Data mining is looking for hidden, valid, and all the possible useful patterns in large size data sets. Data Mining is a technique which helps you to discover unsuspected/undiscovered relationships amongst the data for business gains.There, are many useful tools available for Data mining. Following is a curated list of Top 25 handpicked Data Mining software with popular features and latest download links.
This comparison list contains open source as well as commercial tools. 1) SAS Data mining:Statistical Analysis System is a product of SAS. It was developed for analytics and data management. It offers a graphical UI for not technical users.Features:.
SAS Data mining tools help you to analyze Big data. It is an ideal tool for Data mining, text mining & optimization.
SAS offers distributed memory processing architecture which is highly scalableDownload link:2) Teradata:Teradata is a massively parallel open processing system for developing large-scale data warehousing applications. Teradata can run on Unix/Linux/Windows server platform.Features:.
Teradata Optimizer can handle up to 64 joins in a query. Tera data has a low total cost of ownership. It is easy to set up, maintain, and administrate. It supports SQL to interact with the data stored in tables.
It provides its extension. It helps you to distribute the data to the disks automatically with no manual intervention. Teradata provides load & unload utilities to move data into/from Teradata System.Download link:3) R-ProgrammingR is a language for statistical computing and graphics. It also used for big data analysis. It provides a wide variety of statistical tests.Features:. Effective data handling and storage facility,.
It provides a suite of operators for calculations on arrays, in particular, matrices,. It provides a coherent, integrated collection of big data tools for data analysis.
It provides graphical facilities for data analysis which display either on-screen or on hardcopy.Download link;4) BOARDBoard is a Management Intelligence Toolkit. It combines features of business intelligence and corporate performance management. Features:. Server application with full product functionality. Integrate and access all kind of data sources. Customizable data visualizations.
Smart drag and drop tools. Visualize data through maps.
Predictive and advanced data analyticsDownload link:6) InetsoftInetsoft's Data mining tool style Intelligence is useful data mining and intelligence platform. It allows the quick and flexible transformation of data from various sources.Features:. It helps you to access structured and semi-structured sources, on-premise applications.
Allows you to optimize apps for data consumption and updating. Offer customized and secure levels of data exploration and reporting. Scale up for large data sets of users using Inbuilt Spark platform.
Generate paginated reports with embedded business logic and parameterizationDownload link:7) H3OH3O is another excellent open source software Data mining tool. It is used to perform data analysis on the data held in cloud computing application systems.Features:.
H3O allows you to take advantage of the computing power of distributed systems and in-memory computing. It allows fast and easy deployment into production with Java and binary format. It helps you to use the programming languages like R,.
Python and others to build a model in H3O. Distributed, In-memory ProcessingDownload link:8) QlikQlik is Data mining and visualization tool. It also offers dashboards and Supports multiple data sources and file types.Features:.
Drag-and-drop interfaces to create flexible, interactive data visualizations. Instantly respond to interactions and changes. Supports multiple data sources and file types. It allows easy security for data and content across all devices. It allows you to share relevant analyses, including apps and stories, using a centralized hub.Download link:9) RapidMiner:RapidMiner is a free to use Data mining tool.
It is used for data prep, machine learning, and model deployment. It offers a range of products to build new data mining processes and predictive setup analysis.Features:. Allow multiple data management methods.
GUI or batch processing. Integrates with in-house databases.
Interactive, shareable dashboards. Big Data predictive analytics. Remote analysis processing.
Data filtering, joining, merging, and aggregating. Build, train and validate predictive models. Reports and triggered notificationsDownload link:10) Oracle BI. Oracle BI is an open source machine learning and data visualization for novice and expert. Interactive data analysis workflows with a large toolbox.Features:. Interactive Data Visualization. It Offers Interactive data exploration for rapid qualitative analysis with clean visualizations.
Orange supports hands-on training and visual illustrations of concepts from data science. It offers an extensive range of add-ons to data mining from external data sources.Download link:11) KNIMEKNIME is open source software for creating data science applications and services.
This Data mining tool helps you to understand data and to design data science workflows.Features:. Helps you to build an end to end data science workflows. Blend data from any source. Allows you to aggregate, sort, filter, and join data either on your local machine, in-database or in distributed big data environments. Build machine learning models for classification, regression, dimension reductionDownload link:12) TanagraTangra is a free to use data mining tool for study and research purposes. It offers various data mining methods from statistical learning, data analysis, and machine learning.Features:. Offers easy to use data mining software for researcher and students.
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It allows the user to add their data mining methods.Download link:13) Solver:Solver's XLminer is easy to use professional level Data mining tool for data visualization, forecasting, and Data mining in Excel. It offers comprehensive set of data preparation features to import and clean your data.Features:. XLMiner offers a comprehensive set of analysis features based both on statistical and machine learning methods. The tool allows you to work with large data sets which may exceed the limits in Excel.
It offers built-in features for data exploration and visualization. Exploring data offers quick insights into hidden relationships in the data.Download link:14) SisenseSisense is another effective Data mining tool. It instantly analyzes and visualizes both big and disparate datasets.
It is an ideal tool for creating dashboards with a wide variety of visualizations.Features:. Allows to build interactive dashboards with no tech skills.
Create a single version of the truth with seamless data. Unify unrelated data into one centralized place. East drag-and-drop user interface. Allows to access dashboards even in the mobile device.
Eye-grabbing visualization. Identifies critical metrics using filtering and calculations. Handles large scale data at a single commodity serverDownload link. 15) Data MeltDataMelt is a free to use tool for numeric computation, mathematics, data analysis, and data visualization.
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Introduction to Data Mining SoftwareData mining is a process of analyzing data, identifying patterns and converting unstructured data into structured data ( data organized in rows and columns) to use it for business-related decision making. It is a process to extract large unstructured data from various databases. Data mining is an interdisciplinary science that has mathematics and computer science algorithms used by a machine. Data Mining Software helps the user to analyze data from different databases and detect the pattern. The basic aim of is to find, extract and refine data and then distribute the information.
Features of Data Mining Tools. Easy to use: Data mining software has easy to use Graphical User Interface (GUI) that helps the user to analyze data efficiently. Pre-processing: Data pre-processing is a necessary step. It includes data cleaning, data transformation, data normalization and data integration.
Scalable processing: Data mining software permits scalable processing i.e. Hadoop, Data Science, Statistics & others 1.
Orange Data MiningIt is an open-source data analysis. In this, data mining is done through Python scripting and visual programming. It contains features for data analytics and components for machine learning and text mining.
R Software EnvironmentR is a free software environment for graphics and statistical computing. It can run on various UNIX platforms, MacOS and Windows.
It is a suite of software facilities for calculation, graphical display, and data manipulation. Weka Data MiningIt is a collection of algorithms of machine learning to perform data mining tasks. The algorithms can be called using Java code or they can be directly applied to the dataset. It is written in Java and contains features like machine learning, preprocessing, data mining, clustering, regression, classification, visualization, and attribute selection. SpagoBI Business IntelligenceIt is an open-source. It offers advanced data visualization features, a large range of analytical functions and a functional semantic layer.
The various modules of the SpagoBI suite are SpagoBI Studio, SpagoBI SDK, SpagoBI Server, and SpagoBI Meta. AnacondaIt is an.
It is a high-performance distribution of. It includes packages of R, Scala, and Python for data mining, stats, deep learning, simulation and optimization, and image analysis. ShogunIt is an open-source, free toolbox. It has various data structures and algorithms for machine learning problems. Its main focus is on kernel machines like support vector machines. It allows the user to combine algorithm classes, multiple data representations, and general-purpose tools easily. It allows the full implementation of Hidden Markov Models.
DataMeltIt is a software for statistics, numeric computation, scientific visualization. It is a computational platform. It can use different programming languages on various operating systems.
Natural Language ToolkitIt is a platform for implementing python programs to work with human language data. It has easy to use interface. It provides resources such as WordNet and has a suite of text processing libraries and a discussion forum. It is useful for students, engineers, researchers, linguists, and industry users.
Apache MahoutIts main aim is to create an environment for building scalable machine learning applications quickly. It contains various algorithms for Apache Spark, Scala, and Apache Flink. It is implemented on Apache Hadoop and uses MapReduce Paradigm. GNU OctaveIt represents a high-level language built for numerical computations.
It works on a command-line interface and hence allows users to solve linear and nonlinear problems numerically using a language compatible with Matlab. It offers features like visualization tools. It runs on Windows, macOS, GNU/Linux, and BSD. RapidMiner Starter Edition:It provides an integrated environment for machine learning, data preparation, text mining, and deep learning. It is used for commercial and business applications, research, training, education, and rapid prototyping. It supports data preparation, model visualization, and optimization. GraphLab CreateIt is a to that includes data cleaning, training the model and developing features.
These applications provide predictions for use cases of fraud detection, sentiment analysis, and churn prediction. Lavastorm Analytics EngineIt is a visual data discovery solution that permits to integrate diverse data rapidly and detect outliers, anomalies continuously. It offers the self-service capability for business users. It provides features like transform, acquire, and combine data without pre-planning and scripting. Scikit-learnIt is an open-source machine learning library for. It provides different classification, clustering and regression algorithms including random forests, K-means, and support vector machines. IT is built to work like NumPy and SciPy.
ConclusionThis article contains a brief introduction to data mining software. These software help users to perform data mining tasks efficiently and quickly. If a person wants to build its career in data mining then these tools are highly recommended. Recommended ArticlesThis has been a guide to Data Mining Software. Here we discussed the concepts, features and some different software of data mining.
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