Data Mining Software: Open Source vs. Commercial Which is best for your Business

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Created 12.12.2020, read: 132 times

Data mining tools and methodologies have already become quite effective solutions for data analytics in big databases. The rapid development of database technologies led to creation of the specific language queries for databases.

For relational databases it is SQL, which provides numerous opportunities to create, modify or retrieve stored data. Then there raised a necessity in analytical information (such as information on the company activities during a certain period), and it turned out that the traditional relational database, doing well the operational records maintenance, are no good for analysis.

This led, to the creation of the so-called "Data Warehouse" or simply data storage, which match to the comprehensive mathematical analysis best of all. Now we are going briefly review data mining software tools in contemporary market.

Open Source or Commercial?

Actually there are two types of data mining software Free open-source solutions Commercial applications and tools

First of all we review open source solution. Their major advantage is that they are free; their major disadvantage is that the majority of them lack some important functionality, which can be crucial for data mining software tools. Very often these tools have nothing to do with multitasking and can operate in one and only specific area

Open Source Is Free, but Limited Functionality

Carrot² is a free tool, dealing with search results organization into topics. Instantly reviewing what is available, you can easily find the things you've been looking for. This software allows clustering small collections of documents automatically. Carrot² is not limited to 2 specific search clustering algorithms and that is its major advantage. This solution let us fetch different sources’ search results.

GATE is standing for General Architecture for Text Engineering is highly popular solution as in commercial as well educational sphere. The tool is used for any kind of natural language processing, supports Multi-language and information extraction.

jHepWork , which is often named jWork is a widely used tool among engineers ,scientists and students. This data mining solution could be described as an interactive framework, used for data analysis, scientific computation and data visualization.

jWork is cross-platform solution and can be launched on any OS, with the help of Java virtual machine.

It provides a number of outstanding features for data analysis and that determines software popularity.

Orange is another popular data mining software tool, dealing with machine learning. Orange provides visual front-end development for exploration data analysis, stressing on visualization. Generally its scripts use Python bindings and libraries.

Among the important features of this product is highly valued data processing, exploration techniques, filtering and feature scoring, modeling (including model evaluation techniques).

Commercial Is Expensive, but Effective.

Speaking about commercial software first of all we’d like to mention Microsoft Analysis Services, which is a part of Microsoft SQL Server, database management systems.

It includes a number of useful features to the SQL server, which deal with data analytics for business and data storage. Among them we can find integration and analysis services. The latter also includes a number of tools supporting OLAP and intellectual data analysis.

Speaking about data mining, we cannot avoid Oracle software, which is definitely on the top as highly effective to perform various data mining tasks.

Oracle Data Mining is a part of Oracle Corporation's Relational Database Management System for the Enterprise Edition. Their data analysis and data mining algorithms include: anomaly detection, associations, classification, feature extraction, feature selection, prediction, regression and specialized analytics. Software solution perfectly deals with creation of data mining models, their further management and operational deployment inside the database.

Finally we would like to review IBM SPSS Modeler, which is IBM data mining software tool. As well as the previous two it offers effective data analytics and data mining used to create predictive models. It has user friendly visual interface, giving access to statistical and data mining algorithms with no specific programming skills.

Our brief review of data mining software does not cover every aspect of this broad subject. Though, we have tried to provide you with basic information on the most relevant and competitive data mining tools. The final choice is up to you.

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