It seems that no matter what industry it is, everyone is trying to find the best means to analyze and draw actionable conclusions from their data. Data mining has grown to be the cornerstone of modern-day business operations. By clinical definition, data mining is defined as “the process of extracting patterns from data.” This definition is far from precise, but it does a great job of illustrating how tough the analysis process can be. In many cases, it is labor intense and time consuming, as if you were actually using a pick and axe.
The best data mining application is the application that best fits both your analytical needs and the skill set of your employees. Analytical needs can vary based on the level of analysis you desire and the type of data being utilized. For example, the needs of analysts working with social media data, financial reporting, and survey research data are all different. Applications may provide differences in analysis features (statistics, verbatim reporting, etc.), file size limits, and source data flexibility.
Simultaneously, your employees need to be able to use the application effectively. One of the chief concerns in implementing any new system in the workplace is the amount of time required to adopt and productively use the software. Systems with user-friendly interfaces an
d intuitive functionality can ease the adoption process, while complicated programs may inhibit worker productivity, and in some cases, result in poor or erroneous analysis. And, as employees turn to telecommuting and team-based work, applications that can incorporate cloud co
In short, a multitude of software packages are available for data mining. Each have their own strengths and weaknesses, but all that really matters is which package best suits your objectives. And in an environment where speed, accuracy, and insights are key to success, why not let the software do the heavy lifting?mputing or collaborative capabilities have an advantage going forward.