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Big Data

An Interactive Live Training

About Big Data Live Training

Getting intellectuals ready to become Big Data Experts!

During this live training you will learn about the different ingredients of Big Data such as Hadoop, Spark, Pig, Hive, Sqoop etc.


Further you will have hands-on experience on different pillars of the Big Data Ecosystem starting from parallel processing frameworks like Map Reduce & Spark, Distributed Storage techniques like HDFS, Big Data Administration Ambari etc.


At the end the training you will have in-depth understanding & hands-on related to Big Data solutions like Cloudera & HortonWorks.

View Course Outline Reserve Your Seat

Our Approach for Live Classes

After establishing a reputable Physical Training Model, based on our stellar records and customer earned trust we gradually progressed to establish the same reputation in the Live Training Model. We are committed to empower you by making our trainings accessible, interactive, and well curated specifically to your objective.



Registrations Open


7 Weeks (Saturday)


10:00AM to 6:00PM


Limited seats!


Meet the trainers of this course who are Big Data Experts!


Mr. Asim Rashid

Consultant & Trainer (Big Data and Analytics, Cloud Architect, Systems Integration)

Asim Rashid has 14+ years of Technical experience in ICT industry. He has extensive experience in planning, deploying, optimizing and troubleshooting Big Data Solutions (Hortonworks, Cloudera, Oracle Big Data & Huawei Big Data). He has been working on Big Data Development through SPARK, Hadoop, HIVE & KAFKA. His expertise includes ETL/ELT (Big Data Integrator, Oracle Golden Gate, Talend), Oracle BI, Power BI and Data Virtualization.


Mr. Bilal Maqsood

Big Data Engineer & Trainer - Dice Analytics

Bilal Maqsood is an experienced Big Data Specialist and has been associated with Telecom Sector. He has his vast experience in SQL, Spark, Analysis of Big Data with Hive, Big Data Modeling, Architecting Big Data Applications and Hadoop for Big Data



Course Outline



Week 1

What is Big Data?
Big Data Era
Big Data- Data Sources
4 V’s of Big Data
Conventional Data Warehouse Architecture
Modern Data Warehouse Architecture
What is Data Discovery?
Distributed Computing & its Advantage
Big Data Processing Frameworks (Hadoop, Apache Spark, NoSQL Databases)
What is Hadoop & its History?
Apache Hadoop Stack
Introduction to Hortonworks, Cloudera & MapR (Their Differences)
Basics of Flume, Sqoop, Zookeeper, Ozie, HBase, Mahout, Hive, Pig
Hadoop Cluster (Master Node, Data Node, Namenode, Job Tracker, Task Tracker)
Hortonworks Sandbox Installation
HDFS Working
HDFS Block Size
HDFS Replication Factor
HDFS Write
HDFS Pipeline Writing

Week 2

Parallel Processing Basics
Map & Reduce
Hortonworks Configuration & Overview
Hortonworks HDFS Ingestion Lab
HDFS Commands
HDFS Data Ingestion Lab
Map Reduce Implementation
Hive Alignment with SQL
Hive Query Process
Hive Data Loading
Hive Managed Tables
Hive External Tables
Hive Table Location
Hive Bucketing & Partitioning
Hortonworks Hive Lab
Hive Views
Hive use for XML
Hive Supported File Format
Hive Data Model
Block Compression
Storage Formats in Hive

Week 3

Hadoop 1.0 VS Hadoop 2.0
YARN Architecture
YARN Resource Manager
YARN Node Manager
YARN Application Manager
YARN High Availability
YARN Request Model
YARN Schedulers
YARN Performance Gauging
YARN Performance Measuring
YARN System Health
Resource Allocation in YARN
Hortonworks Yarn Lab
Containers Concept in Hadoop
Tez Framework

Week 4

PIG Architecture
Grunt Shell & PIG Scripting
PIG Commands
Loading Data in PIG
PIG Filter
PIG Joins
Debugging Using PIG
PIG Execution Modes
PIG Execution Mechanism
Sqoop Architecture
Sqoop Execution Modes
Sqoop Lap
Lambda & Kafka Architecture & their Applications

Week 5

Why Apache Spark
Spark Driver
Spark Context
Spark Executors
Working with RDD
Spark Transformations (Map, Flatmap, Filter, Distinct)
Spark Actions (Collect, First, Take, Count, Reduce, Save-as-text)
Transformations VS Actions
Lazy Execution

Week 6

What is Spark Streaming
What is Spark SQL
Spark Lab
Loading Text File in Spark
Loading csv in Spark
Loading XML in Spark
Loading JSON in Spark
Introduction to

Week 7

Project & Test
Self-learning Path Guidance



Following is price for this extensive training on Big Data



Frequently Asked Questions

Who should attend the course?

Recent graduates, third year and final year students from the computer science disciplines.

Professionals from the computer science domain who want to shift the profession to Big Data Analytics.

Executives who want to build the initial knowledge about the impact of the Big Data ecosystem on organization growth.

Who are the Instructors?

What is the timing of the course?

Duration: 7 weeks

Class Days: Saturdays

Timings: 10:00 AM – 06:00 PM

Can I get a job after this course?

Since our instructors are industry experts so they do train the students about practical world and also recommend the shinning students in industry for relevant positions.

How much hands-on will be performed in this course?

Since our courses are led by Industry Experts so it is made sure that content covered in course is designed with hand on knowledge of more than 70-75 % along with supporting theory.

How much internet speed is required?

You will require 3GB internet speed or more for this live training session.

What are the PC requirements?

For Big Data Professional course, you need to have Minimum Core i3 PC, 4th Generation with 12GB RAM and ideally Core i7, 5th Generation with 16GB RAM.

Will I get a certificate after this course?

Yes, you will be awarded with a course completion certificate by Dice Analytics. We also keenly conduct an annual convocation for the appreciation and recognition of our students.

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