Tools & Technologies

  • Apache Kafka
  • cassandra
  • Hadoop mapreduce
  • splunk
  • mongo db
  • presto
  • R language
  • spark
  • tableau
  • Add More

Big Data Analytics Training Objectives

  • Helps employees to bridge the IT skills gap with data and analytics.
  • Teams can build an analytics practice with right analytical tools and techniques
  • Derive the right decisions from the right data insights.
  • Accelerate innovation and tackle business challenges with an analytical approach.
  • Analytical understanding of business with comprehensive set of tools.
  • Identify crucial hidden points within large datasets to influence business decisions

Why Mazenet?

Expert Faculty

Our Faculty comprises of 150+ SMEs with more than 15 years of experience. All our trainers possess a minimum of 8+ years of experience.

Proven Track Record

We have served over 50 global corporate clients, consistently maintaining a 99% success rate in meeting training objectives for 100+ technologies with quick turn around time.

Blended Learning

We provide course content over any platform that our clients prefer. You can choose an exclusive platform or a combination of ILT, VILT, and DLP.

Learning Paths

The learning paths are very defined with clear benchmarks. Quantitative assessments at regular intervals measure the success of the learning program.

Case Study

We have amassed over 10,000 case studies to support training delivery. Candidates will be trained to work on any real-time business vertical immediately after the training.

24*7 Global Availability

We are equipped to conduct training on any day, date or time. We have delivered training pan India, Singapore, North America, Hong Kong, Egypt and Australia.

Key Features

virtual-led
Customized Training Modules

Training programs are highly flexible with module customizations to suit the requirements of the business units.

virtual-led
Certification

The training can be supplemented with appropriate certifications that are recognized across the industry.

virtual-led
Multi-language Support

Course content can be delivered in English, Spanish, Japanese, Korean or any other language upon request.

virtual-led
Personalized Training Reports

Candidates are assessed individually at regular intervals and are provided unique learning suggestions to suit their learning calibre.

virtual-led
Industry Oriented Training

Industry-oriented training, completing which, candidates can be immediately deployed for billable projects.

virtual-led
Diverse Training Platforms

Choose from Instructor-Led Training, Virtual Instructor-Led Training, Digital Learning Platform and Blended Training platforms

Big Data Analytics Training

Mazenet’s industry-oriented big data corporate training approach from real-time training experts will help in driving knowledge of all complex applications of Big Data Analytics.

This Big Data training program covers Hadoop, Scala and Spark while working on real-time industry-oriented case-study projects. In this Big Data course, you will master MapReduce, Hive, Pig, Sqoop, Oozie and Flume for cluster setup, Spark framework and RDD, Scala and Spark SQL, Machine Learning using Spark, Spark Streaming, etc.

This course is comprehensive, filled with hands-on activities and exercises. There are a range of activities in this course for people at every level. The course provides a deep understanding of Big Data and its associated distributed systems which you can apply for real world applications like analyzing financial data or using machine learning to classify customer behavior.

The course modules are structured to give an empirical value and understanding to the candidates. However, all course modules are highly customizable and can be structured to suit the requirements of your organization.

Course Preview

  • Hadoop Configuration and Installation
  • HDFS
  • Hadoop based Projects
  • Hadoop cluster Architecture
  • Hadoop cluster configuration
  • Hadoop cluster modes
  • Basics of Hadoop Eco-System
  • Single node and Multi-Node Cluster
  • Hadoop Shell Commands
  • Map Reduce Architecture
  • Necessity of MapReduce
  • Map Reduce Programs in Java
  • Input Splits
  • HDFS Blocks
  • YARN workflow
  • Traditional Way Vs MapReduce way
  • Counters
  • Joining Data Sets
  • Distributed Cache
  • Streaming
  • Distributed Joins
  • MR Unit
  • Real-Time Example
  • Introduction to Hive
  • HQL
  • Introduction to H-Base and No-SQL Data Base
  • H-Base Architecture
  • Comparison of SQL and HQL
  • Hive Datatypes
  • Hive Tables
  • Importing and Querying Data in Hive
  • Running Hive Scripts
  • HBase Vs Traditional Database
  • Partitions
  • Introduction to Pig
  • Pig Architecture
  • Pig data types
  • Pig Vs MapReduce
  • Coupling Pig and MapReduce
  • Pig Latin
  • Pig Scripting
  • Pig UDF
  • Pig Streaming
  • Pig Script testing
  • Importing Pig Jars
  • Pros and Cons of Pig
  • Real-time Example

Our Clients

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