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9 Best Data Mining and Data Collection tools 03 June, 2019   

Data collection is a crucial aspect in today’s world. A lot of data collected will be unstructured and requires processing to extract useful information into a practical form. A plethora of data mining tools are available which employ machine learning and artificial intelligence to extract data.

Data mining involves the process of mining and analyzing the data to extract usable information from it. This can provide quick solutions to your business needs which may otherwise have consumed a lot of time. Applications of data mining include market segmentation, fraud detection, trend analysis of the market, and a lot more.  

Data mining is accomplished in numerous steps –

Pre-processing: This is the first step in data mining, which refers to all the preliminary tasks that help in starting with the actual mining task. This step involves the removal of noise and anomalies from the data which needs to be mined. It also consists of filling values that are missing as well as normalizing the data with the use of aggregation and generalization techniques. During clustering, a huge set of data is partitioned into sub-classes. 

Classification: This involves the actual classification of data into defined categories. A lot of analysis techniques are employed for the identification of data elements and the relationship between data items within a set. 

Summarization: This offers a compact description of the entire data set. 

Data mining is considered to be a combination of several techniques such as machine learning, statistics and pattern recognition. Data mining is a cumbersome task and requires the use of high precision tools for the purpose.  

Here are the 9 best data collection and mining tools available:

1. Weka 

Weka is an open source data mining software which is based on Java. It can run on Windows, Mac OS X and on Linux platforms and consists of a collection of machine learning algorithms. The tools that come in a package with this software can be used for pre-processing, regression, classification, clustering and visualization. The original version of this data mining tool was not based on Java and was primarily used for the analysis of data collected from the agricultural domain. The Java version is pretty much sophisticated and finds numerous applications such as predictive modeling, algorithms, and visualization for data analysis. This is one of the popular Data collection tools that can be accessed for free and the users even have the power to customize it as per their requirement.

2. Rapid Miner

This is one of the most popular data mining tools available in the market. This tool is available in both commercial and FOSS editions. This tool was announced to be the leader when it comes to using magic quadrant for analysis and advanced mining during the year 2016 by the US Research and Advisory Firm, Gartner. Predictive analysis can be very beneficial in business processes utilizing Rapid Miner with its machine learning algorithms and library of data science. It also comprises a visualization environment and built-in templates. This tool finds applications in the field of education, research, commercial or business applications. 

3. Orange

If you are a python developer and is looking for a user-friendly data mining tool, then Orange is the most appropriate one. This open source tool is quite powerful and is ideal for both experts and beginners. Experts employ the Python scripting and the visual programming features offered by this tool. This tool also presents components for text mining and machine learning. It is known to provide features about data analytics as well. The Python Library is loaded with scripts for modeling, preprocessing, clustering, regression and for other functions. The interface offered by this data mining tool is quite user-friendly, and a lot of assistance is offered to users in the form of online tutorials. 


KNIME is an ideal tool for data preprocessing which comprises three main components such as loading, transformation, and extraction. This tool provides a graphical user interface for assembling the nodes for processing the data. This is one of the most trusted data reporting, analytics and integration platforms among all the data mining tools available currently. KNIME also integrates numerous components for data mining and learning and is utilized for financial and business intelligence data analysis. KNIME allows plugins and is very easy to extend. The core version comprises data integration modules which can prove to be immensely useful. The flexibility of the platform as well as the openness of this tool scores over R and Weka. KNIME has an active community and user base. 

5. DataMelt

This is one of the data mining tools which can accomplish much more than data mining. It is a visualization and computation environment which provides an interactive framework to the users for carrying out analysis of data sets. It has been designed specifically for students, scientists, and engineers. This mining tool has been developed on JAVA and can be run on any OS. It features mathematical and scientific libraries for assisting the users. The scientific libraries permit users to draw 3D/2D plots. The mathematical libraries help with the generation of random numbers and curve fitting.

6. Oracle Data Mining

This tool is a component of the Oracle Advance Analytics which can provide excellent algorithms for data classification, regression, prediction, and specialized analytics. This is one of those Data collection tools which permit the analysts to target best customers and make better predictions. It as well helps in the detection of fraud as well as in the identification of cross-selling opportunities. The GUI of this miner is an extended version of the SQL developer offered by Oracle.

7. Dundas BI

This is another reliable tool for data analytics and reporting. The key features of this tool are its ability to provide quick insights and rapid integrations. It offers unlimited data transformation patterns with graphs and attractive tables. This mining tool also permits data accessibility from various devices. This tool helps in placing data in the form of well-defined structures, thereby permitting easy processing of the data. The relational methods focus on business-critical matters as well as permit multi-dimensional analysis. The reports generated by this tool are reliable and eliminate the need for any additional software. 


This is again an open source software which has been written using Javascript. The prime focus of this tool is cluster analysis as well as outlier detection. This tool can be accessed through a graphical user interface which can display the results upon running the chosen algorithm. The main aim of this mining tool is extensibility, scalability, and performance. No professional support is currently offered to the users of this tool. However, the software is optimized regularly for assisting those in scientific research.


KEEL stands for Knowledge Extraction for Evolutionary Learning. This is an open source tool based on Java and is powered by an organized GUI. This permits the users to manage the data which are in different file formats. Data mining experiments can be carried out by installing JVM on the system. Various supported algorithms can be accessed by visiting the official website. This tool is ideal for educational and research purposes.

Although there are numerous data collection and mining tools are available, you need to look into the individual requirements of your business and then take a call to find out which one is the best for you. Research on the applications and the limitations of each tool and figure out which one would be the most suitable for you.

Data Mining Data Analysis Data Collection Data Mining tools Oracle

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