That data can help us achieve better business results is no secret. Access to data allows us to discover areas for improvement and avenues for optimisation. However, obtaining data is an arduous process that is not always agile. Fortunately, there are many sources of data that can help us speed up the process, as well as data mining, a strategy that is positioning itself as a leader in business.
Data mining is a process of discovering patterns and relationships in data that allow executives to uncover hidden insights into the performance of their business. With this information, companies can take data analytics and data-driven decisions to another level.
Data mining has countless advantages. Data mining allows organisations to gather valuable and reliable information that they can use to make more profitable decisions, reduce operating costs and increase company revenues.
Companies can also use data mining to predict and get ahead of industry trends. In cutthroat markets where the slightest competitive advantage matters, data mining can help businesses survive. Moreover, data mining is significantly more cost-efficient in comparison to other data processing applications.
In terms of customer relations, data mining can actually improve customer loyalty. Since data mining provides companies with insightful information about their customers and their habits, marketing teams will be better equipped to launch successful and more personalized campaigns. Understanding your customers better than they understand themselves allows you to develop a stronger relationship with them as a business. This will ultimately translate into better customer loyalty and a higher conversion rate.
This time, we explore the best free data mining tools and technologies on the market.
1. Xplenty
This platform helps businesses prepare and receive analytic data. It is a great source to use because of its many features. Xplenty has the option of building your own data pipeline.
It has exceptional hardware and software. There are zero code and low code choices. Xplenty also has a great customer support system as well. Due to the variety of features you can customize to your own liking, Xplenty is a perfect data mining platform for any business.
2. Weka
If your intention is to get more visual data and take advantage of data visualisation, Weka is the perfect tool. This platform has several visual tools that reinforce the collected analytics. It also has a greater data mining capability than the previous tool. The data must be in a flat file form so that we can extract the full potential of this platform. With regression, visualisation and processing options, Teka has an optimal software to develop data mining processes.
3. Rapid Miner
Como su nombre deja entrever, Rapid Miner se posiciona como una de las principales plataformas de minería de datos. Creada a partir del lenguaje de programación Java, cuenta con un sinfín de opciones que se centran en el análisis de negocio y en business intelligence.
As its name suggests, Rapid Miner is positioned as one of the main data mining platforms. Created from the Java programming language, it has a host of options that focus on business analysis and business intelligence.
Although it delivers data at a fast pace, the tool performs the process with pretty much no errors. This is all thanks to the available frameworks offered by Rapid Miner, which are easy to use for beginners or non-experts in data mining.
Rapid Miner features Rapid Miner Studio, Rapid Miner Radoop and Rapid Miner Server. Overall, it has a wealth of data collection, processing and mining opportunities for companies to expand their knowledge generation options.
4. Teradata
Also called Teradata database, Teredata is another data mining option that businesses can use. This platform collects specific insights on sales, customer preferences, and also product placement. Teredata is great for helping improve your sales. It is one of the best platforms for sale focused business and or companies.
5. Orange
Instead of being written in Java like most of the previous data mining sites, Orange is written in Python.
Orange offers impeccable software that gathers visual and regular analytics. Unlike the other platforms, Orange has a feature known as widgets. A widget is able to show visual analytics and predictive modeling of algorithms. These widgets contribute to data reading and accessible data tables with checkable features.
Orange also has more bright and appealing tools. So, if you love color, a fresh design, and visual analytics, Orange is a potential choice to collect your business data.
In order to simplify technology-based content for all audiences, try using clear details, and toned-down explanations.
6. Revolution
This platform is user friendly, and data mines statistical and visual data. Revolution gathers data with ease, and can work on more advanced analytics. The graphics and other elements are clean, high quality, and fresh.
Sadly, Revolution lacks the ability to efficiently data mine. This platform is more focused on analysis rather than intense data mining. So, if you want toned down data, revolution can help you gather surface level analytics.
7. Dundas
ere is a platform that can be used by several employees in a company at once. With the feature known as the central data platform, a company can use Dundas to give employees access to data. Dundas has interactive dashboards that make engaging with data less challenging.
This data mining platform is innovative and ideal for large companies with a lot of employees.
All the data mining platforms mentioned in this article are free, so they can help companies gain greater knowledge, information and business insights about their performance, the competition, the market and their customers. Knowing what is really going on is easier than ever.
Exclusively written for bismart.com. Prepared by Kendra Beckley | Kendra Beckley is a business development manager and editor currently working on both Write my thesis and Do my coursework. Kendra assists companies wishing to enter new markets and helps them build lasting relationships with their partners. In her spare time, she enjoys writing about technology applied to business.