You can attend 1st 2 classes or 3 hours for free. once you like the classes then you can go for registration.
or full course details please visit our website www.hadooponlinetraining.net
Duration for course is 30 days or 45 hours and special care will be taken. It is a one to one training with hands on experience.
* Resume preparation and Interview assistance will be provided.
For any further details please contact
INDIA: +91-9052666559
USA: +1-6786933994, 6786933475
visit www.magnifictraining.com
please mail us all queries to info@magnifictraining.com
Ride the Storm: Navigating Through Unstable Periods / Katerina Rudko (Belka G...
Big data and hadoop certification training
1. Big-Data and Hadoop
Certification Training
Course Objective Summary
*During this course, you will learn
*Introduction to Big Data and
Hadoop.
*Hadoop ecosystem – Concepts.
* Hadoop Map-features reduce
concepts.
2. *Big-Data and Hadoop Certification
Training
• CONTACT US:
• Call :
• india +91-9052666559
• USA:+1-6786933994, 6786933475
• Mail :info@magnifictraining.com
• Visit : www.magnifictraining.com
3. Big-Data and Hadoop Certification
Training
• ADpevpelilcoaptiinogn st he map-reduce
• Pig concepts
• Hive concepts
• Oozie workflow concepts
• HBASE Concepts
• Real Life Use Cases
4. Big-Data and Hadoop Certification
Training
• Introduction to Big Data and
• Hadoop
• What is Big Data?
• bWigh adta atare?
• the challenges for processing
• What technologies support big data?
• What is Hadoop?
• Why Hadoop?
5. Big-Data and Hadoop Certification
Training
• Use Cases of Hadoop
• Histiry of Hadoop
• Hadoop eco systems
• Hdfs
• Map reduce
• Statistics
6. Big-Data and Hadoop Certification
Training
• Understanding the Cluster
• Typical workflow
• Writing files to HDFS
• Reading files from HDFS
• Rack Awareness
7. Big-Data and Hadoop Certification
Training
• Let's talk Map Reduce
• Before Map reduce
• Map Reduce Overview
• Word Count Problem
• Word Count Flow and Solution
• Map Reduce Flow
• pArlgoobrleitmhms s
8. Big-Data and Hadoop Certification
Training
• Developing the Map Reduce
• Application
• Data Types
• File Formats