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Course Outline
- Introduction to Data Processing and Analysis
- Basic Information about the KNIME Platform
- installation and configuration
- overview of the interface
- Discussion on Tool Integration within the Platform
- Introduction to Workflow Creation
- Methodology for Creating Business Models and Data Processing Processes
- work documentation
- methods of importing and exporting processes
- Overview of Basic Nodes
- Discussion on ETL Processes
- Data Exploration Methodologies
- Data Import Methodology
- data import from files
- data import from relational databases using SQL
- creating SQL queries
- Overview of Advanced Nodes
- Data Analysis
- preparing data for analysis
- data quality and validation
- statistical data examination
- data modeling
- Introduction to the Use of Variables and Loops
- Building Advanced, Automated Processes
- Visualization of Results
- Publicly Available and Free Data Sources
- Basics of Data Mining
- Overview of selected types of data mining tasks and processes
- Data Knowledge Discovery
- 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
Familiarity with basic mathematical analysis.
Familiarity with basic statistics.
35 Hours
Testimonials (3)
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.
Vorraluck Sarechuer - Total Access Communication Public Company Limited (dtac)
Course - Talend Open Studio for ESB
Richard's training style kept it interesting, the real world examples used helped to drive the concepts home.
