Exploring modern data warehouse analytics

In the age of data mining, most organizations have multiple data stores, often with different structures and varying formats because we may need to collect data from multiple resources. They often have live incoming streams of data, such as sensor data in the case of IoT solutions and it can be expensive to analyze this data. There is often a wealth of useful information available outside the organization. This information could be combined with local data to add insights and enrich understanding. By combining local data with useful external information, it’s often possible to gain insights into the data that weren’t previously possible. The process of combining all of the local data sources is known as data warehousing. The process of analyzing streaming data and data from the internet is known as big data analytics. Azure Synapse Analytics combines data warehousing with big data analytics.

In this section, we will explore...