During the Six (6) weeks of the course, you will learn about the different ingredients of Big Data such as Hadoop, Spark, Pig, Hive, Sqoop etc.
In the subsequent weekly distribution of the course, participants 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 of the course candidates will have in-depth understanding & hands-on related to Big Data solutions like Cloudera & Horton works.
12th Dec, 2018
7 Weeks (Week Days)
09:00AM to 06:00PM
10 Seats Left
Following are the students who got placed in Industry after successfully being certified by Dice!
Meet the trainers of this course who are Big Data experts & are highly experienced!
What is Big Data
Big Data Era
Big Data- Data Sources
4 vs of Big Data
Convetional Datawarehouse Architecture
Modern Datawarehouse 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
Introductino to Hortonworks, Cloudera & Mapr (their difference)
Basics of Flume, Sqoop, Zookeeper, Ozie, HBase, Mahout, Hive, Pig
Hadoop Cluster (Master Node, Data Node, Namenode, Job Tracker, Task Tracker)
How HDFS works (Block Size, Replication Factor, HDFS Read, HDFS write, Pipleline writing)
Parallel Processing Basics
Map & Reduce
Hadoop 1.0 vs Hadoop 2.0
Cloudera Configuration & Overview
Hortonworks Configuration & Overview
Cloudera Data Ingestion Lab
Hortonworks HDFS Ingestion Lab
HDFS Commands
Cloudera HDFS Ingestion Lab
HDFS Data Ingestion Lap
Map Reduce Implementation Lab
Yarn Achritecture
Yarn Resource Manager
Yarn Node Manager
Yarn Application Manager
Yarn High Availability
Yarn Request Model
Yarn Schedualers
Hortonworks Yarn Lab
Cloudera Yarn Lab
Containers Concept in Hadoop
Hive
Hive Alignment with SQL
Hive Query Process
Hive Managed Tables
Hive External Tables
Hive Table Location
Hive Bucketing & Partitioning
Cloudera Hive Lab
Hortonworks Hive Lab
Hive Views
Tez Framework
Pig-Latin
Grunt Shell & Pig Scripting
Pig Commands
Pig Lab
Sqoop
Sqoop Lab
Hadoop Administration
Ambari
Zookeeper
Cloudera Manager
Hortonworks Ambari
Lambda & Kapka Architecture & their Applications
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 Evaluation
What is Spark Streaming
What is Spark SQL
Spark Lab
No SQL Databases
Why & when to use no SQL Databases
Cap theorem for no SQL Databases
No SQL Databases types (column oriented, key value oriented, graph oriented , document oriented)
Casandra Basics
Mongo DB Basics
Setup your own Hadoop Cluster using Amazon Services
Project.
Following is price for this extensive training on Big Data
Watch to find out that what our course attendees have to say about the course and the experience they have got with us!
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.
Duration: 7 weeks
Class Days: Week Days
Timings: 09:00 AM to 06:00 PM
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.
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.
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.
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.
With digital transformations running today’s hyper-connected world, Our full stack Data Analysts help in addressing the data challenges being faced!