Just like any other process, data classification has its challenges.
Some of the challenges that organizations face in their data classification process are:
Big data
Let’s face it, data is ever-growing and poses bigger and bigger challenges as time passes. Non-continuous tools for classification can struggle when applied to data lakes and warehouses with huge amounts of data.
False positives
When the same bit of data appears in different contexts and formats, it’s a false positive. If your classification algorithms don’t consider the context and format, you will likely have false positives.
False negatives
On the other hand, you can have false negatives. Data can be sensitive in one context but not in another context. Since regulations differ, a piece of data can be considered sensitive in one state and not sensitive in another. This can often lead to incorrect classification.