यह है ठीक ही कहा है कि आज की दुनिया में डेटा ही पैसा है। ऐप-आधारित दुनिया में परिवर्तन के साथ-साथ डेटा की घातीय वृद्धि होती है। हालाँकि, अधिकांश डेटा असंरचित है और इसलिए डेटा से उपयोगी जानकारी निकालने और इसे समझने योग्य और प्रयोग करने योग्य रूप में बदलने के लिए एक प्रक्रिया और विधि की आवश्यकता होती है।
डेटा माइनिंग या "डेटाबेस में नॉलेज डिस्कवरी" आर्टिफिशियल इंटेलिजेंस, मशीन लर्निंग, सांख्यिकी और डेटाबेस सिस्टम के साथ बड़े डेटा सेट में पैटर्न खोजने की प्रक्रिया है।
मुफ़्त डेटा माइनिंग टूल का दायरा पूर्ण मॉडल विकास वातावरण जैसे कि नीम और ऑरेंज से लेकर जावा, सी++ और अक्सर पायथन में लिखी जाने वाली विभिन्न प्रकार की लाइब्रेरी तक है। डेटा माइनिंग में आमतौर पर चार प्रकार के कार्य शामिल होते हैं:
- वर्गीकरण:नए डेटा को नियोजित करने के लिए परिचित संरचना को सामान्य बनाने का कार्य
- क्लस्टरिंग:डेटा में उल्लेखनीय संरचनाओं का उपयोग किए बिना, डेटा में समूहों और संरचनाओं को खोजने का कार्य जो किसी न किसी तरह से समान हैं।
- एसोसिएशन रूल लर्निंग:वेरिएबल्स के बीच संबंधों की तलाश करता है
- प्रतिगमन:एक ऐसे फ़ंक्शन को खोजने का लक्ष्य रखता है जो डेटा को थोड़ी सी भी त्रुटि के साथ मॉडल करता है।
- Upload a prediction problem
- Submit
- Evaluate and Exchange
डेटा माइनिंग के लिए नि:शुल्क सॉफ़्टवेयर टूल की सूची नीचे दी गई है -
2022 में सर्वश्रेष्ठ मुफ्त डाटा माइनिंग टूल्स की सूची:-
1. रैपिड माइनर -
रैपिड माइनर, जिसे पहले YALE (फिर भी एक और लर्निंग एनवायरनमेंट) कहा जाता था, मशीन लर्निंग और डेटा माइनिंग प्रयोगों के लिए एक वातावरण है जिसका उपयोग अनुसंधान और वास्तविक दुनिया के डेटा-माइनिंग कार्यों दोनों के लिए किया जाता है। . यह निर्विवाद रूप से डेटा माइनिंग के लिए विश्व-अग्रणी ओपन-सोर्स सिस्टम है। जावा प्रोग्रामिंग लैंग्वेज में लिखा गया यह टूल टेम्प्लेट-आधारित फ्रेमवर्क के माध्यम से उन्नत एनालिटिक्स प्रदान करता है।
यह बड़ी संख्या में मनमाने ढंग से नेस्ट करने योग्य ऑपरेटरों से बने प्रयोगों को सक्षम बनाता है, जो एक्सएमएल फाइलों में विस्तृत हैं और रैपिड माइनर के ग्राफिकल यूजर इंटरफेस के साथ बनाए गए हैं। सबसे अच्छी बात यह है कि यूजर्स को कोड लिखने की जरूरत नहीं है। इसमें पहले से ही कई टेम्प्लेट और अन्य टूल हैं जो हमें डेटा का आसानी से विश्लेषण करने देते हैं।
2. आईबीएम एसपीएसएस मॉडलर -
IBM SPSS मॉडलर टूल वर्कबेंच टेक्स्ट एनालिटिक्स जैसे बड़े पैमाने की परियोजनाओं पर काम करने के लिए सबसे अच्छा है, और इसका विज़ुअल इंटरफ़ेस अत्यंत मूल्यवान है। यह आपको बिना किसी प्रोग्रामिंग के विभिन्न प्रकार के डेटा माइनिंग एल्गोरिदम उत्पन्न करने की अनुमति देता है। इसका उपयोग विसंगति का पता लगाने, बायेसियन नेटवर्क, CARMA, कॉक्स रिग्रेशन और बेसिक न्यूरल नेटवर्क के लिए भी किया जा सकता है जो बैक-प्रचार सीखने के साथ मल्टीलेयर परसेप्ट्रॉन का उपयोग करते हैं। कमज़ोर दिल वालों के लिए नहीं।
3. Oracle डेटा माइनिंग -
डेटा माइनिंग क्षेत्र में एक और बड़ा हिटर Oracle है। As part of their Advanced Analytics Database option, Oracle data mining allows its users to discover insights, make predictions and leverage their Oracle data. You can build models to discover customer behavior target best customers and develop profiles.
The Oracle Data Miner GUI enables data analysts, business analysts and data scientists to work with data inside a database using a rather elegant drag and drop solution. It can also create SQL and PL/SQL scripts for automation, scheduling and deployment throughout the enterprise.
4. Teradata –
Teradata recognizes the fact that, although big data is awesome, if you don’t actually know how to analyze and use it, it’s worthless. Imagine having millions upon millions of data points without the skills to query them. That’s where Teradata comes in. They provide end-to-end solutions and services in data warehousing, big data and analytics and marketing applications.
Teradata also offers a whole host of services including implementation, business consulting, training and support.
5. Framed Data –
It’s a fully managed solution which means you don’t need to do anything but sit back and wait for insights. Framed Data takes data from businesses and turns it into actionable insights and decisions. They train, optimize, and store product ionized models in their cloud and provide predictions through an API, eliminating infrastructure overhead. They provide dashboards and scenario analysis tools that tell you which company levers are driving metrics you care about.
6. Kaggle –
Kaggle is the world’s largest data science community. Companies and researchers post their data and statisticians and data miners from all over the world compete to produce the best models.
Kaggle is a platform for data science competitions. It help you solve difficult problems, recruit strong teams, and amplify the power of your data science talent.
3 steps of working –
7. Weka –
WEKA is a very sophisticated best data mining tool. It shows you various relationships between the data sets, clusters, predictive modelling, visualization etc. There are a number of classifiers you can apply to get more insight into the data.
8. Rattle –
Rattle stands for the R Analytical Tool to Learn Easily. It presents statistical and visual summaries of data, transforms data into forms that can be readily modelled, builds both unsupervised and supervised models from the data, presents the performance of models graphically, and scores new datasets.
It is a free and open source best data mining toolkit written in the statistical language R using the Gnome graphical interface. It runs under GNU/Linux, Macintosh OS X, and MS/Windows.
9. KNIME –
Konstanz Information Miner is a user friendly, intelligible and comprehensive open-source data integration, processing, analysis and exploration platform. It has a graphical user interface which helps users to easily connect the nodes for data processing.
KNIME also integrates various components for machine learning and data mining through its modular data pipelining concept and has caught the eye of business intelligence and financial data analysis.
10. Python –
As a free and open source language, Python is most often compared to R for ease of use. Unlike R, Python’s learning curve tends to be so short it’s become legendary. Many users find that they can start building data sets and doing extremely complex affinity analysis in minutes. The most common business-use case-data visualizations are straightforward as long as you are comfortable with basic programming concepts like variables, data types, functions, conditionals and loops.
11. Orange –
Orange is a component based data mining and machine learning software suite written in Python Language. It is an Open Source data visualization and analysis for novice and experts. Data mining can be done through visual programming or Python scripting. It is also packed with features for data analytics, different visualizations, from scatterplots, bar charts, trees, to dendrograms, networks and heat maps.
12. SAS Data Mining –
Discover data set patterns using SAS Data Mining commercial software. Its descriptive and predictive modelling provides insights for better understanding of the data. They offer an easy to use GUI. They have automated tools from data processing, clustering to the end where you can find best results for taking right decisions. Being a commercial software it also includes advanced tools like Scalable processing, automation, intensive algorithms, modelling, data visualization and exploration etc.
13. Apache Mahout –
Apache Mahout is a project of the Apache Software Foundation to produce free implementations of distributed or otherwise scalable machine learning algorithms focused primarily in the areas of collaborative filtering, clustering and classification.
Apache Mahout supports mainly three use cases:Recommendation mining takes users’ behavior and from that tries to find items users might like. Clustering takes e.g. text documents and groups them into groups of topically related documents. Classification learns from existing categorized documents what documents of a specific category look like and is able to assign unlabeled documents to the (hopefully) correct category.
14. PSPP –
PSPP is a program for statistical analysis of sampled data. It has a graphical user interface and conventional command-line interface. It is written in C, uses GNU Scientific Library for its mathematical routines, and plot UTILS for generating graphs. It is a Free replacement for the proprietary program SPSS (from IBM) predict with confidence what will happen next so that you can make smarter decisions, solve problems and improve outcomes.
15. jHepWork –
jHepWork is a free and open-source data-analysis framework that is created as an attempt to make a data-analysis environment using open-source packages with a comprehensible user interface and to create a tool competitive to commercial programs.
JHepWork shows interactive 2D and 3D plots for data sets for better analysis. There are numerical scientific libraries and mathematical functions implemented in Java. jHepWork is based on a high-level programming language Jython, but Java coding can also be used to call jHepWork numerical and graphical libraries.
16. R programming Language–
There’s no mystery why R is the superstar of free data mining tools on this list. It’s free, open source and easy to pick up for people with little to no programming experience. There are literally thousands of libraries that can be incorporated into the R environment making it a powerful data mining environment. It’s a free software programming language and software environment for statistical computing and graphics.
The R language is widely used among data miners for developing statistical software and data analysis. Ease of use and extensibility has raised R’s popularity substantially in recent years.
17. Pentaho –
Pentaho provides a comprehensive platform for data integration, business analytics and big data. With this commercial tool you can easily blend data from any source. Get insights into your business data and make more accurate information driven decisions for future.
18. Tanagra –
TANAGRA is a data mining software for academic and research purposes. There are tools for exploratory data analysis, statistical learning, machine learning and databases area. Tanagra contains some supervised learning but also other paradigms such as clustering, factorial analysis, parametric and non-parametric statistics, association rule, feature selection and construction algorithms.
19. NLTK –
Natural Language Toolkit, is a suite of libraries and programs for symbolic and statistical natural language processing (NLP) for the python language. It provides a pool of language processing tools including data mining, machine learning, data scrapping, sentiment analysis and other various language processing tasks. Build python programs to deal with human language data.
We hope our list of best free data mining tools was helpful to you. We would love to know your opinion, please do share your views in the comments section below.