GETTING STARTED | DATA LITERACY | KNIME ANALYTICS PLATFORM

SOP: Data Analysis with KNIME (Introductory Level)

An essential tutorial to get started

Imene M.
Low Code for Data Science

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Example of a simple KNIME workflow to visualize data.

I recently discovered KNIME, an open-source data analysis tool powered by AI. In the video, I demonstrate how to use nodes to create workflows, from opening Excel files to creating visualizations like bar charts and pie charts.

The tool simplifies data analysis by allowing easy drag-and-drop functionality. No prior data analysis knowledge is needed to get started.

Watch to see how KNIME can streamline your data analysis process!

Video tutorial: Data Analysis Made Easy with KNIME.

Objective

To utilize KNIME, an open-source data analysis tool, to analyze data and create visualizations efficiently.

Key Steps

  1. Opening an Excel File:
  • Drag the “Excel Reader” node onto the workflow sheet.
  • Double click on the node to open a dialogue box.
  • Browse and select the Excel file to open.
  • Click on “Apply” to open the file.

2. Data Analysis and Visualization:

  • After opening the file, add a “Column Filter” node to filter data as needed.
  • Connect the “Column Filter” to other nodes like a “Bar Chart” for visualization.
  • Customize the nodes and settings based on the analysis requirements.

3. Utilizing Additional Features:

  • Explore other nodes like data type modifiers, report creators, etc.
  • Experiment with various data visualization options like value cups, aggregators, splitters, etc.

Cautionary Notes

  • Ensure proper data linking between nodes for accurate analysis.
  • Exclude irrelevant columns using the “Column Filter” for focused analysis.
  • Be cautious when modifying advanced settings to avoid unintended changes in the analysis.

Tips for Efficiency

  • Familiarize yourself with the tool’s interface and functionalities.
  • Practice dragging and dropping nodes to build workflows efficiently.
  • Utilize the AI assistant for guidance and suggestions in constructing workflows.
  • Regularly save your work to avoid losing progress.

By following these steps, you can effectively use KNIME for data analysis and visualization with ease.

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Imene M.
Low Code for Data Science

I help both skilled professionals and beginners start their freelance careers and boost their income 💪