Published By - Brian Curtis

List of 6 Open Source Data Mining Tools

Open Source Data Mining Tools

Data mining is the extraction of knowledge from various databases and concluding it into useful information.

It all starts with data that is in a raw state when received or captured until it is mined for useful information.

Data mining is very useful for businesses as it can quickly respond to business queries.

It also helps an organization in segmenting its data according to different markets, tastes, and preferences set by the consumer, its geography, and what type of transactions a consumer prefers, etc.

Here are the 6 Best Open Source Data Mining Tools

Weka

It is a free open source data mining tool that uses a machine-learning algorithm for mining the data. This tool can be used for macOS, Linux, and Windows.

This tool is used in various ways for data mining, which includes Experimenter, Weka Knowledge explorer, Simple CL, and Knowledge Flow.

Here, these tools work differently as compared to each other. For two-dimensional visualization purposes, the explorer is used, and where data sets are large, then Simple CL is used.

Also, an organization that uses rapid prototyping prefers Weka over others.

H3O

It is also an open source data mining tool that is used by organizations for analyzing data that is stored in cloud infrastructure.

H3O uses R language for programming purpose but users can also use Python for building models under it.

Also, easy and fast deployment into production is possible because of the support of the Java language.

Also Read: 8 Use Cases of Data Mining by Industry

Orange

Written in python language, Orange is one of the best open-source data mining as well as machine learning tool present in the market.

It is a widget-based software which is best known for its data visualization feature.

It’s easy look and feel attracts many organization towards it. Data, when uploaded into Orange’s system can be formatted into the desired pattern.

This data can be moved easily according to the need by moving the widgets. Orange also allows its users to make smarter decisions with the help of data analysis.

KNIME

This open-source data mining tool is written in java that can help you in creating data science applications and workflows as well.

KNIME can blend your data present in any source, be it on-premise, infrastructure or cloud.

The tool is the main contributor to the pharmaceutical industry. Also, organizations use it for data analytics and business intelligence as well.

KNIME will also let your organization perform data pre-processing viz. extraction, transformation, and loading.

KNIME, with the help of its modular data pipelining concept, integrates many components for machine learning and data mining.

KNIME also consists of various functionalities pre-installed. Also, it is easy to add plugins to it.

ContentMine

ContentMine is a leading data and mining company that provides open-source data mining solutions. It is based in Cambridge, England.

Their tools help an organization in retrieving and analyzing the content which is locked in tables and graphs.

This helps an organization in reducing the time that is used to perform meta-analyses, thus saving the organization’s cost.

Rattle

Rattle is an open source data mining tool based on GUI that uses R programming language for running purposes. R language helps Rattle in providing statistical power with data mining functionality.

Also, Rattle has one of the best user interfaces as compared to its competitors present in the market.

Moreover, Rattle also has a full form, knowingly “R Analytical Tool To Learn Easily.” It can be used on Windows, macOS, and Linux.

Conclusion:

We must tell you that before taking the final decision about buying any particular data mining tool, you should first understand what your requirements are.

Does it help you in increasing your efficiency? Will it bring some value to your business? After you get all these answers, then select the tool you want to use.

Also Read: 5 Best Practices of Data Lineage

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