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 5.5.0 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 5.5.0 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 5.5.0 Screenshots

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

    KNIME 5.5.0 Screenshot 1
  • KNIME 5.5.0 Screenshot 2
  • KNIME 5.5.0 Screenshot 3
  • KNIME 5.5.0 Screenshot 4

What's new in this version:

New nodes:
- Microsoft Fabric Data Warehouse Connector
- Google Workload Identify Federation node
- Message Part Extractor
- Message Creator
- Agent Chat View
- Workflow to Tool node
- Agent Prompter Rewrite
- Microsoft Fabric Workspace Connector
- Vertex AI Connector node
- Google AI Studio Authenticator node
- Gemini Embedding Model Connector node
- Gemini Chat Model Connector node
- IBM watsonx Embedding Model Connector node
- IBM watsonx Chat Model Connector node
- IBM watsonx Authenticator node
- Anthropic Chat Model Connector node
- Anthropic Authenticator node
- Microsoft OneLake Connector
- Power BI Model Reader
- Power BI Model Refresher
- BD-1350: (Big Data Extensions): Delta Table Reader (Labs)
- Date&Time Rounder
- Duration Format Manager

Enhanced:
- Call Workflow Nodes: Set parent job identifier when creating callee job
- Row Filter to allow equality check between compatible numeric types
- Row Filter to support "is not equal " variant that retains missing cells
- Expressions: Keep selected text as argument when inserting functions
- Expression node should auto-complete boolean operators "and ", "or ", and "not "
- Allow removal of arbitrary port from extensible port groups
- Web UI for Column Name Replacer (aka Column Rename (Regex))
- Web UI for UNIX Timestamp to Date&time
- Trim native (outside JVM) memory usage from the Watchdog periodically and on low resources
- Make boolean operators case insensitive in expressions to allow "AND ", "OR ", and "NOT "
- Node name improvements and other minor enhancements in AI Extension
- Tableau Writer to be streamable (performance enhancements)
- Allow multi-modal message column as input for LLM Prompter
- Allow python node view to be completely defined by static resources
- Support multi resources OAuth authorization in Microsoft Authenticator
- Add description-field to Workflow Service Input/Output nodes
- Introduce multi-modal Message data type
- Introduce Workflow Tool data type
- Allow underscores in number strings going into parse_int and parse_float
- More robust "state notification " when workflow/node state changes (e.g. notifications may break state in executor)
- Improve "KNIME > Customization Profiles " preferences page
- Ability to "soft lock " mount point preferences using AP customization
- (Internals) Invisible ThreadPool threads to not stay invisible for the remainder of their lifetime
- Constant Value Column node: Improve Performance with Columnar Backend
- Add date and time expression types and functions to K-AI’s prompt
- LLM Prompter: Support JSON prompt columns
- Secrets Retriever node should show a proper exception if an extension is missing for a selected secret e.g. Databricks
- "BufferedDataTable Reference Reader "-Nodes not copy-paste-able between Workflows
- Run REST Request nodes' I/O without consuming KNIME thread pool slot (i.e. "invisibly ")
- (Internal Metrics:) Track KNIME Executor’s internal thread pool queue length
- K-AI Build Mode: Display K-AI’s explanation of its actions
- Breakpoint node: Option to fail on non-empty table
- Expose health metrics via standard Java monitoring API
- Extend Expression nodes to handle Date&Times
- Improve Python extension installation robustness, speed and size by using pixi
- Cancel node execution if watchdog detects memory pressure
- Report watchdog metrics to prometheus
- Make KNIME Explorer synchronization less resource intensive on remote end
- "KNIME Audio Processing " marked legacy (due to low usage) - still available via update site but uncategorized
- Support Markdown in Quick Build Mode
- K-AI Quick Build Mode: Support building from scratch, or from multiple nodes
- K-AI Build Mode: Provide port type information to K-AI
- AP to be more error robust (=better error message) when system runs out of temporary disk space, default 100MB space left
- Secrets Retriever node should fetch secrets in parallel
- REST Client Nodes: Split default timeout to 5s connect and 120s read defaults
- Data types to have user-friendly names (e.g. "Set " ? "Collection (Set) " or "Period " ? "Duration (Date-based) ")
- Google Ads Query node automatically converts column names and values to human-readable formats.
- Legacy H2O model versions (3.36-) separated into separate hidden extension (no longer installed by default)
- Add most nodes with modern dialog to K-AI build mode
- Decision Tree Learner: Fix links in description
- Ability to load preference profiles from multiple providers in AP
- Become verified publisher of KNIME Analytics Platform Azure App
- BD-1346: (Big Data Extensions): KNIME H2O Sparkling Water Integration uncategorized (to be removed); after marking legacy in 5.3
- BD-1342: (Big Data Extensions): Update Databricks JDBC driver to version 2.7.3
- Update Equo Chromium 128.0.13
- Introduce Reset-Before-Upload Handling for Hub/Server Workflows
- "Reveal in space explorer " to unfold sidepanel
- Enable embedded dialogs by default
- "Info " panel for metanodes is empty
- Enable Copy/Move for items in local space
-Align nodes
- Web UI for Integer Configuration
- Web UI for Double Configuration
- Web UI for String Configuration
- Don’t allow renaming the same column twice in the Column Renamer
- Web UI for Boolean Configuration
- Enable Embedded Component Dialogs
- Web UI for Row Sampler (aka Row Sampling)
- Web UI for Nominal Value Row Splitter
- Web UI for Reference Row Splitter
- Web UI for Reference Column Splitter
- Web UI for Column Splitter
- Web UI for Variable Creator
- WebUI for DB Query Extractor
- WebUI for DB Query Injector
- WebUI for DB Column Filter
- WebUI for DB Column Name Replacer (aka Column Rename (Regex))
- Web UI for Table Column to Variable
- Web UI for String to Duration
- Web UI for Duration to String
- Web UI for Duration Part Extractor (aka Extract Duration Fields)
- Web UI for Duration to Number
- Support binary/integer columns as category
- Web UI for Date&Time Difference
- Web UI for Constant Value Column
- Web UI for Table Partitioner (aka Partitioning)

Fixed:
- Python node dialog moves and resets file stores of incoming row-based table
- K-AI code suggestions in multi-expression context doesn’t know about columns added before the current expression
- Manual Aggregation via GroupBy on a Network column produces error
- Chemistry type value factories do not adhere to KNIME type system contract
- 'Temperature' parameter in HF Hub LLM Selector node does not affect responses
- GraphCell is not registered at extension point
- Parallel Coordinates Plot: Selection not working in component with other views
- ColumnFilter overwritten by flow variable behavior changed
- Port view factory and port spec view factory are flipped for CredentialPortObject
- Excel Reader throws IllegalStateException when reading XLSB and parsing is canceled quickly (e.g. in loop)
- LLM Chat Prompter requires an empty table to be provided when starting a new conversation
- KnimeExtensionArray.to_pylist called with unexpected argument with pyarrow 20
- String flow variables with the value null cause Expressions to fail with NullPointerException
- GPT4All Connectors unnecessarily contact the gpt4all website
- DB Pivot can make AP unresponsive and takes a long time to react on an attempt to cancel execution
- Attempts to log to closed appenders (again)
- Metanode name in Description view data is not encoded (Classic UI)
- Terminal stays open when starting AP on Windows via knime-hidpi.bat
- Expression If function returns wrong values for large INTEGER values
- "Build with K-AI " button in Quick Node Add dialog should be bottom-anchored
- Parts of K-AI’s messages are formatted differently
- Python extensions cannot be uninstalled on Windows if there’s a space in the path
- Framework sets NO_PROXY environment variable incorrectly
- Expression diagnostics do not update reliably when inserting columns or from function catalog via double click
- Expression editor steals focus if the node is selected in the embedded mode
- Concatenate: The reported number of skipped rows is not accurate, off by one
- Python Extension Framework hides relevant stack trace if extension import fails
- Very long scripting AI prompt makes AI popup unusable
- Very large expressions can cause a StackOverflowError
- Cannot use modules or packages named "ports " in Python extensions because the name clashes with ports.py in our Databricks extension
- Expression editor not accessible
- String representation of unknown python types show internal types
- Deleting a not-selected expression changes the selection to the previous expression to the deleted expression
- Remove Top-Level Domain Check in Web Interaction Navigator Node
- Invalid regexes show ugly error message, error obstructed in large embedded mode
- When appending the same table twice using VirtualTable, the second copy gets stuck on the last row
- Only render node or component view tab outputs for nodes which have a view
- Table View: Opening view in disabled branch raises com.fasterxml.jackson.databind.JsonMappingException
- Casing of space items cannot be changed by "rename " in Space Explorer on macOS
- Retain correct port description on port removal for components
- Importing KNWF or KNAR file into local space keeps temp files until AP is shut down
- Component loading can’t be cancelled
- Cannot Drag and Drop Workflow from Non-Authenticated Hub
- Opening Temp Copies of Remote Workflows Not Cancelable
- Ctrl + Enter in node not always triggers node execution
- Inline error messages are not reset when new errors occur
- Unsetting flow variable not applyable in some cases
- Missing (null) valued control flow variable causes a non-user-friendly error message in BarChart
- File chooser component cannot handle non existent drive on windows
- Unsetting deprecated flow variables does not make dialog dirty
- Table View: Illegal Group Reference when used with String Formatter

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