Data enables us to granularly understand our consumers and build better, more effective marketing campaigns. In other words, it’s marketing gold.
Too many companies today underutilize the customer data that’s available to them. While the amount of data available may seem overwhelming at times, there are a number of tools available today to help you analyze your data and put it to good use. With the help of open-source data mining tools, today collecting useful data has never been easier.
What is data mining?
Data mining can be explained in three simple words: looking for patterns. Data mining is the practice of looking for patterns by association, connecting events with each other, and looking for possible new patterns and documenting them.
There are hundreds of open-source tools out there that can help you mine data. Even though many data mining softwares are great for novice users, it is helpful to know some data mining languages as you get more technical down the road.
The most popular are Python, R, and SQL, and there are dozens of resources out there to help you learn them.
Why open source makes sense
Open source is quickly becoming the gold standard in the tech industry. Tech giants like Facebook and Google have been sharing their data and code to the public in an effort to improve their product quickly and cheaply. We aren’t the only ones who are big open source advocates. PC World, Datamation, InfoWorld, and others agree on the power of open source being a secure solution to developing a project.
When it comes to data mining, open source tools provide easy integration with other technologies and many offer a marketplace to fully customize your data mining experience.
Even more, R, a language and environment for statistical computing and graphics, is completely free as well as the Google Chart API, that allows you to make charts and graphs that you can embed into your site.
Closed just doesn’t fit
With proprietary software, you’re stuck with a single vendor, the languages don’t translate easily across platforms, retain the source code and is constantly critiqued.
Talking about closed-source data mining tools is difficult because there simply aren’t that many. The leading data mining tools are open source because open platforms provide users with the agility and freedom to mine complex data.
Open source data mining tools
With data mining tools, even the messiest, unorganized data can become extremely valuable. Here are the best open source data mining tools for the beginners, hobbyists, or professional coders:
Rapid Miner
Rapid Miner is the number one open source data science platform. They boast a lightning fast platform with over 1,500 built-in functions, including easy integration with all types of data, machine learning, and advanced analytics through template-based frameworks. Rapid Miner is written in Java, yet instead of a software, Rapid Miner acts like a service, requiring little coding knowledge. The most celebrated tool is the Visual WorkFlow Designer that makes it easy to use the visual environment.
Orange
Orange data mining is another option to experience great visualization and data analysis that doesn’t allow coding. Orange boasts the value of their online tutorials. The software runs on Python and is used in many universities and training courses around the world. True to open source, Orange has tons of add-on features to mine data
Weka
On the Weka homepage, the community has it’s own widget, along with a marketplace tab where you can download plugins and language packs, making your data mining platform fully customizable. The data mining platform also encourages you to submit your own plugins and language packs. Weka also allows you to import data from many data types including a database, or a CSV file.
KNIME
With the tagline, “open for innovation,” KNIME even has a quick link to it’s open source story. The platform is written in Java and based on Eclipse and like WordPress, equipped with a plugin system. KNIME takes pride in having the largest database of advanced algorithms, no artificial limitations, like machine processing size and number of data rows.
Happy mining
All marketers today should be leveraging data in as many ways as possible. It can help them become successful and provide the insight to their marketing to the next level.