KNIME Analytics Platform is a free and open-source application dedicated to data analysis, reports and integration with machine learning and data mining tools. It takes a modular approach toward data pipelining, featuring an intuitive graphical interface for ETL (Extraction, Transformation, Loading) and requires minimal programming experience.
Some users consider it to (partially) be an alternative to SAS. Although it’s primarily used in pharmaceutical research, KNIME is also utilized in business intelligence, CRM customer data, and financial data analysis.
The free and open-source data analytics tool
The interface is really clean when taking into account the range of options provided by the tool. Multiple panels are listed for exploring projects in a tree view, managing the node repository, viewing node descriptions, previewing the project’s outline, and examining errors in the console.
The editing panel is multi-tabbed, so you can keep multiple projects opened at once and navigate them easily. To get a better idea of how KNIME works, you can open example projects for building a simple classifier, data blending, simple reporting, building and deploying a Churn prediction model, and others.
Configure objects settings and execute code
Objects in the designer can be double-clicked to configure settings. For instance, when it comes to the data reading file, you can preview the table of data entries, change the column delimiter, edit flow variables, or set memory policy options. For each executed object, you can view log details in the console window.
- Powerful: A vast arsenal of native nodes, community contributions, and tool integrations makes KNIME Analytics Platform the perfect toolbox for any data scientist.
- Reliable & Trusted: Hardened in the field since 2008 with bi-annual software releases and thousands of dedicated users.
- Scalable: Toggle effortlessly between a single computer, streaming, and big data execution. Integrate new capabilities on top of, alongside, or within your existing infrastructure.
- Room to Grow: Extend existing capabilities with KNIME Server for better collaboration, automation, and deployment functionalities.
Data and Tool Blending
- Big Data Extensions: KNIME Big Data Extensions integrate the power of Apache Hadoop and Apache Spark with the ease-of-use of KNIME Analytics Platform and Server.
- Data Blending: Simple text files, databases, documents, images, networks, and even Hadoop-based data can all be combined within the same visual workflow.
- Tool Blending: Integration of more than a dozen tools, including legacy scripting/code (R & Python), allows expertise to be reused, graphically documented, and shared among data scientists.
- Visual: Easy-to-learn graphical interface means that coding is optional and work is visually documented.
- Meta node Linking: A practical feature for checking in meta nodes. Once checked in and placed in the workflow, KNIME saves that link and automatically updates it in every instance if a meta node is updated or a new version checked in.
- Local Automation: Enables the Call Workflow nodes to be included and parameterized in any workflow, allowing the creation of reusable workflows and adding another layer of flexibility to your toolkit.
- Workflow Difference: Compare changes made to a workflow – whether they are different versions, changes by a co-worker or you simply want to ensure against accidental changes, Workflow Difference makes comparisons easy.
- More information on these features can be found here.
- Unrestricted Open Source: We release our latest, complete code base under the GPLv3 license, with support for major operating systems. The only restriction is your creativity.
- Open Platform: Your innovation is amplified by bringing our massive worldwide community of data scientists to your most difficult analytics problems.
- Portable & Durable: Backwards compatibility ensures that existing workflows continue to function with new versions, future-proofing your work. Industry-leading PMML support allows effortless model portability and deployment.
Over 1500 Modules and Growing
- Connectors for all major file formats and databases
- Native and in-database data blending and transformation
- Support for a wealth of data types; XML, JSON, images, documents, and more
- Advanced predictive and machine learning algorithms
- Integrations with machine learning libraries such as H2O, Keras for Deep Learning, Scikit-Learn
- Comprehensive design of dynamic workflows
- Interactive data views and web-based reporting methods
Intuitive analytics platform with practical features
You can export KNIME workflows to file and open them later to pick up where you left off, similarly, export and import preferences, use a wizard for creating a so-called “metanode” from the template, or change workflow editor settings like grid size or curved connections.
The application has over 1,500 modules when it comes to data access, transformation, analysis, data mining, visualization, and deployment. It supports connectors for major filetypes and databases. Learn how to use this software, so you can get the right way to use.