Large-scale data warehousing solutions combine conventional data warehousing used to support business intelligence (BI) with techniques used for so-called "big data" analytics. A conventional data warehousing solution typically involves copying data from transactional data stores into a relational database with a schema that's optimized for querying and building multidimensional models. Big Data processing solutions on the other hand, are used with large volumes of data in multiple formats, which is batch loaded or captured in real-time streams and stored in a data lake from which distributed processing engines like Apache Spark are used to process it.
Reference
https://learn.microsoft.com/bs-latn-ba/training/modules/examine-components-of-modern-data- warehouse/1-introduction