Course Outline

  1. Introduction to data processing and data analysis
  2. Fundamental information of KNIME platform
  • Installation and configuration
  • Overview of the interface
  1. Discussion of tool integration
  2. Building workflows
  3. Methodology of creating business models and data modeling
  • Documentation
  • import and export workflows
  1. Basic nodes
  2. Design ETL processes
  3. Data mining
  4. Data Import 
  • from files
  • from relational databases using SQL
  • creating SQL queries
  1. Advanced nodes
  2. Data analysis:
  • data preparation
  • data check-up
  • statistical data examination
  • data modeling
  1. Introduction to Flow Variables and Loops
  2. Advanced process automation
  3. Visualization Features
  4. Open source data sources
  5. Data mining basics
  • selected types of Data Mining tasks and processes
  1. Getting more knowlegde from data
  • Web Mining
  • SNA
  • Text Mining
  • Data visualization on graphs
  1. Install Extensions and Integrations
  • R
  • Java
  • Python
  • Gephi
  • Neo4j
  1. Reporting
  • Overview
  • BIRT Integration
  • KNIME WebPortal
  1. Conclusion and Q&A session

Requirements

Analytical thinking approach.

Basics of statistics and mathematical analysis.

  35 Hours

Number of participants



Price per participant

Testimonials (2)

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