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Big Data Hadoop Certification Training in Dubai

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Rated #1 Recoginized as the No.1 Institute for Big Data Hadoop Certification Training in Dubai

Boost your career with Big Data Hadoop Certification Training in Dubai by enrolling in expert-led sessions. Gain practical experience that will exciting opportunities in the rapidly growing field of big data.

Upon completing the Big Data Hadoop Training in Dubai, you’ll build a strong foundation in the Hadoop ecosystem, Big Data placement processing, distributed storage, MapReduce, and data analysis. Gain the essential skills to manage and analyze massive datasets and optimize performance.

  • Get affordable, industry-recognized training with placement support.
  • Connect with 400+ hiring companies and 15,648+ trained professionals
  • Join the Big Data Hadoop Certification course in Dubai to fast-track your career growth.
  • Gain practical experience in handling real-world big data projects and improving data workflows.
  • Unlock job opportunities with top tech companies, data-driven organizations, and analytics firms.
  • Master Big Data course tools and Hadoop frameworks to elevate your career in the data industry!

Fee INR 18000

INR 14000

Training

  • Case Studies and Projects 8+

  • Hours of Training 45+

  • Placement Assurance 100%

  • Expert Support 24/7

  • Support & Access Lifetime

  • Certification Yes

  • Skill Level All

  • Language All

Learn From Experts, Practice On Projects & Get Placed in IT Company

  • 100% Guaranteed Placement Support for Freshers & Working Professionals
  • You will not only gain knowledge of Big Data Hadoop Certification Certification and advanced concepts, but also gain exposure to Industry best practices
  • Experienced Trainers and Lab Facility
  • Big Data Hadoop Certification Professional Certification Guidance Support with Exam Dumps
  • Practical oriented / Job oriented Training. Practice on Real Time project scenarios.
  • We have designed an in-depth course so meet job requirements and criteria
  • Resume & Interviews Preparation Support
  • Concepts: High Availability, Big Data opportunities, Challenges, Big Data Hadoop Certification 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!
  • Classroom Batch Training
  • One To One Training
  • Online Training
  • Customized Training
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10-Feb-2025
Mon-Fri

Weekdays Regular

08:00 AM & 10:00 AM Batches

(Class 1Hr - 1:30Hrs) / Per Session

12-Feb-2025
Mon-Fri

Weekdays Regular

08:00 AM & 10:00 AM Batches

(Class 1Hr - 1:30Hrs) / Per Session

15-Feb-2025
Sat,Sun

Weekend Regular

(10:00 AM - 01:30 PM)

(Class 3hr - 3:30Hrs) / Per Session

16-Feb-2025
Sat,Sun

Weekend Fasttrack

(09:00 AM - 02:00 PM)

(Class 4:30Hr - 5:00Hrs) / Per Session

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    About Big Data Hadoop Certification Online Training Course in Dubai

    ACTE's Big Data Hadoop Training , helps you master Big Data and Hadoop Ecosystem tools such as HDFS, YARN, Map Reduce, Hive, Impala, Pig, HBase, Spark, Oozie, Flume, Sqoop, Hadoop Frameworks, and more concepts of Big Data processing Life cycle. Benefits Big Data Hadoop certification training online course is best suited for IT, data management, and analytics professionals looking to gain expertise in Big Data Hadoop, including Software Developers and Architects, Analytics Professionals, Senior IT professionals, Testing and Mainframe Professionals, Data Management Professionals, Business Intelligence Professionals, Project Managers, Aspiring Data Scientists, Graduates looking to begin a career in Big Data Analytics.
    Top Job Offered Big Data Hadoop Certification Online Tools Covered
    • Big Data, HDFS YARN, Spark MapReduce
    • PIG, HIVE HBase Mahout, Spark MLLib
    • Solar, Lucene Zookeeper Oozie
    Big Data Hadoop Certification skills are in demand – this is an undeniable fact! Hence, there is an urgent need for IT professionals to keep themselves in trend with Big Data Hadoop Certification and Big Data technologies. Apache Big Data Hadoop Certification provides you with means to ramp up your career and gives you the following advantages: Accelerated career growth.
    Big Data Hadoop Certification is the supermodel of Big Data. If you are a Fresher there is a huge scope if you are skilled in Big Data Hadoop Certification . The need for analytics professionals and Big Data architects is also increasing . Today many people are looking to pursue their big data career by grabbing big data jobs as freshers.
    Even as a fresher, you can get a job in Big Data Hadoop Certification domain. It is definitely not impossible for anyone to land a job in the Big Data Hadoop Certification domain if they invest their mind in preparing and putting their best effort in learning and understanding the Big Data Hadoop Certification concepts.
    We are happy and proud to say that we have strong relationship with over 700+ small, mid-sized and MNCs. Many of these companies have openings for Big Data Hadoop Certification . Moreover, we have a very active placement cell that provides 100% placement assistance to our students. The cell also contributes by training students in mock interviews and discussions even after the course completion.
    A Big Data Hadoop Certification Cluster uses Master-Slave architecture. It consist of a Single Master (NameNode) and a Cluster of Slaves (DataNodes) to store and process data. Big Data Hadoop Certification is designed to run on a large number of machines that do not share any memory or disks. These DataNodes are configured as Cluster using Big Data Hadoop Certification Configuration files. Big Data Hadoop Certification uses a concept of replication to ensure that at least one copy of data is available in the cluster all the time. Because there are multiple copy of data, data stored on a server that goes offline or dies can be automatically replicated from a known good copy.
    • To learn Big Data Hadoop Certification and build an excellent career in Big Data Hadoop Certification , having basic knowledge of Linux and knowing the basic programming principles of Java is a must. Thus, to incredibly excel in the entrenched technology of Apache Big Data Hadoop Certification , it is recommended that you at least learn Java basics.
    • Learning Big Data Hadoop Certification is not an easy task but it becomes hassle-free if students know about the hurdles overpowering it. One of the most frequently asked questions by prospective Big Data Hadoop Certification ers is- “How much java is required for Big Data Hadoop Certification ”? Big Data Hadoop Certification is an open source software built on Java thus making it necessary for every Big Data Hadoop Certification er to be well-versed with at least java essentials for Big Data Hadoop Certification . Having knowledge of advanced Java concepts for Big Data Hadoop Certification is a plus but definitely not compulsory to learn Big Data Hadoop Certification . Your search for the question “How much Java is required for Big Data Hadoop Certification ?” ends here as this article explains elaborately on java essentials for Big Data Hadoop Certification .
    Apache Big Data Hadoop Certification is an open source platform built on two technologies Linux operating system and Java programming language. Java is used for storing, analysing and processing large data sets. ... Big Data Hadoop Certification is Java-based, so it typically requires professionals to learn Java for Big Data Hadoop Certification . Yes, you can learn Big Data Hadoop Certification , without any basic programming knowledge . The only one thing matters is your dedication towards your work. If you really want to learn something, then you can easily learn. It also depends upon on which profile you want to start your work like there are various fields in Big Data Hadoop Certification .
    Our course ware is designed to give a hands-on approach to the students in Big Data Hadoop Certification . 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.
    Yes It is worth , Future will be bright. Learning Big Data Hadoop Certification will definitely give you a basic understanding about working of other options as well. Moreover, several organizations are using Big Data Hadoop Certification for their workload. So there are lot of opportunities for good developers in this domain. Indeed it is! No Learning Big Data Hadoop Certification is not very difficult. Big Data Hadoop Certification is a framework of java. Java is not a compulsory prerequisite for learning Big Data Hadoop Certification . ... Big Data Hadoop Certification is an open source software platform for distributed storage and distributed processing of very large data sets on computer clusters built from commodity hardware.
    Big Data Hadoop Certification framework can be coded in any language, but still, Java is preferred. For Big Data Hadoop Certification , the knowledge of Core Java is sufficient, and it will take approximately 5-9 months. Learning Linux operating system: - It is recommended to have a basic understanding and working of the Linux operating system.

    Top reasons to consider a career in Big Data Hadoop Certification ?

    Big Data Hadoop Certification brings in better career opportunities in 2015. Learn Big Data Hadoop Certification to pace up with the exponentially growing Big Data Market. Increased Number of Big Data Hadoop Certification Jobs. Learn Big Data Hadoop Certification to pace up with the increased adoption of Big Data Hadoop Certification by Big data companies.
      What Is Big Data And Hadoop? Big data refers to the large and complex set of data that are difficult to process using traditional processing systems. Stock exchanges like NYSE and BSE generates Terabytes of data every day. Social media sites like Facebook generates data that are approximately 500 times bigger than stock exchanges.Hadoop is an open source project by Apache used for storage and processing of large volume of unstructured data in a distributed environment. Hadoop can scale up from single server to thousands of servers. Hadoop framework is used by large giants like Amazon, IBM, New York Times, Google, Facebook, Yahoo and the list is growing every day. Due to the larger investments companies make for Big Data the need for Hadoop Developers and Data Scientists who can analyse the data increases day by day. Scope Of Hadoop In Future
    • Big Data Analytics job has become a trending one currently and it is believed to have a great scope in future as well.
    • There is a survey which states Big Data Management and Analytics job opportunities has been increased in 2017 when compared to the past 2 years.
    • This leads many IT professionals to switch their career to Hadoop by taking up Hadoop Training.
    • Many organizations prefer Big Data Analytics as it is necessary to store their large amount of data and retrieve the information when it is wanted.
    • After this, many other organizations that have not used Big Data have also started using it in their organization which makes the demand for Big Data Analytics in town.
    • One of the main advantages of Hadoop is the salary aspects, when you become Big Data Analyst with a proper training you may have a very good package over a year of experience, this is the main reason for people preferring Big Data Training.
    • Adding to it, there are lots of job opportunities available in India as well as abroad which gives you the hope of onsite jobs too.
    • Putting upon all these factors in a count, Big Data Hadoop is trusted to have the stable platform in future.
    • If you are in a dilemma in taking up Hadoop Training Chennai then it is the right time to make your move.
    Advantages Of Big Data Hadoop
    • Cost-Open source—commodity Hardware
    • Scalability- Huge data is divided to multiple machines and processed parallel
    • Flexibility- Suitable for processing all types of data sets - structured -unstructured (images, videos)
    • Speed - HDFS—massive parallel processing
    • Fault Tolerance- Data is replicated on various machines and read from one machine.
    Hadoop Industry Updates What Is New In Hadoop?
    • The industry standard hardware from Hadoop helps to store the data for the analysis of the data applied to the structured and unstructured data.
    • To move the data the bulk load processing and streaming techniques are used.
    • Apache squoop is used to move the data through bulk load process. Apache flume and Apache kafka is used to move the data through streaming.
    • The data process options are fast and grouped as batch.
    • The fast in memory is called as the Apache spark and the data processing as batch is called as Apache hive or Apache pig.
    • Join the Hadoop Training  to know about the industrial updates and industrial demand for the hadoop technology.
    • Cloudera and Apache impala have turneddata analysis to BI quality.
    • It has compatibility with all leading BI tools and the high performance of the SQL help for the analysis of the patterns in the data.
    Innovation from Santander
    • The latest innovation of Santander UK’s next generation is the data warehousing and steaming analytics to improve the customer experience. Apache kudu is used for the fast analytics.
    • This is used for the operations like offloading workload from existing legacy systems, ask questions regarding the customer behavior and ask questions regarding the current status of the bank. With the help of Apache Kafka the data streams can be easily moved to online.
    • Apache kudu vault is conforming the data events from the Hub, satellite and link structure of the Data Vault 2.0 methodology.
    • The elastic event delivery platform is based on the scalaAkka and Apache Kafka for the data transformation.
    • The fast data, timely decisions, reusable patterns and high speed are essential factors for the reusable platform and architecture.
    • The big community followers and high level products show the demand for the Big Data Training.
    • For the sake of financial security and enhance the customer satisfaction the Santander UK innovated the real time insight.
    • The cluster used by the legacy systems requires the raw event streams that are canonical.
    • This canonical event stream is redistributed to the other systems. The other systems like HDFS file system, Apache HBase or Apache kudu. This innovation was awarded as the data impact award finalist.
    Hadoop 3
    • Hadoop 3 demand for the Java 8 and to work withhadoop3 java 7 is not helpful for the developers. The erasure encoding in HDFS will provide the fault tolerance and reduce the storage overhead.
    • The smaller units in the sequential data are divided as bit, byte and block.
    • Join the Big Data Course and head the big team of data analysts in a reputed company with the help of the practical knowledge and the constant interest towards learning.
    • These smaller units are saved in different disks in the hadoop.
    • The compared with the HDFS replication the overhead cost of the Erasure coding is comparatively less.
    • The factors like the storage, network and CPU decides the overheads of the erasure coding.Yarn 2 supports the flows or logical applications are supported by the notion of flows explicitly.
    • The time line collector in the YARN separates the data and sent it to the resource manager timeline collector.
    • The shell script rewrite is designed with new features like all the variables in one location which is called as hadoop-env.sh, it is easy to start a daemon command, if pdsh is installed then ssh connections are used in the operations, without symlinkinghadoop is honoured now, the error messages are handled well by displaying it to the user.
    Scalability
    • The namenode extensions, client extensions, datanode extensions, and erasure coding policy forms the architecture of the HDFS erasure encoding. YARN timeline service v.2 is updated on the hadoop 3.
    • The version 2 brings the scalable distributed writer architecture and a scalable backend storage. The queries from the YARN application are dedicated to the REST API.
    • One collector is allocated to each YARN application and the APacheHBase is used as the primary backing storage.
    • The Big Data Training is the best training to get placed in the big company and dream high with the top salary in the industry.
    • The two major challenges are resolved with the updations in the YARN.
    • The challenges are revolving around the scalability, reliability and usability.
    • The scalability is reached with the seperation of the writes and the reads of data.
    • The REST API help to resolve the problems from the queries and differentiate the queries.
    • To process the large size data the HBase handles the response time very well.
    Usability
    • The flows are explicit in the YARN version 2 and the storage system with the application master, node managers and resource managers are well planned.
    • The data that belong to the application are collected in the application master,
    • The resource manager collect the data with the time line collecter. Big Data Hadoop training with the expert trainers makes the subject still more interesting and provides in-depth knowledge in to the subject.
    • To make the volume as reasonable the resource manager emits the YARN generic life cycle.
    • The time line collector on the node which is running the application master with the node managers also collects and writes the data to the time line collector.
    • The storage is backed up with the application master, node managers and the resource managers. The queries are handled by the REST API.
    • The new features in the shell script of the Hadoop also help to fix the bugs.
    • The new hadoop-env.sh aid for the collection of the variables in one location.
    • The daemon is edited and it is easy to start a daemon in hadoop3. Daemon is used for the operations such as daemon stop, stop a daemon, and daemon status. The error messages are handled by the log and pid dirs on daemon start up.
    • The unprotected errors are generally displayed to the user and it elminates the user satisafaction of using the system. So, the new hadoop 3 help for the elimination of error messages and efficient bug fixing.
    • Join the Hadoop Training and see the difference in the number of interviews you get. The right knowledge by the right time is important to get the success in the job.
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    Key Features

    ACTE Dubai offers Big Data Hadoop Certification 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 .
     

    Curriculum

    Syllabus of Big Data Hadoop Certification Online Course in Dubai
    Module 1: Introduction to Big Data Hadoop Certification
    • 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 Big Data Hadoop Certification
    • Big Data Hadoop Certification Distributed File System
    • Comparing Big Data Hadoop Certification & SQL
    • Industries using Big Data Hadoop Certification
    • Data Locality
    • Big Data Hadoop Certification Architecture
    • Map Reduce & HDFS
    • Using the Big Data Hadoop Certification single node image (Clone)
    Module 4: Big Data Hadoop Certification Distributed File System (HDFS)
    • HDFS Design & Concepts
    • Blocks, Name nodes and Data nodes
    • HDFS High-Availability and HDFS Federation
    • Big Data Hadoop Certification 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 Big Data Hadoop Certification 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 Big Data Hadoop Certification Configuration API discussion
    • Emulating “grep” for searching inside a file in Big Data Hadoop Certification
    • DBInput Format
    • Job Dependency API discussion
    • Input Format API discussion,Split API discussion
    • Custom Data type creation in Big Data Hadoop Certification
    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
    Show More
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    Our Top Hiring Partner for Placements

    ACTE Dubai offers placement opportunities as add-on to every student / professional who completed our classroom or online training. Some of our students are working in these companies listed below.
    • We are associated with top organizations like HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc. It make us capable to place our students in top MNCs across the globe
    • We have separate student’s portals for placement, here you will get all the interview schedules and we notify you through Emails.
    • After completion of 70% Big Data Hadoop Certification training course content, we will arrange the interview calls to students & prepare them to F2F interaction
    • Big Data Hadoop Certification Trainers assist students in developing their resume matching the current industry needs
    • We have a dedicated Placement support team wing that assist students in securing placement according to their requirements
    • We will schedule Mock Exams and Mock Interviews to find out the GAP in Candidate Knowledge

    Get Certified By MapR Certified Big Data Hadoop Certification 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

    Get Certified

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

    Get Certified

    About Experienced Big Data Hadoop Certification Trainer

    • Our Big Data Hadoop Certification Training in Dubai. Trainers are certified professionals with 7+ years of experience in their respective domain as well as they are currently working with Top MNCs.
    • As all Trainers are Big Data Hadoop Certification domain working professionals so they are having many live projects, trainers will use these projects during training sessions.
    • All our Trainers are working with companies such as Cognizant, Dell, Infosys, IBM, L&T InfoTech, TCS, HCL Technologies, etc.
    • Trainers are also help candidates to get placed in their respective company by Employee Referral / Internal Hiring process.
    • Our trainers are industry-experts and subject specialists who have mastered on running applications providing Best Big Data Hadoop Certification training to the students.
    • We have received various prestigious awards for Big Data Hadoop Certification Training in Dubai from recognized IT organizations.

    Big Data Hadoop Certification Course FAQs

    Looking for better Discount Price?

    Call now: +91-7669 100 251 and know the exciting offers available for you!
    • 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
    ACTE
      • Gives
    Certificate
      • For Completing A Course
    • 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 .
    • The entire Big Data Hadoop Certification 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 Big Data Hadoop Certification Course At ACTE?

    • Big Data Hadoop Certification Course in ACTE is designed & conducted by Big Data Hadoop Certification experts with 10+ years of experience in the Big Data Hadoop Certification 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 project experience, job support, and lifetime resources.
    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 Big Data Hadoop Certification batch to 5 or 6 members
    Our courseware is designed to give a hands-on approach to the students in Big Data Hadoop Certification . 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 76691 00251 / 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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          Job Opportunities in Big Data

          More than 35% of Data Professionals Prefer Big Data. Big Data Is Widely Recognized as the Most Popular and In-demand Data Technology in the Tech World.

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