TrustRadius: an HG Insights company

KNIME Analytics Platform

Score7.8 out of 10

66 Reviews and Ratings

Get a Demo

What is KNIME Analytics Platform?

KNIME empowers data users to build, collaborate, and upskill on data science. KNIME offers support across the data science life cycle, from creating analytical models to deploying them and sharing insights across the enterprise.

Users of KNIME tend to wear one of four hats:

Data experts can accelerate time to insight, collaborate with other disciplines, and empower upskilling across business functions. KNIME lets them:
* Connect to any data, access any analytic technique, and the choice to code in any language
* Get to insights faster using a low-code/no-code interface
* Eliminate repetitive, manual work by creating reusable, automated workflows
* Save and share Python scripts, analytical models, or data processes for reuse
* Provide blueprints that non-experts can learn and upskill from independently
* Speed up learning by accessing workflow samples by KNIME community members and experts
* Validate models with performance metrics and carry out cross validation to guarantee model stability
* Automatically document each step of the analysis visually * Maintain models and fix mistakes more easily with version control, debugging, tracking, and auditing

Business & domain experts can access and blend data, perform advanced analyses, and deliver timely insights in a visual, interactive environment that eliminates the need to code. They can prep data faster and do deeper analyses because KNIME lets them:
* Connect to all data sources and access any file format in one visual environment.
* Transform data self-sufficiently in the same visual environment without IT dependency
* Use visual workflows from others as blueprints to get started faster
* Automate repetitive data tasks like data prep and reporting with reusable workflows
* Minimize the time to spot and fix errors with each step of the analysis clearly visible, and track changes with version control
* Access thousands of self-explanatory nodes to perform the actions needed on data
* Create workflows of any complexity by joining nodes together via drag and drop

End users can get insights with custom-built, interactive data apps without needing to know how to code or build analytical models. They can make faster, data-driven decisions with advanced analytics at their disposal because KNIME lets them:
* Interact with analyses of any complexity level with a data app UI
* Access data apps via the browser with a secure connection or shareable link
* Identify patterns with job-relevant data apps and provide feedback to improve the model
* Lower the barrier between them and data science teams, enhancing analytics output accuracy
* Choose to get insights from simple dashboards or complex, interactive visualizations
* Explore data and perform ad hoc analyses using interaction points within data apps
* Avoid vendor lock-in and adapt to changing business needs with an extensible platform

MLOps and IT teams use KNIME to securely deploy, manage, and scale with a single installation while ensuring enterprise-grade security and governance. The platform enables them to:
* Safely deploy and monitor models from one single place
* Ensure adherence to best practices
* Meet enterprise needs while ensuring data security and governance
* Securely productionization data science at scale

Categories & Use Cases

Videos

Screenshots

Screenshot of the KNIME Modern UI. This is the the new user interface for the KNIME Analytics Platform that is available with improved look and feel as the default interface, from KNIME Analytics Platform version 5.1.0 release.
Screenshot of the KNIME Analytics Platform user interface - the KNIME Workbench - displays the current, open workflow(s). Here is the general user interface layout — application tabs, side panel, workflow editor and node monitor.
Screenshot of the KNIME user interface elements — workflow toolbar, node action bar, rename components and metanodes.
Screenshot of the entry page, which is displayed by clicking the Home tab. From here users can; check out example workflows to get started, access a local workspace, or even start a new workflow by clicking the yellow plus button.
Screenshot of the status of a KNIME node, which shows whether it's configured, not configured, executed, or has an error.
Screenshot of the KNIME node action bar, which can be used to configure, execute, cancel, reset, and - when available - open the view.
Screenshot of the common node port types. Nodes can have multiple input ports and multiple output ports. A collection of interconnected nodes, using the input ports on the left and output ports on the right, constitutes a workflow
Screenshot of the three ways nodes can be added to the workflow canvas; drag & drop, double click on the node in the node repository, or drop a connection into an empty area to display the quick nodes adding panel.
Screenshot of how to set a workflow coach preferences.
Screenshot of replacing a node into the workflow editor via drag & drop.
Screenshot of the annotation field of a node, which is helpful for explainability and documenting of a workflow.
Screenshot of the annotation function, which is helpful for explainability and documenting of a workflow.
Screenshot of the space explorer, which is where users can manage workflows, folders, components, and files in a space, either local or remote on a KNIME Hub instance.
Screenshot of the node repository, which is where currently installed nodes are available. Here, users can search for and then add a node from the repository into the workflow editor by drag & drop.
Screenshot of the node monitor. This is located on the bottom part of the workbench and is especially useful to inspect intermediate output tables in the workflow.
Screenshot of the KNIME Business Hub teams view. Resources can be owned by a team (e.g. spaces & the contained workflows, files, or components) so that team members can access these resources.
Screenshot of the KNIME Collections view. Upskill users by providing selected workflows, nodes, and links about a specific, common topic.
Screenshot of the KNIME Business Hub versioning. Track changes to workflows easily and in a transparent way.
Screenshot of the KNIME Business Hub deployment options. After a workflow is uploaded to KNIME Hub different type of deployments can be created. For example: a Data App, schedule, API service, or trigger.
Screenshot of the KNIME Business Hub Data Apps Portal. This page is available to every registered user. Consumers, for example, can access to this page to see all the data apps that have been shared with them, execute them at any time, interact with the workflow via a user interface, without the need to build a workflow or even know what happens under the hood.

1 / 20

Screenshot of the KNIME Modern UI. This is the the new user interface for the KNIME Analytics Platform that is available with improved look and feel as the default interface, from KNIME Analytics Platform version 5.1.0 release.

Product Demos

Technical Details

Technical Details
Deployment TypesOn-Premise, SaaS
Operating SystemsWindows, Linux, Mac
Mobile ApplicationNo
Supported CountriesGlobal
Supported LanguagesEnglish

Downloads

FAQs

What is KNIME Analytics Platform?
KNIME enables users to analyze, upskill, and scale data science without any coding. The platform that lets users blend, transform, model and visualize data, deploy and monitor analytical models, and share insights organization-wide with data apps and services.
How much does KNIME Analytics Platform cost?
KNIME Analytics Platform starts at $0.
What are KNIME Analytics Platform's top competitors?
Alteryx Platform, Qlik Sense, and Dataiku are common alternatives for KNIME Analytics Platform.
What is KNIME Analytics Platform's best feature?
Reviewers rate Extend Existing Data Sources highest, with a score of 10.