Which of the following are issues in data integration? (which would actually cause conflicts) Question 4 options: Two different databases may have different column names for the same actual information (e. g. customer ID vs customer-id). Databases on related subjects that you want to integrate may have different numbers of columns or rows. An attribute named 'weight' may be in different units in different databases. There may be discrepancies between entries in two different databases for the same actual real-life entity (e. g. for an employee).

The observed issues in data integration include the following from the listed options:

Two different databases may have different column names for the same actual information (e.g. customer ID vs customer-id).

There may be discrepancies between entries in two different databases for the same actual real-life entity (e.g. for an employee).

Explanation:

Data integration aims at consolidating data from disparate sources into a single dataset provide users with consistent access to data that will meet their various needs.  However, the process of data integration faces many challenges.  One of the challenges is disparate data formats and sources.  There is also the velocity or speed at which data are gathered.  For successful data integration, the different datasets need to be cleaned and updated with quality data.