated association for preparing, over the course of the years has acquired the regard, acclaim, and love of our learners for our creative, steady, and expert work style in the field of schooling.
    • Our educators unmatched expert experience gets from long periods of making a positive training environment and supporting learners with imaginative critical thinking and group building capacities.
    • To sort out outstandingly regular live online arranged get-togethers, we will utilize neighborhood web conferencing with screen sharing.

    Hadoop Course Reviews

    Our ACTE Bhubaneswar Reviews are listed here. Reviews of our students who completed their training with us and left their reviews in public portals and our primary website of ACTE & Video Reviews.

    Mahalakshmi

    Studying

    "I would like to recommend to the learners who wants to be an expert on Big Data just one place i.e.,ACTE institute at Anna nagar. After several research with several Training Institutes I ended up with ACTE. My Big Data Hadoop trainer was so helpful in replying, solving the issues and Explanations are clean, clear, easy to understand the concepts and it is one of the Best Training Institute for Hadoop Training"

    Josephin

    Software Engineer

    I sincerely thank ACTE institute for the best training I got in Bhubaneswar. Being new to this training institute, all kind of necessary assistance has been providing to me so far ,here the People are cooperative and very helpful.I found this is the Best institute for Hadoop Training

    Harish

    Software Engineer

    The training here is very well structured and is very much peculiar with the current industry standards. Working on real-time projects & case studies will help us build hands-on experience which we can avail at this institute. Also, the faculty here helps to build knowledge of interview questions & conducts repetitive mock interviews which will help in building immense confidence. Overall it was a very good experience in availing training in Tambaram at the ACTE Institute. I strongly recommend this institute to others for excelling in their career profession.

    Sindhuja

    Studying

    I had an outstanding experience in learning Hadoop from ACTE Institute. The trainer here was very much focused on enhancing knowledge of both theoretical & as well as practical concepts among the students. They had also focused on mock interviews & test assignments which helped me towards boosting my confidence.

    Kaviya

    Software Engineer

    The Hadoop Training by sundhar sir Velachery branch was great. The course was detailed and covered all the required knowledge essential for Big Data Hadoop. The time mentioned was strictly met and without missing any milestone.Should be recommended who is looking Hadoop training course ACTE institute in Chennai.

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    • ACTE is the Legend in offering placement to the students. Please visit our Placed Students List on our website
    • We have strong relationship with over 700+ Top MNCs like SAP, Oracle, Amazon, HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc.
    • More than 3500+ students placed in last year in India & Globally
    • ACTE conducts development sessions including mock interviews, presentation skills to prepare students to face a challenging interview situation with ease.
    • 85% percent placement record
    • Our Placement Cell support you till you get placed in better MNC
    • Please Visit Your Student Portal | Here FREE Lifetime Online Student Portal help you to access the Job Openings, Study Materials, Videos, Recorded Section & Top MNC interview Questions
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    • Certification is Accredited by all major Global Companies
    • ACTE is the unique Authorized Oracle Partner, Authorized Microsoft Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of AWS and National Institute of Education (NIE) Singapore
    • The entire Hadoop training has been built around Real Time Implementation
    • You Get Hands-on Experience with Industry Projects, Hackathons & lab sessions which will help you to Build your Project Portfolio
    • GitHub repository and Showcase to Recruiters in Interviews & Get Placed
    All the instructors at ACTE are practitioners from the Industry with minimum 9-12 yrs of relevant IT experience. They are subject matter experts and are trained by ACTE for providing an awesome learning experience.
    No worries. ACTE assure that no one misses single lectures topics. We will reschedule the classes as per your convenience within the stipulated course duration with all such possibilities. If required you can even attend that topic with any other batches.
    We offer this course in “Class Room, One to One Training, Fast Track, Customized Training & Online Training” mode. Through this way you won’t mess anything in your real-life schedule.

    Why Should I Learn Hadoop Course At ACTE?

    • Hadoop Course in ACTE is designed & conducted by Hadoop experts with 10+ years of experience in the Hadoop domain
    • Only institution in India with the right blend of theory & practical sessions
    • In-depth Course coverage for 60+ Hours
    • More than 50,000+ students trust ACTE
    • Affordable fees keeping students and IT working professionals in mind
    • Course timings designed to suit working professionals and students
    • Interview tips and training
    • Resume building support
    • Real-time projects and case studies
    Yes We Provide Lifetime Access for Student’s Portal Study Materials, Videos & Top MNC Interview Question.
    You will receive ACTE globally recognized course completion certification Along with National Institute of Education (NIE), Singapore.
    We have been in the training field for close to a decade now. We set up our operations in the year 2009 by a group of IT veterans to offer world class IT training & we have trained over 50,000+ aspirants to well-employed IT professionals in various IT companies.
    We at ACTE believe in giving individual attention to students so that they will be in a position to clarify all the doubts that arise in complex and difficult topics. Therefore, we restrict the size of each Hadoop batch to 5 or 6 members
    Our courseware is designed to give a hands-on approach to the students in Hadoop. The course is made up of theoretical classes that teach the basics of each module followed by high-intensity practical sessions reflecting the current challenges and needs of the industry that will demand the students’ time and commitment.
    You can contact our support number at +91 93800 99996 / Directly can do by ACTE.in's E-commerce payment system Login or directly walk-in to one of the ACTE branches in India
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