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Bite Size Analytics: How to Build Simple Datasets

Analytics are dependent on the quality of the data available. While pre-built datasets exist, users may need to create their own to report on specific areas of Certinia products. This process involves understanding data connections and selecting the appropriate level for reporting. When building datasets, numerical fields from lower-level objects can be duplicated if not handled correctly. It is advisable to source numerical and currency fields directly from the source object.

  • May 28, 2024
  • Knowledge

Title
Bite Size Analytics: How to Build Simple Datasets
URL Name
Bite-Size-Analytics-How-to-Build-Simple-Datasets
Summary
Analytics are dependent on the quality of the data available. While pre-built datasets exist, users may need to create their own to report on specific areas of Certinia products. This process involves understanding data connections and selecting the appropriate level for reporting. When building datasets, numerical fields from lower-level objects can be duplicated if not handled correctly. It is advisable to source numerical and currency fields directly from the source object.

Objective

Analytics is only as good as the data you have and we have built some out-of-the-box datasets that allow you to report on this data within analytics. Many of the datasets that we ship relate to dashboards we have built but some can be repurposed. However, there may be areas of the Certinia products that we do not have datasets for yet and as such you may want to build your own datasets so that you can build reports and dashboards. Complex datasets with object transformations can be built with analytics and that is what we do lots of within our shipped products, however it does not need to be difficult and simple datasets can be built as outlined below.

Product Area
Reporting & Analytics
Release Version
Environment

All versions

Procedure

One thing to bear in mind is how data is connected and choose the lowest level of reporting that will be required within the dataset. This can normally be determined by viewing the object you want to report on and then by going into each related list until you don't want to go any further. The reason for this is that when we build a data structure we can go into the lookup fields to get more fields but we can't go into related lists easily.

You should also note that when it comes to reporting on numerical fields if there are multiple lower-level object records then any numbers reported higher up may be duplicated. For example, if you wanted to report on opportunity lines and get the sum of the amounts, the sum will be the correct total. If however, you then took the total amount from the opportunity record (via the line), and you had more than one opportunity line for an opportunity, then when it comes to reporting on the data, the opportunity amount will be multiplied by the number of lines as it will be duplicated that many times. Where possible, get numerical and currency fields from the source object and use other connections for text-based fields.

The below video is based on PSA data but learnings can be applied to all product areas.

Additional Notes

For any feedback or requests for future Bite Size Analytics, post in the Reporting Chatter group.

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Knowledge:Bite Size Analytics: How to Build Simple Datasets