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Sii Poland

SII UKRAINE

SII SWEDEN

Send your request
Course objectives

Introduction to data processing on the Apache Hadoop – Cloudera platform using Apache Hive, Impala, Sqoop and HBase database frameworks.

Benefits

Participants will learn and understand:

  • A practical approach to data processing on the Apache Hadoop platform
  • Apache Hadoop platform architecture
  • Working environment
  • Work with data
  • Real use cases

Participants will be able to:

  • Create data processing tasks
  • Create data-oriented systems
Training scope
  • Big Data in data engineering
  • Historical outline – basic concepts
    • Apache Hadoop – theoretical overview
    • Architectural concepts used in on-premise solutions
    • Key players and technologies
  • Apache Hive
    • Definitions, operations and aggregation of data
    • Performance and optimization
  •  Apache Impala
    • Key elements
    • Query language
    • Efficiency
    • Integration with other frameworks
  •  Apache HBase
    • NoSQL
    • Schema definition
    • Data Types
    • Operations and scans
    • Filters and counters
    • Designing keys
    • Framework clients
  •  Apache Sqoop
    • Importing and exporting data
    • Integration with the Hadoop ecosystem
  • Project / exercises
    • Building a comprehensive solution to integrate the above platforms
Audience

People involved in data processing in databases, data warehouses or BI. Engineers who work with different data sources and data formats on a daily basis

Course objectives

Introduction to data processing on the Apache Hadoop – Cloudera platform using Apache Hive, Impala, Sqoop and HBase database frameworks.

Benefits

Participants will learn and understand:

  • A practical approach to data processing on the Apache Hadoop platform
  • Apache Hadoop platform architecture
  • Working environment
  • Work with data
  • Real use cases

Participants will be able to:

  • Create data processing tasks
  • Create data-oriented systems
Training scope
  • Big Data in data engineering
  • Historical outline – basic concepts
    • Apache Hadoop – theoretical overview
    • Architectural concepts used in on-premise solutions
    • Key players and technologies
  • Apache Hive
    • Definitions, operations and aggregation of data
    • Performance and optimization
  •  Apache Impala
    • Key elements
    • Query language
    • Efficiency
    • Integration with other frameworks
  •  Apache HBase
    • NoSQL
    • Schema definition
    • Data Types
    • Operations and scans
    • Filters and counters
    • Designing keys
    • Framework clients
  •  Apache Sqoop
    • Importing and exporting data
    • Integration with the Hadoop ecosystem
  • Project / exercises
    • Building a comprehensive solution to integrate the above platforms
Audience

People involved in data processing in databases, data warehouses or BI. Engineers who work with different data sources and data formats on a daily basis

The number of participants: 8-15 people

Duration: 2 days

Available language: PL / EN

Available course material: PL / EN

Course form
Presentation, workshop, exercises, discussion

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Natalia & Agata

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