A data platform within Azure can be an expensive piece of software. Expensive doesn’t always mean that it isn’t necessary, but to make a decision on how you spent your money the right way it is good to know what is causing costs and which process it facilitates.

When you are loading data within Azure using Synapse Analytics you have multiple options; Integration Pipelines, Mapping dataflows and Notebooks within Spark. With the use of the Azure Cost monitor you can get an overview of the costs that you are making on resource-level, but you won’t have insights on a more granular level.

Senior management asks you, “How much does it cost to load data from source x into our datalake?” or “We are exceeding our budget for the data platform, why and how did this happen?”. When using Azure Cost monitor it is impossible to give a accurate answer.

Within this session I show you how you can deliver fine grained insights in your costs, allowing you to give accurate answers to the questions asked!

Recommended knowledge:
- Data Engineering with Azure Synapse Analytics Workspace or Azure Data Factory
- Knowledge of building a Data platform within Azure
- Basic knowledge of SQL

Target audience:
- BI Developers/Data Engineers
- Data Architects
- Cost owners