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Course Outline
- Introduction to data processing and data analysis
- Fundamental information of KNIME platform
- Installation and configuration
- Overview of the interface
- Discussion of tool integration
- Building workflows
- Methodology of creating business models and data modeling
- Documentation
- import and export workflows
- Basic nodes
- Design ETL processes
- Data mining
- Data Import
- from files
- from relational databases using SQL
- creating SQL queries
- Advanced nodes
- Data analysis:
- data preparation
- data check-up
- statistical data examination
- data modeling
- Introduction to Flow Variables and Loops
- Advanced process automation
- Visualization Features
- Open source data sources
- Data mining basics
- selected types of Data Mining tasks and processes
- Getting more knowledge from data
- Web Mining
- SNA
- Text Mining
- Data visualization on graphs
- Install Extensions and Integrations
- R
- Java
- Python
- Gephi
- Neo4j
- Reporting
- Overview
- BIRT Integration
- KNIME WebPortal
- Conclusion and Q&A session
Requirements
Analytical thinking approach.
Basics of statistics and mathematical analysis.
35 Hours
Testimonials (2)
Very useful in because it helps me understand what we can do with the data in our context. It will also help me
Nicolas NEMORIN - Adecco Groupe France
Course - KNIME Analytics Platform for BI
It's a hands-on session.
