SAP Certified Associate — Data Analyst, SAP Analytics Cloud

What it covers

• Data modelling in SAC — models, dimensions, measures, hierarchies, currency handling.
• Stories and visualisation — building analytic content that answers a question rather than displaying a table.
• Connectivity — live and import connections to SAP and non-SAP sources.
• Planning — SAC's planning capability, versions, data actions.
• Administration — users, roles, content lifecycle.

Why both certifications in the same week

C_ABAPD on 16 April, C_SAC on 17 April 2026 — deliberately back to back, because they are the two halves of the same argument I have been making about my own career.

The ABAP certification says I can build what happens inside the system. The analytics certification says I can carry that data through to the point where somebody makes a decision with it. Most people in the SAP ecosystem specialise in one side. The value I try to offer is that a requirement can be handed to one person and come back as a working end-to-end answer.

What it added to the warehouse work

My data experience before this was Microsoft-shaped: SQL Server, SSIS, SSAS, Power BI. SAC is the SAP-native answer to the same problem, and knowing both means I can give a client an honest recommendation rather than the one I happen to know.

The short version of that recommendation: SAC when the data and the audience are both inside the SAP landscape, particularly with live connections to S/4HANA where you avoid replicating data at all. Power BI when the reporting spans well beyond SAP and the organisation already lives in the Microsoft stack.

The planning capability was the part I knew least about going in, and the part I found most interesting — it is the one thing in the analytics space that writes back rather than only reading.

To expand: a fuller SAC vs. Power BI comparison for SAP landscapes.