Low Code/No-Code Data Literacy with KNIME: From Basic to Advanced

Take your data literacy to the next level with tools that make sophisticated data analytics accessible to non-technical people.

1. KNIME Analytics Platform

• What is KNIME Analytics Platform?
• What is a node? What is a workflow?
• How to install KNIME Analytics Platform
• Tour of the user interface of KNIME Analytics Platform
• Build your first workflow with KNIME Analytics Platform
• How to import and export KNIME workflows
• The KNIME Community Hub
• Collaboration and execution on KNIME Community Hub
• How to install KNIME extensions

2. Data Access

• Data access with KNIME: Reading files
• Data access with KNIME: Accessing databases

3. Data Cleaning

• Data cleaning with KNIME: How to filter rows
• Data cleaning with KNIME: How to filter columns
• Data cleaning with KNIME: How to handle missing values

4. Data Transformation

• Data transformation with KNIME: Numbers, strings, and rules
• Data transformation with KNIME: How to split cells

5. Workflow Documentation

• How to keep workflows tidy and documented

6. Data Merging

• Data merging with KNIME: How to concatenate tables
• Data merging with KNIME: Value lookup
• Data merging with KNIME: How to join two tables

7. Data Aggregation

• Data aggregation with KNIME: Simple aggregations
• Data aggregation with KNIME: The GroupBy node
• Data aggregation with KNIME: Pivoting

8. Data Export and Visualization

• Data export with KNIME: Write to a CSV file
• Data visualization with KNIME: How to create a scatter plot
• Three steps to build an interactive dashboard with KNIME

9. Flow Variables

• Flow variables in KNIME Analytics Platform: Concept and application

10. Components

• What is a component in KNIME Analytics Platform?
• Create, modify, and configure a component in KNIME Analytics Platform

11. Workflow Control

• What is a loop?
• Build, execute, and debug a loop in KNIME Analytics Platform
• Switch workflow branch execution in KNIME Analytics Platform

12. Error Handling

• Error handling with try-catch in KNIME Analytics Platform

13. Date and Time Data

• Handling date and time data with KNIME: Convert strings, extract date, and time fields
• Handling date and time data with KNIME: Modify and filter date and time data

14. Databases

• Querying databases from KNIME Analytics Platform
• Modify database tables from KNIME Analytics Platform