KNIME Analytics Platform - comprehensive training Training Course

  1. Data Analysis Training
  2. KNIME Training
  3. KNIME Analytics Platform - comprehensive training Training Course

Course Code

knimecompr

Duration

35 hours (usually 5 days including breaks)

Requirements

Analytical thinking approach.

Basics of statistics and mathematical analysis.

Overview

KNIME is a free and open-source data analytics, reporting and integration platform. KNIME integrates various components for machine learning and data mining through its modular data pipelining concept. A graphical user interface and use of JDBC allows assembly of nodes blending different data sources, including preprocessing (ETL: Extraction, Transformation, Loading), for modeling, data analysis and visualization without, or with only minimal, programming. To some extent as advanced analytics tool KNIME can be considered as a SAS alternative.

Since 2006, KNIME has been used in pharmaceutical research, it also used in other areas like CRM customer data analysis, business intelligence and financial data analysis.

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

Testimonials

★★★★★
★★★★★

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