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Course Outline
- Introduction to Data Processing and Analysis
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Basic Information about the KNIME Platform
- installation and configuration
- overview of the interface
- Discussion of the Platform in Terms of Tool Integration
- Introduction to Workflow Creation
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Methodology for Creating Business Models and Data Processing Processes
- documentation
- methods for importing and exporting processes
- Overview of Basic Nodes
- Discussion of ETL Processes
- Data Exploration Methodologies
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Data Import Methodology
- data import from files
- data import from relational databases using SQL
- creating SQL queries
- Overview of Advanced Nodes
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Data Analysis
- preparing data for analysis
- data quality and validation
- statistical data analysis
- data modeling
- Introduction to Using Variables and Loops
- Building Advanced, Automated Processes
- Visualizing Results
- Public and Free Data Sources
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Basics of Data Mining
- discussion of selected types of data mining tasks and processes
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Knowledge Discovery from Data
- Web Mining
- SNA - Social Networks
- Text Mining - Document Analysis
- data visualization on maps
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Integrating Other Tools with KNIME
- R
- Java
- Python
- Gephi
- Neo4j
- Building Reports
- Training Summary
Requirements
Basic knowledge of mathematical analysis.
Basic knowledge of statistics.
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.
