Learning Microsoft Azure

Chapter 7. Big Data, Reporting, and Analytics Services in Azure

From the global economic crisis caused by the pandemic to the rapid adoption of AI tools like ChatGPT, businesses have never been more reliant on data and analytics to compete and stay ahead. To make this happen, legacy silos between data analysts versus scientists or archival versus streaming data must be torn down in favor of an interoperable, governed platform for analytics and reporting. Done well, analytics means getting the right information at the right time to the right people—to do this, the right architecture matters.

George Mount, Founder of Stringfest Analytics, Microsoft MVP, and author of Advancing into Analytics (O’Reilly Media)

In Chapter 6, we learned about how artificial intelligence (AI), machine learning (ML), and Azure AI Services can be used to build intelligent applications. We explored using these AI, OpenAI, and cognitive services to collect data to develop applications and enterprise-level solutions.

In this chapter, we’ll shift gears and dive deeper into how to use and visualize data collected using cloud services to analyze and understand it better.

Big Data, Reporting, and Analytics Services in Azure

Organizations constantly collect, process, and use data in applications on all sorts of devices. Looking at this data at scale through extensive data analysis turns datasets into actionable information. This level of analysis is referred to as big data analytics, and it’s the foundation ...