Knowledgehut INC

Big data Analytics

Knowledgehut INC
  • Knowledgehut INC

Originalpreis in GBP:
£ 999

Wichtige informationen

Tipologie Kurs
Methodologie Online
Unterrichtsstunden 30h
Beginn nach Wahl
Online Campus Ja
Versendung von Lernmaterial Ja
Beratungsservice Ja
Virtueller Unterricht Ja
  • Kurs
  • Online
  • 30h
  • Beginn:
    nach Wahl
  • Online Campus
  • Versendung von Lernmaterial
  • Beratungsservice
  • Virtueller Unterricht

Big Data analytics is the process of gathering, managing, and analyzing large sets of data (Big Data) to uncover patterns and other useful information.  These patterns are a minefield of information and analysing them provide several insights that can be used by organizations to make business decisions. This analysis is essential for large organizations like Facebook who manage over a billion users every day, and use the data collected to help provide a better user experience.  

Wichtige informationen
Welche Ziele verfolgt der Kurs?

1. Understand the Fundamentals
2. Learn Pig framework
3. Understand the Hive framework
4. Perform Real-time analysis
5. Choose the best tool

Ist dieser Kurs für mich?

1. professionals who want to acquire knowledge on big data
2. Data Architects
3. Data scientist
4. Developers
5. Data Analyst
6. BI Analyst
7. BI Developers
8. SAS Developers
9. project managers
10. mainframe and analytics professionals

Wie geht es nach der Info-Anfrage weiter?

An Expert from Knowledgehut will take it forward.

Voraussetzungen: There are no specific prerequisites required to learn Big Data.





nach Wahl Anmeldung möglich

Was lernen Sie in diesem Kurs?

Architecture Design
Architecture landscape
Big Data
Data science


1. introduction big data & Hadoop :
  • Big Data Introduction,
  • Hadoop Introduction and Hands On
2. Hadoop daemon processes :
  • Name Node
  • Data Node
  • Secondary Name Node
  • Job Tracker
  • Task Tracker
Hands On 3:
  • HDFS : Blocks and Input Splits
  • Data Replication
  • Hadoop Rack Awareness
  • Cluster Architecture and Block Placement
  • Accessing HDFS
  • JAVA Approach
  • CLI Approach
Hands On 4.
  • Hadoop installation Modes and HDFS
5. Hadoop Developer tasks :
  • Basic API Concepts
  • The Driver Class
  • The Mapper Class
  • The Reducer Class
  • The Combiner Class
  • The Partitioner Class
Examining a Sample MapReduce Program with several examplesHadoop's Streaming API

Hands On 6.
  • Hadoop Ecosystems : PIG concepts
  • Install and configure PIG on a cluster
  • PIG Vs MapReduce and SQL
  • Write sample PIG Latin scripts
  • Modes of running PIG
  • PIG UDFs Hive concepts
  • Hive architecture
  • Installing and configuring HIVE
  • Managed tables and external tables
  • Joins in HIVE
  • Multiple ways of inserting data in HIVE tables
  • CTAS, views, alter tables
  • User defined functions in HIVE
  • Hive UDF SQOOP concepts
  • SQOOP architecture
  • Install and configure SQOOP
  • Connecting to RDBMS
  • Internal mechanism of import/export
  • Import data from Oracle/MySQL to HIVE
  • Export data to Oracle/MySQL
  • Other SQOOP commands. HBASE concepts
  • ZOOKEEPER concepts
  • HBASE and Region server architecture
  • File storage architecture
  • NoSQL vs SQL
  • Defining Schema and basic operations
  • DDLs
  • DMLs
  • HBASE use cases OOZIE concepts
  • OOZIE architecture
  • Workflow engine
  • Job coordinator
  • Installing and configuring OOZIE
  • HPDL and XML for creating Workflows
  • Nodes in OOZIE
  • Action nodes and Control nodes
  • Accessing OOZIE jobs through CLI, and web console
  • Develop and run sample workflows in OOZIE
  • Run MapReduce programs
  • Run HIVE scripts/jobs.FLUME Concepts
  • FLUME Architecture
  • Installation and configurations
  • Executing FLUME jobs
7. Data Analytics using pentaho as an ETL tool :
  • Data Analytics using Pentaho as an ETL tool
  • Big Data Integration with Zero Coding Required
Hands on 8. Integrations :
  • MapReduce and HIVE integration
  • MapReduce and HBASE integration
  • Java and HIVE integration
  • HIVE - HBASE Integration
  • Hands On"