30 % of companies say data duplication is Redundant data one of the top issues facing their intelligence team. This often happens for a number of reasons, the two most common being the lack of a shared tool across different departments and a standard for entering data.
2. Human error
Remember that data mining is analyzing a lot of pre-existing data somewhere in your company? This means that someone has collected and stored this data before, and it may not have been done according to best practices.
3. Security and privacy
When it comes to data mining, cybersecurity is key for any business. In fact, data privacy is no longer a requirement of a few customers, but a business responsibility under the law .
Read more: Data Protection Act: What is it and how to follow it in your company?
4. Lack of specialized professionals
Technology is a great phone number database ally, but it does not work miracles. No matter how sophisticated data processing techniques are, a specialized professional is always necessary. After all, there are human aspects and nuances that many computer programs are not yet able to recognize.
How is data mining done?
The explanation of what data mining is is only complete when the stages that make up this process are understood. They are:
Definition of the objective Redundant data
Data selection
Data cleansing
Application of data mining techniques
Evaluation of the pomodoro time management technique results obtained
Use of information
1. Definition of the objective
When learning how to america email do data mining, the first step is to define what the objective of the process is. This search for information must be aligned with the strategic objectives of the company .
To achieve a good definition of objectives, you can base yourself on goals and indicators that need to be improved.