What are some of the best practices for data quality...Published 1 month ago Views (16) Technology
While running a company, you may face several data quality issues during monitoring machine learning models. These can eventually result in the dissatisfaction of your customers.
Sometimes it becomes very difficult to find the problems with your data and solve those issues without any delay. This is a common problem that you may face while dealing with the quality of data.
So, to avoid those data-related problems, you should follow a few practices for data quality checks and monitoring while working with the procedures of monitoring ML models.
Nowadays, machine learning needs a good amount of data to work properly. Also, the analytics always search for new data, which can increase the value of the data sets. Discussed below is all about data quality and what the steps are to check and monitor this properly.
What is Data Quality?
The quality of data is high when it can satisfy the requirements of its intended purpose and use for decision-makers, clients, and also downstream applications and procedures.
A good quality product can eventually meet the expectations of the customers and increase their levels of satisfaction, hence making the company more successful. Similarly, data quality is a crucial attribute that could increase...
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