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Course Outline
- An introduction to data processing and analysis
- Basic information about the platform KNIME
- installation and configuration
- interface overview
- Discussion of the platform in terms of tool integration
- Introduction to work. Creating flows
- Methodology for creating business models and data processing processes
- work documentation
- process import and export methods
- Overview of basic nodes
- Overview of ETL processes
- Data mining methodologies
- Data import methodology
- import data from files
- importing data from relational databases using SQL
- creating queries SQL
- Advanced nodes overview
- Data analysis
- preparing data for analysis
- quality and data checking
- statistical examination of data
- data modeling
- Introduction to the use of variables and loops
- Building advanced, automated processes
- Visualization of results
- Publicly available and free data sources
- Basics Data Mining
- Overview of selected types of tasks and processes Data Mining
- Discovering knowledge from data
- Web Mining
- SNA – social networks
- Text Mining – document analysis
- data visualization on maps
- Integration of other tools with KNIME
- R
- Java
- Python
- Gephi
- Neo4j
- Building reports
- Training summary
Requirements
Analytical thinking approach.
Basics of statistics and mathematical analysis.
35 Hours
Testimonials (2)
It's a hands-on session.
Vorraluck Sarechuer - Total Access Communication Public Company Limited (dtac)
Course - Talend Open Studio for ESB
La capacitacidad de la herramienta
