Data designer hacks

Hi Everyone! I’ve put together a few hacks that I have been using so far to solve different use cases to overcome the limitations of Data Designer.

1. How to enable Mapping or click-through through DD.

As you may have already observed when you merge two datasets lets say Company and Contact, the resultant merge dataset will have only Company name/CTA name as text and click-through will be lost disabling the flexibility to navigating to that Company C360 page or cockpit when you click on Company name. The reason for this could be not bringing the Company GSID or CTA ID.

Solution/Workaround: The catch here is that you need to bring the Comapny GSID(to navigate C360)and name or CTA ID (To navigate to cockpit) and Name so that URLs are perserved rather than displaying just text.

2. You can drill down only upto three levels in DD. Then what do you do to drill down if you want data from fourth Level?

Solution/Workaround: In Data Designer, you can drill down upto three lookups, and the lookups beyond the third shown will not show up at all. So if you want to drill down to the fourth level, you need to bring the fourth level object as a separate dataset and then merge the actual dataset with the new dataset.

Example: NPS Survey Response: Participant id (Survey Participant)-> AO Participant id(AO Participant) -> Company id (Company) ->CSM (Company Person)

Now picking the CSM for a survey participant becomes fourth level, we bring in the Company person object as separate another dataset within the same data designer and we merge both of them using Company id.

3. You can’t create lookups on DD objects.

If you observe the objects created when you run the data designer are standard ones which means it is not possible to edit the object schema or add lookups.

Solution/Workaround: Because you will not be able to create lookups you need to carefully choose and bring-in all the fields which you will need in the final dataset. If you have missed to include any field, you need to drag that field in the design from source to final dataset and run the designer again so that the previous object gets deleted and a new object with more fields will be created automatically.

4. Data designer objects are truncate and load type, so to manage incremental data.

Solution/Workaround: Since Data designer objects are temporary datasets, the data present in these objects is truncated and freshly loaded every time the job is run. So when trying to manage incremental data(Usage data for example) through designer, work around is to route all this data to a custom object through rules engine before the next run of data designer.

5. Data Designer objects are standard type, you cannot modify the field data types or add fields.

Solution/Workaround: We need to carefully change the datatypes of required fields proactively within the design rather than trying to modify it from Data management. If at all you realise that the datatype should have modified afterwards, just modify it in designer and re-run the job so that the object is deleted and freshly created accommodating the new changes.

Hope these help, please feel free to post in comments if you have any more hacks.