big-data-and-hadoop

Big Data and Hadoop

OUR ALUMNAE

Ashish Shah PfMP results
Ashish Shah PfMP results
Ashish Shah PfMP results
Ashish Shah PfMP results
Ashish Shah PfMP results
Ashish Shah PfMP results
Ashish Shah PfMP results
Ashish Shah PfMP results
Ashish Shah PfMP results

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DESCRIPTION

Hadoop is an open source programming framework based on Java. It has been developed primarily for storing & processing extremely large unstructured data in a distributed computing environment. With Hadoop, applications can be run on thousands of distributed commodities hardware called as nodes and can handle thousands of terabytes. Its distributed file system facilitates very fast data transfer rates among nodes over network. The inbuild redundancy allows to recover from node failures.

Hadoop has emerged as the foundation of big data and its processing such as analytics, handling humongous amount of data generated from internet of things (IoT) sensors.

  • Master fundamentals of Hadoop 2.7 and YARN and write applications using them
  • Setting up Pseudo node and Multi node cluster on Amazon EC2
  • Master HDFS, MapReduce, Hive, Pig, Oozie, Sqoop, Flume, Zookeeper, HBase
  • Learn Spark, Spark RDD, Graphx, MLlib writing Spark applications
  • Master Hadoop administration activities like cluster managing,monitoring,administration and troubleshooting
  • Configuring ETL tools like Pentaho/Talend to work with MapReduce, Hive, Pig, etc
  • Detailed understanding of Big Data analytics
  • Hadoop testing applications using MR Unit and other automation tools.
  • Work with Avro data formats
  • Practice real-life projects using Hadoop and Apache Spark
  • Be equipped to clear Big Data Hadoop Certification.

Hadoop

        + Hadoop Distributed File System (HDFS) – storing data across thousands of commodity servers with high data transfer rate supported. 

        + Hadoop's Yet Another Resource Negotiator (YARN) – resource management & scheduling for user applications.

        + MapReduce – programming interface to handle large distributed data processing – mapping data and reducing it to result.

HBase – An open source, nonrelational, distributed database.

Apache Flume – Collect, aggregate, and move huge volume of streaming data into HDFS.

Apache Hive – A data warehouse data provides data summarization, query, and analysis. 

Apache Pig – A high level open source platform for creating parallel programs that run-on Hadoop.

Apache Sqoop – A tool to transfer bulk data between Hadoop and structured data stores (RDBMS) 

Apache oozie – Workflow scheduler for managing Hadoop jobs. 

Apache Spark – A fast engine for big data processing capable of streaming and supporting SQL, Machine Learning, and graph processing. 

Apache Zookeper – An open source configuration, synchronization, and naming registry service for large distributed systems. 

NoSQL – “Not only” or “Non-relational” SQL for storage and retrieval of data which is modelled unlike tabular relations as in relational databases. 

        + Cassandra or MongoDB

We will share the reading material before the lectures
  • Java
  • Basics of Linux

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Our Testimonials

Manali Khimasia

Attending Addon Skills PgMP certification course gave me a lot of confidence for attempting the exam and I successfully cleared the exam on my first attempt. The course material was thorough and all important concepts were explained in detail during the 3 days training. The best part about Addon Skills was that the training was not limited to 3 day classroom session. Another 10 online sessions were conducted to discuss questions and clear doubts. We were also provided with videos, question banks and highlights of important concepts and likely questions from SPMv3. Besides, Kailash personally reviewed each of our applications multiple times and gave valuable feedback for improvements till it was ready for submission. I strongly recommend Addon Skills for professional certification preparation courses since they provide complete guidance and support till the date you take your certification exam.

Sachin Shirke

I was fortunate to be well trained by Addon Skills team for PgMP certification and well supported me during my journey of achieving PgMP. They have a skilled professional trainer who understands your issues and makes you comfortable while imparting complex knowledge. The best part of Addon Skills team is the total commitment towards your success. Even after training, they kept in touch with me to check on my progress and any queries I had and ensured I am focused on achieving PgMP. From the first day, they provided me tremendous confidence booster till the last day. Considering the complexity of PgMP I never imagined that my journey will be so much fun, fruitful and enriching.

Nitin Rai

Addon Skills sheer committment anf focused approach toward each and every aspirant ensures every aspirant achieve their goal. I must say their overall training approach, study materials, question bank, post training support helped me alot in my journey of PgMP certification. Best part of joining your course is that you will get introduced to multiple aspirant who have same goal as you and interaction with same group help you to not only clear your doubt and query but also stay motivated and focused for exam, Also the process of un-learn few of our way of doing things and re-learn few new things as per PMI way. This is where your help comes very handy. Lastly, I want to wish all the very best to all PgMP aspirant.

Vinit Menon

Thanks for the excellent training on PMP. The concepts and processes was clearly explained by Kailash. He was very disciplined and more focused on trainees efforts to understand PMP instead of finishing the workshop as soon as possible. I would recommend kailash for PMP training for those who are interested in PMP training.

Deepti Jagtap

Thank you sir for a your training,it was a good experience and learning.kailash upadhyay is good trainer, if any1 want to do PMP, u can join his training.. He clears all the concept and makes training interactive by discussing many different topics and examples of subject.

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