Big Data and Hadoop Certification Course/Training

Location: Gurgaon

Dr. Sayaji Hande

Course Director

A renowned data scientist with two and a half decades of experience. PhD. in statistics from Purdue university and alumni of IIM, Ahmedabad and Indian Institute Statistical Institute. A multi patent holder and is on board of organizations and academic institutes of global repute. Played transformational roles in projects of high stake and impact with government and industry leaders.

Baljeet Singh

Master Faculty

Alumni of HBTI, Kanpur and MDI Gurgaon with 22 years of rich experience as a technology leader in world-class organizations. Founder and CEO of Digialaya, a state of the art voice over cloud platform integrated with Big Data, Artificial Intelligence and Machine learning. He possesses unparalleled experience of data science and engineering with expertise in various digital platforms and coding.

Expectations and Commitments

“You go ahead of scope of work to make us deliver above scope of value”

“You to be ambitious to shape your future to accomplish our commitment to nurture future”

“Solid execution aptitude to catch our regular updates of NextGen skills and knowledge to meet the pace of time”


Hadoop is one of the most demanding technologies that has made possible to analyze big data to reach at right decision in various industry to human lives. Be a part of this expedition and explore this tremendous flow of information with Hadoop’s way of distributed processing. Learn not only about the Hadoop ecosystem but also the different system and  their integration to solve the real-world problems. This course will make you learn all the elements of Big data technologies going beyond Hadoop into various distributed systems required to arrive at decisions in business.
This course will train you to manage bigdata on a cluster with storage at HDFS and process through MapReduce,Store and query your datawith Sqoop, Hive, MySQL, HBase, MongoDB, manage real time data with Kafkaand Flume,write programs with Pig and Spark. You will find lot of hands on activities and exercises to prepare you to implement your learning and address practical problems.


Case Studies


Capstone Projects

Live Projects

Length of course:

136 Hours

Course location:


By earning this certification, you will be able to :

  • Understand characteristics, types, sources and analytics of Bigdata
  • Explain the working of HDFS, List data access patterns and store data in HDFS cluster
  • Add and remove nodes from a cluster and modify Hadoop Configuration parameters
  • Write MapReduce programs to process bigdata and implement on Hadoop to solve complex business problems
  • Import or Export data into HDFS from common data sources like RDBMS, data warehouses, web server logs, etc using Sqoop and Flume
  • Start and configure a Flume agent
  • Create databases and table in Hive and do partitioning to improve the performance of queries
  • Load and export data into and out of Hive and use different queries
  • Use various operators and functions in Hive
  • Design, schedule and control workflow jobs using Oozie
  • Use graphical workflow editor tool for the generation of workflow and link multiple application to form new application
  • Use Load operator, relational operator and evaluation functions of Pig to study data sets and efficiently write mapper and reducer Programs
  • Use Zookeeper administration to maintain Zookeeper environment to ensure trouble free running of bigdata application
  • Learn relational model and its constraints, apply create, insert, select, update, delete and join table statements
  • Explain the concept, characteristics and categories of NoSQL databases and architectural differences in different categories
  • Understand the difference between local database system, hosted database, and
    database-as-a-service and parameters for the selection of data layer
  • Use Spark to access different data sources like HDFS, HBase etc.
  • Use Spark to manage data processing integrating SQL, streaming and analytics in the same application. Create parallelized collections and external datasetsand run Resilient Distributed Dataset (RDD) operations. Configure,monitor and tune Spark cluster
  • Understand components and architecture of Kafka Use Kafka Command line tools to create and absorb messages
  • Create database in MongoDB. Differentiate JSON and XML

• Engage in hands-on and project-based learning.
• Complete coding exercise to reinforce newly learned skills.
• Dive deeper into topics and techniques via programming labs.
• Receive individualized feedback and support from your instructional learn.
• Interaction with mentors.

  • Working Professionals
  • Hadoop Architects
  • Data Scientists
  • Data Analysts
  • Job Seekers / Changers

Interested In Taking this course?

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