Hadoop/Big Data is one of the most demanded skills. Hadoop offers very good pay package and profile to the candidates. Hadoop is an open source technology and written in Java-based programming framework that supports the processing and storage of large data sets in a distributed computing environment.
Hadoop modules are a much easier solution for BigData Problem. It is also open source technology, Based on open source platforms. Contains several tools for entire ETL data processing Framework, It can process distributed data over multiple storages as Hadoop is SQL based tools. Learn Well Technocraft’s Big Data Training in Pune is best as per market requirement in industry.
More Than an Education: Big Data/Hadoop Course gives you the knowledge, confidence, and experience to help you make your professional career better.
Stand Apart in The Crowd With Certification: Big Data/Hadoop Course makes you more selective in the eyes of future employers and helps to increase your earning potential.
Better Career Prospects: Hadoop’s vocational degree can significantly increase your job possibilities at the same time as providing you with professional skills and knowledge.
Hadoop/Big Data is one of the most demanded skills. Hadoop offers a very good pay package and profile to the candidates. Hadoop is an open source technology written in Java-based programming framework that supports the processing and storage of large data sets in a distributed computing environment.
1) Big Data Basics:
Understanding of Big Data and its Echosystem
Distributed computing
Hadoop 1 and Hadoop 2 understanding
Hadoop core components and echosystem
HDFS -Hadoop Distributed File System
Unix and HDFS commands
Map Reduce a processing framework
Cloudera Installation
2) Data Ingestion – Sqoop :
Data Ingestion
ETL and ELT
Sqoop architecture
Data ingestion with sqoop
Incremental Sqoop
Data export
Sqoop automation using Sqoop Jobs
Industry use case and Interview Guide
3) Data Processing using Hive:
Sql basics
HQL vs SQL
Hive on topof Hadoop
Hive Basics
Hive Advance
Hive Optimization -Partitioninng , Bucketing , bucket join ,
windowing and analytical functions , UDF
Hive Special file format – Parquet, ORC, Avro
Hive compression type and uses
Industry use case and Interview Guide
4) Working on NoSQL DB : HBASE
NOSQL Basics
HBASE Architecture and Processing
HBASE Basics
HBASE Integration with Hive
5) Transforming data with Spark:
SCALA basics
Scala for Spark
Basics of Spark
MR Vs Spark
Spark in depth
SPARK Core – RDD
Spark Structure API – DataFrame , Dataset, Saprk Sql
File formats in Spark -Parquet, ORC, Avro
Spark Transformation and Action
Spark Optimization – Partitioning , Bucketing , Joins
Broadcast join vs SMB Join
Spark Advance level Optimization
Spark and Hive Integration
Spark UI
Industry use case and Interview Guide
6) Big Data on Cloud – AWS
AWS basics
AWS Big Data and Data Analytics basics
AWS S3 – Simple Storage Service
S3 vs HDFS
AWS Redshift, Athena,EMR
Industry use case and Interview Guide
7) Interview Preparation guide, Mock Interview sessions and resume review and tips
There is no prerequisite as such to learn Big Data. Though basic understanding of a programming language like Java, Spark etc will help.
Along with it hardworking in nature ,eagerness to learn and interest in Big Data and Data handling.
Big Data and Hadoop is not 1 tool its echo system which is the combination of different tools and technology which help in completing big data life cycle including Sqoop, Hive, HBASE, Spark, KAFKA, FLUME,PIG and many more, In order to become a good Big Data engineer you don’t need to be master of every tools and technologies but its mandatory to have in depth understanding of – Spark, Hive, Sqoop and anyone cloud preferring AWS.
Big data classes in Pune at Learn Well Technocraft course in a way that we cover all mandatory tools and technology that is required for Big Data and Spark developer/engineer.
Learn Well Technocraft have been pioneers in providing learning on Hadoop and Big Data for the last 12 years. Connect to us to know more about how we can assist.