Data mining is a computational process of finding patterns in large data sets with methods like artificial intelligence, machine learning, statistics, analysis, and systems. With a goal to get information from that data that can later be used. The relationship between customers and companies has changed – companies have become easily accessible through social media and messaging platforms which provide valuable but unstructured data. This is why companies need data mining and tools that come with it.
Data mining tools allow businesses to gather information from these platforms and use it for their purposes – namely, marketing evaluation and analysis. It helps businesses find and use important data to improve their business.
The software plays an important role here – it became pivotal in business decision making. They turn unstructured patterns into information that business can turn into success. The task here is to automatically analyze large amounts of data and gather unknown, interesting and relevant information like cluster analysis, dependencies and so on. But in order to do that, a company needs help from a data mining software. Some of them are quite expensive but there are free options on the market.
Here are the top 5 free data mining software businesses can use:
Rapid Miner is an open source predictive analysis system developed by the company of the same name. Deemed one of the best in the market, this software was written in Java language and it provides a great, comprehensive environment for deep learning, machine learning, predictive analysis, and text mining.
It can be used for business, commercial purposes, training, education, research, and machine learning. It has a server for both on-premise and on a cloud with a client-server as its base.
Rapid Miner gives you quick delivery and virtually no errors.
R, sometimes called ‘the superstar of free data mining’, is a free, open source software easy to use for people with little to no previous experience with programming. It can run on a wide variety of platforms including Mac and Windows. There are thousands of templates that you can just download and use to get information out of large datasets using advanced algorithms.
It allows you to:
- Manipulate the data – Developers can separate large datasets in a simple way, making them easy to analyze and use.
- Visualize the data – After the data is separated, it allows you to use graphs to create a visualization with animated or interactive graphs.
- Analyze the data – R has thousands of packages which allow you to perform a statistical analysis.
Weka is a free machine learning software which was developed at the University of Waikato in New Zealand. You would want to use this software for analysing the data and predictive modeling because it contains algorithms and visualization tools that support machine learning. It was written in Java programming language and it has a GUI that provides an easy and simple access to the features.
Weka allows you to do big data mining tasks like mining, processing, visualization, regression and so on based on the assumption that data is in the form of a flat file.
Orange is an open source, component-based software written in Python language that works best for machine learning and data mining – namely, visualization. These components are called widgets and they range from visualization to pre-processing, evaluation and predictive modeling.
Orange allows you to:
- Show a data table and select features
- Read the data
- Compare learning algorithms and train predictors
- Visualize data elements
“Developers often say that Orange is more interactive than other software and that it has a fun vibe which makes the otherwise dull and boring analytics interesting.
Orange quickly formats the data in a pattern that you can move with widgets. You can make smart decisions fast with this tool and users are fascinated by it”, – says Dan Emerson, a data blogger with 1Day2write.
KNIME is an open source integration platform developed by KNIME.com AG and it’s best known for performing data analytics and reporting, mainly used in pharmaceutical research.
The concept of how it operates is that of the modular pipeline and it is made of various machine learning and mining elements intertwined together.
“Other than being a preferred pharmaceutical tool, it’s also commonly used for customer, financial and business data analysis. Some of its stellar features include development and scaling efficiency which is pretty quick and simplicity of use even for new users”, – says a data analyst from Writemyx, Gérard Foxley.
Try data mining with one of these tools
Data mining software doesn’t have to be expensive or complex to do the necessary job and this free, simple, open source software prove it. Use this guide to find the one that works for your business and improve your results with these tools.