KNIME (pronounced /naɪm/), the Konstanz Information Miner, is an open source data analytics, reporting and integration platform. KNIME integrates various components for machine learning and data mining through its modular data pipelining concept. A graphical user interface allows assembly of nodes for data preprocessing (ETL: Extraction, Transformation, Loading), for modeling and data analysis and visualization.
Since 2006, KNIME has been used in pharmaceutical research, CRM customer data analysis, business intelligence and financial data analysis, plus many other areas requiring Data Integration and Analysis.
KNIME allows users to visually create data workflows (or pipelines), selectively execute some or all analysis steps, and later inspect the results, models, and interactive views. KNIME is written in Java and based on Eclipse and makes use of its extension mechanism to add plugins providing additional functionality. The core version already includes ~1,500 modules for data integration (file I/O, database nodes supporting all common database management systems), data transformation (filter, converter, combiner) as well as the commonly used methods for data analysis and visualization. With the free Report Designer extension, KNIME workflows can be used as data sets to create report templates that can be exported to document formats like doc, ppt, xls, pdf and others. Other capabilities of KNIME are:
- KNIMEs core-architecture allows processing of large data volumes that are only limited by the available hard disk space (most other open source data analysis tools are working in main memory and are therefore limited to the available RAM). E.g. KNIME allows analysis of hundreds of millions of customer addresses, cell images and molecular structures.
- Additional plugins allows the integration of methods for Text mining, Image mining, as well as time series analysis.
- KNIME integrates various other open-source projects, e.g. machine learning algorithms from Weka, the statistics package R project, as well as LIBSVM, JFreeChart, ImageJ, and the Chemistry Development Kit.
- New fuctionality is continuusly being added, and being Open Source you can easily add your own special code to the system.
KNIME is implemented in Java but also allows for wrappers calling other code in addition to providing nodes that allow to run Java, Python, Perl and other code fragments.
WISR has built a wide range of new Knime Nodes to expand the functionality of the Knime system.
The WISR Knime nodes include functions to:
- send, receive and store data on Amazon Web Services (AWS) S3 (storage) and SQS (Simple Queue System).
- integrate with email services.
- integrate with popular CRM system (e.g.: Vtiger).
- See a list of WISR Knime Nodes here.
WISR can also create Custo Knime Nodes to match your specific requirements.
See Example Knime Applications
The following applications show some possible usage scenarios for KNIME.
The business examples include Telco churn and retention, social media music recommendation, social media text and network analysis, automated model selection for credit scoring and advanced chemical library enumeration workflows and are documented and available for download via the public server.