There are different types of rules that can be created in Loome Monitor.
An alert is used to define a data quality or process compliance exception that you want to keep track of and assign to someone to resolve.
Annotate an existing list of terms, fields or tables with explanatory notes and classifications.
Define a data set that requires a data steward to manually update additional attributes for reporting purposes.
Define a set of validation checks to be run for specific columns in your data set.
Check for differences between two data sets. You can compare two data sets in one rule, and view both in the one results table to see highlighted mismatches and orphan records from each data set. You will need to provide a connection for both your source and comparison data set, as well a query for each. The column names and data types will also need to match.
As well as choosing from different rule types, you can also choose whether you would like to add manually created records to your data set. The option to add manually populated data is provided once you have chosen a rule type.
You can only manually populate rows in a glossary or reference. Once you select ‘Manual Data’ or ‘Both Source Query And Manual Data’ as your data source, you can also choose to add additional records to your source data set on the results page, or you can create a data set comprised entirely of columns and rows that you have added in Loome.