![]() The more advance processing is related to database normalisation techniques. If some column may have some cells that remain empty, it's an optional relationship. On the other side, we see that the same value can be repeated, so you can fine-tune the relationship as one-to-many. primary key in Table1 is unique, so it'll be a one-to-xxx relationship. You then need to find out about the cardinality (i.e. This will allow you to draw the relationships between tables. We can also see that some values in LokaalId are repeated several times in Klaslookal. Of course, the name is not a guarantee, but cross-checking it appears that every value of Klaslokaal exist in LokaalId. Candidate 1: Table 1, column Klaslokaal seems to refer to table 2, identifying column LokaalId.Obviously, you'd better check if the hypothesis works: Sometimes they have similar names and there is obviously the same values as content. ![]() In particular, you'll look for the identifier columns of one table to see if it is used in another table. You then need to find out columns in one table that look like columns in the other table.
0 Comments
Leave a Reply. |