Even after Summer'18, we still have a key gap between Classic and #Lightning about scheduling refresh of dashboards :
In Lightning, we have the 'Subscribe' option for Dashboards but this option is different than the 'Schedule refresh' option in Classic. With the Subscribe option in Lightning :
- we cannot assign public groups to recipient list
- the subscribe option is limited to 5 subscriptions per user.
In Classic, we have none of these 2 limitations.
In my company, many users (through groups) are receiving, by email, more than 10 refreshed Classic dashboards each week in their mailbox. We cannot move to Lightning dashboards as long as the Schedule refresh to groups option is not implemented in Lightning.
Is there any solution or workaround ?
Is there any #Roadmap for removing this gap ?
I found the following idea, that is raising a similar need. Thanks in advance for your votes : https://success.salesforce.com/ideaView?id=0873A000000lLiMQAU
Hi, @Pierre SUCHET - Wow! That is a really impressive set of Dashboards for sure!
Here are my thoughts though, specifically around each of the Data Quality Dashboards, as an example, I have a customer who has many objects with key data points where data quality is a concern.
We made very specific reports for each object to get us record counts of all records that failed a particular data quality check.
Then, we added each Report to the common "Data Quality" dashboard - all as Metric Components...just show me the record counts for all.
This one dashboard is reviewed daily by me, the two System Admins and one Executive Sponsor (we are still in Classic, so we have the benefit of Refresh) and, if there are any Metric Components with Record Count not equal to 0, we first correct the data errors (or notify Users to do so) and then we add to our Road Map a plan for Corrective Action.
The Road Map is reviewed by a Committee periodically and when they approve the Corrective Action(s), we make the updates to the Sandbox first (say a Validation Rule or a WFR/Process Builder), test it and deploy to Production.
The goal is for the Data Quality issues to be mitigated so that we can drop them off our Dashboard for good.
