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The standard way to do this is to use Group and Merge, grouping on whichever attribute you want to group on before summing. Then configure the merged output to use the Sum output selector on the group (others such as Average are also available).
You could then use the Number Profiler on the Sum output or similar.
Note that if you want to group by several attributes, it is best to concatenate them first (using a pipe delimiter or similar) and use the output attribute from Concatenate as the Grouping key.
If you are doing transformations regularly / often ( sums, data enrichment from multiple sources, schema inflation / deflation ( source data and target data schemas differ ), perhaps consider using both EDQ and ODI-EE together. Let each do what each does best.
If populating a Data Warehouse or Data Mart with the cleansed data - absolutely want to use ODI-EE along with EDQ. Let EDQ do the enrichment from reference data, matching / merging, deduplication - Let ODI-EE populate the Data Warehouse ( and perhaps also preliminary loading of multiple sources of data into one that is to be cleansed ). ODI-EE has out of the box integration for invoking EDQ data quality processes within ODI-EE data workflows.