What is Data Mining Tool?
In today’s world, a large amount of data is generated within seconds. To handle this data, we should have some knowledge of different techniques and tools. Data mining tools are nothing but a set of methodologies used to analyse this large amount of data and other data relationships.
List of Data Mining Tool
Here is the list of few notable data mining tools which are helpful for us to analyze data:
1. Rapid Miner
It is developed by Rapid Miner company; hence the name of this tool is a rapid miner. It is written using java language. The fast miner can be used for predictive analysis, business application, education and research, commercial applications, etc. It increases the speed of delivery as it follows the template framework. It not only increases the delivery speed but also reduces errors while transforming. There are three types of rapid miner – Rapid Miner Studio, Rapid Miner Server, and Rapid Miner Radoop.
- Rapid Miner Studio: Workflow design, prototyping, validation, etc., are done in this module.
- Rapid Miner Server: This module is used for operating predictive data models.
- Rapid Miner Radoop: For simplification of predictive analysis, this module executes a process in Hadoop.
2. Orange
It is open-source software written in python language. Orange is the best software for analyzing data and machine learning. These components are called widgets. These widgets are used for reading data, analyzing components, allowing users to select the features, and showing the data. With orange, data formatting and moving them with the help of widgets becomes fast and easy.
3. Weka
The University of Waikato develops weka. It is an open-source software used for predictive modelling and analysis of data. Weka has a GUI interface that provides easy and interactive access to users. It supports SQL and allows a user to connects to the database, and performs operations by firing query. It stores data in a flat-file format.
4. KNIME
It is an open-source developed by KNIME.com AG used for data analytics. It is built by combining data mining and machine learning components. It has been used for pharmaceutical research, business intelligence, and financial analysis.
5. Sisense
It is not open-source software; it is licensed software, and we have to purchase the license to use this. Small and large organizations use Sisense to handle the data. As it also supports widgets like orange, it is easy to move data and creates reports by dragging and dropping. Not even technical people can work with Sisense as its GUI based. With the help of widgets, Sisense generated words are in the form of bar chart, pie chart, line chart, etc.
4.7 (3,220 ratings)
View Course
6. Apache Mahout
The Apache foundation develops it. Apache Mahout aims to create algorithms for machine learning and focus on regression, clustering classification of data. As it is written in a well-known language like java and contains java libraries that support mathematics operation, it is used for statistical analysis.
7. SSDT
SSDT is short for SQL Server Data Tools. It is used to expand the database development phases in a visual studio. It is widely used for data analysis and provides solutions to solve business intelligence problems. SSDT provides a table designer to perform table operations like create a table, adding table data, deleting table data, modifying table content. It allows a user to connect to the database as it supports SQL.
8. Rattle
The Rattle is an open-source developed using the R language. It provides a GUI interface. The inbuilt log close tab enables Rattle to generate duplicate for every activity.
9. DataMelt
It is also known as DMelt. It is used to analyze and visualize data. It is designed for students, engineers, and scientists. It is platform-independent, which means it can run on any operating system which contains JVM( Java Virtual Machine). It is used to create 2D or 3D plots, random numbers, mathematical operations, algebra equations.
10. IBM Cognos
It is suited for Business Insider intelligence. It is used for analyzing data, data reporting.
Components of IBM Cognos
- Report Studio: It is used to generate reports.
- Query Studio: Contains query operation to get desired results.
- Analysis Studio: It is used to handle a large amount of data and analyzing the relation between data
- Event Studio: It is used to give the event notifications.
- Cognos Connection: It is a web portal to summarize the large volumes of data and give the reports.
11. SAS
It is developed for managing a large amount of data. It allows a user to modify the data, store data from different locations into one space. As it provides a GUI interface, a non-technical person can also use this quickly and handles their data efficiently.
12. Teradata
It contains data warehouse tools as well as data mining software. It is widely used for business analytics. Teradata is used to give information about data like the available product, number of products sold, inventory, etc.
13. Dundas
It is a dashboard, analytics, reporting tool. With Dundas, unlimited data transformation is possible. It provides features to create attractive data like charts, tables styles, graph, text formatting, etc.
Conclusion
In this article, we have seen what data mining is and which tools are used to complete data mining.
Recommended Articles
This has been a guide to Data Mining Tool. Here we discussed the concepts and list of Data Mining Tool. You can also go through our other suggested articles to learn more –
