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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 (3)
What was very practical.
Alfonso Ramos - Banco de Mexico
Course - Fundamentos de Integración de Datos Pentaho
Machine Translated
It's a hands-on session.
Vorraluck Sarechuer - Total Access Communication Public Company Limited (dtac)
Course - Talend Open Studio for ESB
The tool's capacity
Gerardo Avila - Reckitt Benckizer
Course - KNIME Analytics Platform for BI
Machine Translated
