Knime

KNIME stands for Konstanz Information Miner.

Knime

What Is KNIME?

KNIME stands for Konstanz Information Miner. The KNIME platform is open source and designed for data analysis and reporting. It’s written in Java and built on Eclipse. There are extensions available with additional features.

The platform has machine learning components built in. KNIME integrates with Weka, another open-source project, which adds machine learning algorithms to the system. The R project adds statistical functionalities as well.

KNIME features the concept of a modular data pipeline, which allows for data mining within a straightforward user interface. Data preprocessing, modelling, analysis, and visualization are all enabled within KNIME.

The workflows can run both through the interactive interface and also in batch mode. These two setups allow for easy local job management and regular process execution.

One of the primary benefits of KNIME is the ability to create visual data flows. Users can then selectively execute the steps of analysis and review the output with the interactive view. The core version of KNIME has hundreds of modules already incorporated. This means KNIME supports the common database management systems right out of the box.

All common methods for data analysis and visualization are already found in KNIME’s core version. This includes the ability to filter, convert, and combine data sets. However, certain extensions are extremely popular thanks to their added practical functionalities.

For instance, the Report Designer is a free extension that most KNIME users will install. With this extension, a workflow in KNIME can become a dataset, enabling the user to create a report template. This can then get exported into multiple formats.

Other extensions allow for text mining, image mining, time series analysis, and so on.

Benefits and Features

Some of the Collaborative Extensions of KNIME include TeamSpace, Server Lite, WebPortal, and the KNIME Server. The KNIME Analytics Platform in and of itself has over 1,000 routines for data analysis. Together, these allow for:

Univariate Statistics
Multivariate Statistics
Data Mining
Time Series
Image Processing
Web Analytics
Text Mining
Network Analysis
Social Media Analysis

Scalability is one of the key features that KNIME promises. With its countless extensions, there are many ways to customize and grow the system to fit a company’s specific needs.

The intuitive user interface also helps speed up the learning curve. In fact, considering the many possibilities of the KNIME system, the interface makes everything quite easy to use. Being able to import and export workflows also gives way for collaboration between multiple KNIME users.

For an environment that runs a multi-core system, features like parallel execution will prove extremely valuable. Add to this the capability of “headless” batch executions using the command line version and it’s easy to see why many prefer KNIME.