Why is operational data sometimes unusable for Business Intelligence (BI) use? Include at least two examples

What will be an ideal response?

Data in operational databases can suffer from a number of problems. These include: (1 ) Dirty data—data that has problems with it, for example an age of "323;" (2 ) Missing values—data values that are unknown, for example a person's age; (3 ) Inconsistent data—old data values that needed to be updated may not have been—for example a ZIP code in an area that was split into two new ZIP codes; (4 ) Data not integrated—when data from two or more data sets is used, the data may be from two or more different DBMSs; (5 ) Data in the wrong format—data values may have been recorded at an inappropriate value for the needed analysis—for example, distance may have been recorded in miles when we need meters; (6 ) Too much data—it is possible to simply have very large data sets in terms of records or fields.