Data mining is the process of predicting outcomes by looking for trends, patterns, and correlations in huge data sets, and then classifying them into valuable data, which is collected and organized in unique areas such as data warehouses, efficient analysis, data mining algorithms, decision support, and other data requirements, resulting in cost savings and revenue generation.
Data mining even has applications in the healthcare sector. Several pharmaceutical companies utilize data mining software to examine data and uncover links between patients, medications, and results when developing new drugs or vaccines.
(Also Read - Big Data in Healthcare)
Software Required for Data mining
Data mining software is such software that allows the user or companies to extract useful information and data from a huge amount of uncategorized data. There are many such softwares and the “Top 10” among them are listed below :-
It is one of the most popular open-source data mining systems purely because of its easy-to-use interface. It's a data science software that brings together data preparation, machine learning, deep learning, text mining, and predictive analysis in one place.
Having an easy-to-use visual interface is a solution that removes the difficulty of working with a huge amount of data. It aids in the creation of a repeatable procedure without requiring complicated programming. Its simple visual interface takes the guesswork out of working with your data.
RapidMiner’s benefits are:
1. Predictive Modeling (a technique for predicting the future.)
2.Recognize the Present, revisit and analyze the past.
3. Provides RIO ( Rapid Insight online) webpage for users to share reports and visualizations among teams.
2. Oracle Data Mining
Oracle Data Mining is a software that allows data analysts to create and deploy prediction models. It includes techniques for classification, regression, trend detection, prediction, and other data mining activities.
You may use Oracle Data Mining to create models that display customer behavior analytics, customer profiles in a certain segment, detect fraud, and find the best prospects to target. These models can be integrated into the Business Intelligence application through API using JAVA.
Oracle Data Mining Benefits include:
It can be used to mine data tables
Has advanced analytics and real-time application support
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3. IBM SPSS Modeler
When it comes to large-scale initiatives, IBM SPSS Modeler proves to be the most suitable option. It is a data mining product that enables data scientists to visualize and speed up the process of Data Mining. Advanced algorithms can be used to develop prediction models in a drag-and-drop interface, thus aiding in the creation of data mining techniques that need little or no programming.
Large amounts of data from many sources can be imported and rearranged by data science teams to find trends and patterns. This program only works with numerical data from spreadsheets and relational databases in its standard version, with the text analytics feature being available in its premium version.
IBM SPSS Modeler’s Benefits are :
It has a drag and drop interface making it easily operable for anyone.
A very little amount of programming is required to use this software.
Most suitable Data Mining software for large-scale initiatives.
4. Weka (Waikato Environment for Knowledge Analysis)
Being open-source is one of the best things about this software. It is developed by the University of Waikato, in New Zealand which reflects in its name. It offers a user-friendly graphical interface and can perform a variety of data mining tasks, including preprocessing, classification, regression, clustering, and visualization.
Weka has built-in machine learning algorithms for each of these processes, allowing you to easily test and deploy models without having to write any code. But if you want to take its advantage to the fullest you'll need a thorough understanding of the many algorithms available so that you can select the best one according to your needs.
WEKA’s Benefits include :
If you have a good knowledge of algorithms, Weka can provide you with the best options based upon your needs.
Of course, as it is open source, any issue in any released version of its suite can be fixed easily by its active community members.
It supports many standard data mining tasks.
5. KNIME (Konstanz Information Miner)
It's also an open-source data integration and analysis platform that allows users to create complete data science processes from modeling visualizations to production. The user can deploy, scale, and familiarise data in a matter of minutes.
KNIME is known in the business intelligence sector as the platform that makes predictive intelligence accessible to even unskilled users as using pre-built components, you may quickly create the model without writing any code.
KNIME’s Benefits are -
Offers features such as Social media Sentiment analysis
Data and Tools Blending
It is free and open-source, hence accessible to a large number of users easily.
Data Mining Tools
When it comes to reporting within the company, Sisense is the most useful and well-suited BI software. It enables the merging of data from diverse sources to create a common repository, as well as the refinement of data to provide rich reports that can be shared across departments for reporting.
It holds the honor of being the best business intelligence software in 2016. The reports created by it are highly graphical as this software has been designed keeping in mind non-technical people and hence it offers a drag and drop feature.
Sisense’s benefits include -
It's simple to connect your data, get up, run and get results quickly.
It has an In-Chip Engine.
Offers drag and drop feature which is friendly for beginners.
Reports can be generated using different graphical representations such as pie charts, line charts, bar graphs, and so on.
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7. SAS (Statistical Analysis System)
SAS can mine, modify, and manage data from various sources, as well as do statistical analysis. It also has a graphical user interface designed keeping in mind the non-technical users. It's one of those data science tools that's designed specifically for statistical tasks.
SAS data miners allow users to analyze large amounts of data and gain precise insights into which they may make timely decisions. SAS features a highly scalable distributed memory processing architecture. It's ideal for data mining, text mining, and optimization. The only issue with this application is that it is quite expensive and is only used by larger companies.
SAS Benefits are -
Has a very easy-to-use User Interface.
Supports advanced data modeling
It is fast and also self-efficient in generating models.
Because of its exceedingly basic straightforward visualizations that can be made by anyone, skilled or newbie, Orange is featured in this list of the best free data mining tools. The drab interface that most of the analytic tools have, has been given a more engaging and exciting feel by Orange.
Playing with it is a great experience. The data that comes into Orange is immediately structured into the required pattern, and it can be readily moved about by simply dragging or flipping the widgets. Orange is an open-source data mining and machine learning tool that was written in the Python programming language.
Learning to utilize Orange is also a lot of fun, so if you're a newbie, you can jump right into data mining with this tool. It's ideal for beginners and completely free, with a variety of instructive activities packed with data mining workflows.
Orange’s benefits include :
Has a very vivid and Interactive UI.
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Python is a freely available and open-source language that is easy to learn because of its simple syntax and is one of the most popular programming languages on Earth. Python is an excellent tool for businesses who want their software to be created according to their exact required specifications.
It doesn’t offer fancy features that some open source software provides with Python, but it offers the ability to anyone to pick up and construct their environment using their graphical interfaces according to their own needs.
Python’s Benefits are-
Offers powerful on-the-fly Visualization features to the users.
Has a huge community of package developers who guarantee that the packages available are stable and secure and bug-free.
It is the easiest to learn programming language, and anyone can develop their own Data mining software using this as a tool.
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It is an R language-based Data Mining GUI Software. The software is free and open-source, and it may be used to generate statistical and graphical summaries of data, data transformation for data models, supervised and unsupervised machine learning models, and graphically compare predictive accuracy. You can use the UI to conduct many actions or you can use the code and modify it as needed.
Rattle’s Benefits include -
1 Rattle generates a data set that can be examined and edited.
2. It allows you to inspect the code, utilize it for a variety of purposes, and enhance it without limitation.
By discovering hidden trends and patterns in data, data mining tools can assist you or your company in making better decisions. You must first examine your aim with so many possibilities before deciding which one is ideal for your requirements.
Even if you need to create your data mining solution, we have some wonderful open-source tools that you may use to quickly create one for yourself. So here it is, a list of the most widely used data mining tools assembled for you.