Customization and basic concepts of visual programming for data analytics!

KNIME Analytics Platform
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KNIME Analytics Platform

  -  631 MB  -  Open Source
Free Download

Security Status

  • Latest Version

    KNIME 5.5.1 LATEST

  • Review by

    Daniel Leblanc

  • Operating System

    Windows 7 / Windows 8 / Windows 10 / Windows 11

  • User Rating

    Click to vote

  • Author / Product

    KNIME AG. / External Link

  • Filename

    KNIME 5.5.1 Installer (64bit).exe

KNIME Analytics Platform is the open-source software for creating data science. Intuitive, open, and continuously integrating new developments, KNIME for Windows PC makes understanding data and designing data science workflows and reusable components accessible to everyone.

Open and combine simple text formats (CSV, PDF, XLS, JSON, XML, etc), unstructured data types (images, documents, networks, molecules, etc), or time-series data.

Connect to a host of databases and data warehouses to integrate data from Oracle, Microsoft SQL, Apache Hive, and more.

Load Avro, Parquet, or ORC files from HDFS, S3, or Azure. Access and retrieve data from sources such as Twitter, AWS S3, Google Sheets, and Azure.

Derive statistics, including mean, quantiles, and standard deviation, or apply statistical tests to validate a hypothesis. Integrate dimensions reduction, correlation analysis, and more into your workflows. Aggregate, sort, filter, and join data either on your local machine, in-database, or in distributed big data environments.

Clean data through normalization, data type conversion, and missing value handling. Detect out of range values with outlier and anomaly detection algorithms. Extract and select features (or construct new ones) to prepare your dataset for machine learning with genetic algorithms, random search, or backward- and forward feature elimination. Manipulate text, apply formulas on numerical data, and apply rules to filter out or mark samples.

Build machine learning models for classification, regression, dimension reduction, or clustering, using advanced algorithms including deep learning, tree-based methods, and logistic regression. Optimize model performance with hyperparameter optimization, boosting, bagging, stacking, or building complex ensembles. Validate models by applying performance metrics including Accuracy, R2, AUC, and ROC. Perform cross-validation to guarantee model stability.

Explain machine learning models with LIME, Shap/Shapley values. Understand model predictions with the interactive partial dependence/ICE plot. Make predictions using validated models directly, or with industry-leading PMML, including on Apache Spark.

Visualize data with classic (bar chart, scatter plot) as well as advanced charts (parallel coordinates, sunburst, network graph, heat map) and customize them to your needs.

Display summary statistics about columns in a KNIME Analytics Platform table and filter out anything that's irrelevant. Export reports as PDF, PowerPoint, or other formats for presenting results to stakeholders. Store processed data or analytics results in many common file formats or databases.

Build workflow prototypes to explore various analysis approaches. Inspect and save intermediate results to ensure fast feedback and efficient discovery of new, creative solutions.

Scale workflow performance through in-memory streaming and multi-threaded data processing. Exercise the power of in-database processing or distributed computing on Apache Spark to further increase computation performance. Download KNIME Analytics Platform and build your first workflow!

How to Use
  • Launch the application and create a new workflow
  • Drag and drop nodes to build a data workflow
  • Configure node settings and connect them logically
  • Execute the workflow to process data
  • Visualize results using built-in charts and reports
  • Save and export workflows for future use
  • Install extensions for additional functionalities
  • Use KNIME Hub to find and share workflows
  • Integrate with Python, R, and other tools
System Requirements
  • Operating System: Windows 11 or Windows 10 (64-bit)
  • Processor: Intel or AMD, 2 GHz or faster
  • RAM: Minimum 4 GB, recommended 8 GB or more
  • Storage: At least 5 GB free disk space
  • Graphics: OpenGL 2.1 or higher support
  • Java: Bundled with KNIME, no separate installation needed
PROS
  • User-friendly drag-and-drop interface
  • Supports various data sources and formats
  • Extensive library of pre-built nodes
  • Strong integration with Python and R
  • Active community and extensive documentation
CONS
  • Can be resource-intensive for large workflows
  • Limited real-time data processing capabilities
  • Some extensions require additional setup
  • Steeper learning curve for advanced features
  • Occasional performance lags with big data


Download KNIME Analytics Platform Latest Version
Why is this app published on FileHorse? (More info)

  • KNIME 5.5.1 Screenshots

    The images below have been resized. Click on them to view the screenshots in full size.

    KNIME 5.5.1 Screenshot 1
  • KNIME 5.5.1 Screenshot 2
  • KNIME 5.5.1 Screenshot 3
  • KNIME 5.5.1 Screenshot 4

What's new in this version:

Enhancements:
- Clean up environments that Python extensions could have left behind during updates
- Allow Python extensions to have feature_dependencies from other update sites
- Improve resizing of embedded node dialogs
- Update Equo Chromium 128.0.16

Fixed:
- DB Loader fails when connected to Google BigQuery with No FileSystem for scheme "file" (kudos to @JaimeAlzx, @lmmr, @Jason_Kish for reporting 1, 2, 3)
- Deleting an unselected expression does not update dirty and diagnostics state (kudos to @ebarr for reporting 1)
- Granularity unrecoverably invalid after modifying Date&Time Difference (kudos to @EmanuelTavares for reporting 1)
- Effects depending on special choices do not work anymore (kudos to @ersy for reporting 1)
- Geospatial extension doesn’t work in executor images
- DB Column Name Replacer node cancels execution if metadata retrieval takes longer than configure timeout
- Row Filter breaks backwards compatibility when using ordering comparison between long column and double reference value
- IndexOutOfBounds in LLM Prompter on empty table
- Creating component with detached view fails
- Possible executor crash in 5.5.0 in long running instances due to libcef.so+0x6bf7605
- Data apps don’t work for Server 4.18.0 and Executor 5.5.0
- Modern UI does not work on Wayland
- Python nodes show loading animation on empty possible values
- Boxplot execution results in Column index out of bounds error
- String Replacer breaks backwards compatibility when having two backslashes in the Regex replacement string
- Agent Chat View stops working when data-app page is re-executed
- Call Workflow Service may not be able to read error message
- Hitting the token limit of the LLM breaks the Agent Chat View
- FilestoreCells vanish when tool workflows are executed by an agent
- Extract Table Spec node throws error when dragged into workflow
- Messages containing non-UTF-8 encoded text cause Prompter nodes to fail
- Agent Prompter adds empty User message to conversation history if not specified in configuration dialog
- NO_PROXY variable is incorrectly set with wildcards
- LLM Prompter fails in JSON mode with multi-part Messages
- Python string representation of primitive types does not fit column type names
- WorkflowToolCells of non-local workflows with data area are broken
- Agent Chat View: Error when sending messages too quickly after opening the view
- Community Servers, Community Hubs, and EXAMPLES mountpoints are filtered by AP customization, but not removed from mount dialog
- Mountpoint-relative access from within tool executed by Agent Chat View doesn’t work
- Race condition when shutting down draining executor due to load error
- Fabric Workspace Connector has no output view and doesn’t check for connection
- String Replacer changes wildcard \ behavior when reconfiguring a node from 5.4 in 5.5
- BoxPlot does not check for cancelation during execution
- Column Combiner: Using an empty string as the quote character inserts invisible characters and leaves the dialog unusable

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