“Normal” Dashboards are based on BAQs. Output is generally grids. Portions of the dashboard can subscribe to another grid that updates as records change. Dashboards can be updatable.
Epicor Data Discovery (EDD) is also based on BAQs. They generally display data visually although it’s possible to filter and drill down into the under lying data. They cannot update data as far as I’ve seen.
BI, short for Business Intelligence, generally works on data extracted and imported into its own datastore. Grow, Epicor Data Analytics (EDA), PowerBI/Microsoft Fabric, Tableau, etc. are examples of BI products. Like EDD, data is visualized and one can drill down and filter into it. One often combines data from multiple systems.
If you’re in the browser, you could generate (or export) the link that would take to you the associated app. Check out the Share capability in the vertical dot menu to see the link.
OTOB, I don’t think you can update the original data source since you’re working on a copy. You may be able to update the copy though…
To expand on Mark’s comment a bit regarding the largest difference. BAQs, SQL/SSRS, EDD are all going to provide latest version of the data.
Typically for BI, you extract the data, warehouse it, possibly transforming or normalizing it. Not just from ERP, but all related analytical information. Social Media, multiple ERP DBs, etc.
BI platforms are fancy solutions for sourcing, storing, calculating and visualizing business data.
In the Epicor sphere: Grow BI is the most user-friendly and Microsoft Fabric/PowerBI being the most flexible in exchange for higher technical complexity.
– In my opinion, I’d lean more towards a comprehensive solution like Microsoft’s if you have more data or sources. You don’t need a massive scale business to benefit from BI, but if you have a simple setup - go simple with your solution. Grow BI being an amazing choice there.
Also, something stuck with me was a delineation of when a BAQ/SQL query should be used and when BI should be used.
BAQ/SQL/Dashboards are primarily used for real time data where the row counts are in the thousands or less. So what’s currently happening in the business, what happened last month or last year is irrelevant and shouldn’t be included in the data.
BI is used when the row counts are approaching the millions and doesn’t need to be real time. This is things like analyzing sales trends over year(s). This approach extracts the data and does some transformation work on it so that when the reports are used they can have an acceptable calculation and response time. Because of this load and translation, this is usually done in batches so data is usually delayed until a load and transformation happens. This is usually scheduled daily, or weekly depending on what the data is used for.
There is a considerable amount of overlap between the capabilities of the two and in many cases, either can be used. As stated the primary two drivers for selection of which tool is best are: performance when dealing with large data sets, and the necessity of real time data.