SQLBits 2024

Analytics Architectures on Microsoft Fabric

On this presentation we will see different analytics architectures, discuss the advantages and disadvantages of those and how Microsoft Fabric is a platform that we can rely on to implement those different architectures.
Data is the new oil, and analytics is the engine that drives value from it. However, the analytical workload has evolved over time, from simple reporting and dashboarding to complex machine learning and artificial intelligence. How can we keep up with the changing demands and challenges of data analytics? How can we leverage the latest technologies and innovations to transform our data into insights? In this presentation, we will explore the evolution of analytical workload and how Microsoft Fabric can help us achieve our data goals.
We will cover:
The history and trends of analytical workload, from descriptive analytics to predictive analytics to prescriptive analytics, and how they differ in terms of data types, processing methods, and use cases.
The challenges and opportunities of analytical workload, such as data volume, variety, velocity, veracity, value, etc., and how they affect the performance, scalability, reliability, and security of our data platforms.
The features and benefits of Microsoft Fabric, an end-to-end analytics platform that integrates technologies like Azure Data Factory, Azure Synapse Analytics, Azure OpenAI Service, Power BI, etc., into a single unified product that provides all the capabilities required for building modern data platforms that support various analytics workloads.
The demo scenarios and examples that showcase the capabilities and performance of Microsoft Fabric in action, such as data ingestion, etc.