High Scale Patterns
In the previous chapter, we learned how to optimize DAX expressions. So far, we have covered all the advice on optimizing different layers of a Power BI solution, from the semantic model layer to report design. In this chapter, we will take a step back and revisit architectural concepts and related features that help deal with very high data volumes.
The amount of data that organizations collect and need to analyze is increasing all the time. With the progression of streaming data such as the Internet of Things (IoT) and predictive analytics, certain industries, such as energy and resources, are collecting more data than ever before. It is common for a modern mine or gas plant to have tens of thousands of sensors, each generating many data points at a granularity much higher than a second.
Even with Power BI’s data compression technology, it isn’t always possible to load and store massive amounts of data in an Import mode model in a reasonable...
