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Your top questions on KNIME 5.1, answered

August 30, 2023
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KNIME continuously invests in increasing analytic depth as well as ease of use and onboarding to ensure that anyone can use the platform to make sense of data, irrespective of their background or level of experience. Active participation and inputs from the community have been key to making these improvements and reducing the data science learning curve for users.

After months of gathering feedback from the community, we released KNIME Analytics Platform 5.1 with the new UX, improved product onboarding, and a more intuitive way to build analytical workflows last month. In a recent webinar, KNIME’s product team took users through a tour of the top new features and enhancements in the latest version. As the team opened up a Q&A session, they received over 70 questions from the audience.

Because many people might have the same questions, we have provided answers to some of the most frequently asked questions in this article. If you’d like to watch the entire webinar, you can access it here whenever you want.

  1. What’s different in the new UI in KNIME 5.1?

    The new interface in KNIME 5.1 features a sleeker look and feel, a more intuitive workflow editor, improved navigation and search to let users identify which nodes they need more quickly. A new quick node feature also offers next-node recommendations to build workflows faster, based on the nodes users have selected thus far in their workflows. The 5.1 release also offers improved workflow annotations. Users can add more detailed notes to their workflows, making it easier to understand the analysis when shared with colleagues for reuse.

  2. What is K-AI?

    K-AI is the new AI assistant and one of our most exciting additions in KNIME that helps onboard new users by providing them guidance. It can be used in two modes. In the first “Q&A” mode, the assistant answers user questions and provides instructions on workflow building. In the second “Build” mode, it builds workflows from scratch, adding and connecting nodes according to the user’s instructions.

    Please note that the AI assistant is not part of the vanilla KNIME installation and has to be installed from the Labs category.

  3. What is the new AI extension?

    It enables users to build their own AI assistant or augment their workflows with AI. It provides nodes for building LLM-powered applications such as chat bots via KNIME workflows. The extension supports both state-of-the-art OpenAI models and open source Large Language Models (LLMs) from the Hugging Face Hub.

  4. Can we embed an AI chatbot to a webpage or website?

    Yes, you can build a data app using the AI extension for your webpage.

  5. Due to data protection laws within my organization, I must work offline, i.e, I can't sign in. Is there any alternative to profit from the AI assistant?

    Unfortunately, it’s not possible to use K-AI in an offline setting. In theory, you could build your own assistant that you run locally using the KNIME AI Extension. But so far the models that can be run locally don’t match up with OpenAI's ChatGPT.

  6. Will workflows using 4.7.5, for example, need to be rebuilt to be compatible with 5.1?

    No, they don’t need to be rebuilt. You can open and use them in KNIME 5.1.

  7. In the new version, do we need to manually reinstall all the extensions that we used in the previous version?

    Yes, you’d need to reinstall extensions in the new version. However, you can do so using the migration scripts release notes.

  8. Will KNIME Hub be available in the modern UI as it was in the classic version?

    Yes, the KNME Explorer in the modern UI now offers a more intuitive way to browse and access workflows from KNIME Hub.

  9. Which new nodes have been introduced for spreadsheet users?

    The following new nodes have been added to make it easy for spreadsheet users to automate repetitive work, combine spreadsheets with workflows, and even transition entirely to workflows.

    • Value Lookup: Adds matching values from a dictionary table to a data table based on a lookup column. When a lookup value matches an entry in the dictionary, the selected cells are added to the data table. Otherwise, missing cells will be inserted.

    • Row Aggregator: Aggregates numerical columns based on one of the following aggregation functions: Occurrence count, sum, average, minimum, or maximum. Some aggregation functions support weighting. Rows can optionally be grouped by a category column.

    • Table Splitter: Splits the input table at the row that matches a given condition. The part of the table that occurred before the matching row is forwarded to the top output table, the bottom output table contains the rest of the input table

    • Table Cropper: Crops the input table based on the chosen row and column range. The row range is defined via row number, the column range either via column name or column number.

    • Cell Extractor: Extracts the value of a single cell from the input table and outputs it as a 1x1 table. The row selection is defined via row number, the column selection either via column name or column number.

    • Table Updater: Updates cells in the top input table with matching cells from the bottom update table. A matching cell must have the same column name and RowID in both tables. Multiple cells of multiple rows and columns can be updated. Additional rows and columns from the update table can be appended to the input table.

    • Cell Updater: Updates a single cell of the input table with the value of the specified flow variable. The cell to be updated must be specified via the row number and column name. The output table will be identical to the input table except for the single updated cell.

      Read this cheat sheet to quickly understand how to use these nodes to automate data processing.

  10. What are the next steps for reporting in KNIME?

    KNIME 5.1 introduces a new KNIME Reporting (Labs) extension that allows you to export your visualizations as static PDF or HTML reports quickly and easily.

    You can further format data in table visualizations using the Number Format Manager or highlight data using conditional formatting via new functions in the Column Expression node. You can also choose to concatenate different reports, for instance by using the loop functionality, and export your visualizations as PDF or HTML reports using the new Report PDF Writer and Report HTML Writer nodes.

    Learn more about building a static PDF reporting using the new extension in this article.

Take a look for yourself

Try out the latest version of KNIME Analytics platform here. Additionally, you can find step-by-step instructions on getting set up and building your first workflow in the modern interface in the Getting Started Guide.


by Dipti Panchwadkar
Dipti is a product marketer at KNIME and is based in Berlin. With a background in computer engineering, she loves working at the intersection of technology and communication. Her focus is on translating complex technologies into accessible, compelling stories that resonate with users.
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