Big data Analytics- LIVE VIRTUAL
Course
Online
Provide a better user experience thanks to big data!
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Type
Course
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Methodology
Online
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Class hours
30h
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Duration
Flexible
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Start date
Different dates available
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Online campus
Yes
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Delivery of study materials
Yes
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Support service
Yes
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Virtual classes
Yes
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.
Facilities
Location
Start date
Start date
About this course
1. Understand the Fundamentals
2. Learn Pig framework
3. Understand the Hive framework
4. Perform Real-time analysis
5. Choose the best tool
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
There are no specific prerequisites required to learn Big Data.
An Expert from Knowledgehut will take it forward.
Reviews
This centre's achievements
All courses are up to date
The average rating is higher than 3.7
More than 50 reviews in the last 12 months
This centre has featured on Emagister for 7 years
Subjects
- Architecture Design
- Architecture landscape
- Architecture
- Replication
- Introduction
- Processes
- Big Data
- Data science
- Hadoop
- Placement
- Tracker
Course programme
- Big Data Introduction,
- Hadoop Introduction and Hands On
- Name Node
- Data Node
- Secondary Name Node
- Job Tracker
- Task Tracker
- HDFS : Blocks and Input Splits
- Data Replication
- Hadoop Rack Awareness
- Cluster Architecture and Block Placement
- Accessing HDFS
- JAVA Approach
- CLI Approach
- Hadoop installation Modes and HDFS
- Basic API Concepts
- The Driver Class
- The Mapper Class
- The Reducer Class
- The Combiner Class
- The Partitioner Class
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
- Data Analytics using Pentaho as an ETL tool
- Big Data Integration with Zero Coding Required
- MapReduce and HIVE integration
- MapReduce and HBASE integration
- Java and HIVE integration
- HIVE - HBASE Integration
- Hands On"
Big data Analytics- LIVE VIRTUAL