Top 5 Data Mining Tools for a Growing Business | Saras Analytics
Data Engineering

Top 5 Data Mining Tools for a Growing Business

5 minutes read

eCommerce

Table of Contents

What is data mining? 

Data mining uses machine learning techniques, statistics, and database systems that help extract and discover patterns in massive data sets. The data mining goal is to get the most relevant information using intelligent methods from varied and enormous data sets and transform them into an easily comprehensible structure for future utilization. Data mining tools use the ETL system (extract, transform, and load). Above all, data engineers use this system to extract data from various sources and fill the data warehouse for further analysis. Data scientists also choose the most relevant data from the data warehouse for gaining insights. It further leads to the data modeling process using data visualization and predictive analysis.

Why does a business need data mining tools? 

Companies generate a large number of data over the years, which has a solid potential to cater to the company’s different needs. Secondly, data scientists and analysts use data mining tools for gaining deep insights into other areas of an organization. Therefore, data mining can derive data from companies’ various sources like transaction data, price determination, customer preferences, positioning of a product, impact on sales, corporate profits, and customer satisfaction. In conclusion, with the help of data mining, a company can use customers’ purchase records to develop products and plan promotions to attract particular customer segments.

Top 5 Data mining tools 

The top data mining tools that extract raw data from various sources and process it into relevant information for future use are:

Oracle

Oracle data mining is one of the top data mining tools. It installs data mining in the Oracle database and uses algorithms to operate the relational tables or views. Secondly, Oracle’s data mining tool helps users by applying unique predictive models according to users’ needs. Hence, this process helps to eliminate the requirement to extract the data and transfer it into standalone tools or a particular analytics server. This tool helps data analysts mine data in the database, build data models, and turn them into results for further use.  In conclusion, Oracle SQL Developer 3.1 is free of cost. Oracle Data Miner GUI is its extension. Users can download SQL developer from OTN ( Optical Transport Networking).

IBM SPSS Modeler

IBM SPSS Modeler developed by IBM is a text analytics software and one of the top data mining tools. It helps to make predictive models and perform analytics tasks. Therefore, it permits users to use statistical and other data mining algorithms without programming. Hence, the IBM SPSS modeler reduces data transformation complexities. This tool is used in healthcare, forecasting demands and sales, predicting movie box office results, education, telecommunications, and much more. In conclusion, the current version of this tool is the SPSS Modeler version 18.2.1. This tool has three editions. They are Personal, Professional, and Premium editions. Additionally, Personal costs from $4950 per user per year, Professional edition costs $7430 per user per year, and Premium edition costs $12300 per user per year.

Orange

Orange is an open-source data visualization tool that provides facilities like machine learning and data mining. It offers a comprehensive solution for business, and can easily script the prototypes of the current algorithms and testing patterns. Secondly, data analysts use this tool for qualitative data analysis. This software is an important data analysis and data mining tool that uses components called widgets. Most importantly, it can help in predictive modeling. The latest version of Orange software for the Windows platform is 3.28.0. Additionally, it provides versions for macOS and Linux too. A free trial is available—pricing not provided by the vendor.

Apache mahout

Apache mahout has a very robust data mining architecture that uses the Hadoop infrastructure at its backend to manage significant volumes of data. Its data mining algorithms efficiently process massive datasets and provide real-time results, unless computational operations run on several machines and spread over the cloud. Mahout analyzes large bulk of data to spot new trends and draw conclusions. It uses robust data mining algorithms. It is available on windows and apple operating systems. The latest version of Apache Mahout is 14.1, which was released in 2020. Mahout provides 30 days of a free trial.

RapidMiner

RapidMiner is an ETL tool that helps in data extraction, transformation, and loading. It has a robust data mining capacity. Other features RapidMiner provides are data preprocessing, data visualization, predictive analysis, statistical modeling, data evaluation, and deployment. RapidMiner is used for commercial applications and businesses. It offers excellent support in research, education, rapid prototyping, training, the development of the application, and all the stages of the machine learning process, including preparation of data, visualization of results, model validation, and optimization. This tool was developed on an open core model. Its latest model is 9.6 and released in 2020. RapidMiner Go is free and has an upgraded version with enhanced features that can cost $10 a month. RapidMiner Studio is free.

Conclusion

Data mining tools use the extraction, transformation, and loading (ETL) system. It helps the data analysts and data scientists extract raw data and put it into data warehouses to be further polished and processed into meaningful information for future use. Modern businesses can use the processed information for predictive analysis, understanding customers’ buying patterns, setting prices, and marketing the products at the right time.  Hence, they save time and effort of the extensive data mining process using a cloud data pipeline: Daton. It is a highly automated cloud data pipeline that fetches real-time data from multiple data sources and loads it to popular data warehouses such as Google Bigquery, Snowflake, and Amazon Redshift. It is easy to use, and requires zero maintenance and coding experience.

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