Overview of Microsoft Fabric and Understanding Its Different Concepts

As data volume and complexity grow, organizations across every industry have opportunities to harness data to digitally transform themselves by exploiting its power and gaining competitive advantages. However, these organizations have to manage and stitch together different specialized and disconnected products to build their end-to-end analytics system. As a result, they end up incurring high integration costs when ensuring these products function together as one analytics system. This often results in delays in obtaining insights to the extent that the information is no longer relevant.

This chapter will introduce you to Microsoft Fabric, its core capabilities, and how it addresses the challenges of modern data analytics.

Here is what will be covered in this chapter:

• Introduction to Microsoft Fabric
• Reviewing the core capabilities of Microsoft Fabric
• An understanding of Microsoft Fabric as...

Introduction to Microsoft Fabric

Microsoft Fabric is an end-to-end, all-in-one unified analytics platform that brings together all the data and analytics tools that organizations need. As a single, unified platform for data management, data lakes, data integration, data engineering, data warehousing, data science, real-time analytics, and business intelligence, it has been designed from the ground up to help organizations simplify their analytics workloads, reduce costs, and reduce the time taken to obtain insights in this era of AI. Microsoft Fabric is built on Azure, and it leverages the power of Azure’s computing, storage, reliability, security and governance, scale, performance, and networking services.

Reviewing the core capabilities of Microsoft Fabric

Microsoft Fabric is designed for the age of AI and is delivered as a single Software-as-a-Service (SaaS) product that provides auto-integration, auto-optimization, common architecture, central security and governance, a unified business model, and Office-like experiences across all workloads.

There are four core pillars of Microsoft Fabric:

Figure 1.1 – Microsoft Fabric’s core capability pillars

Let’s review each pillar in detail in the next subsections:

• Complete Analytics Platform
• Lake-centric and open
• Empower Every Business User
• AI Powered

Complete analytics platform

While there is a standard pattern (for data warehouses or lakehouses) for typical analytics systems with well-defined components (such as ingestion, processing, and consumption), each of the components might need a different array of capabilities and might be well-served by a different...

Unified business model with universal compute capacity

As discussed earlier, when you build a data analytics system today, you typically combine multiple products—often from multiple vendors—to build different components in a single analytics system. This means computing capacity is provisioned and charged for the multiple components (for the multiple products used) in the system, such as data integration, data engineering, data warehousing, and business intelligence. This not only burdens you with managing the overall cost but also, when one of the components is idle, its capacity cannot be used by another component. Thus, this can cause significant wastage and overall increased Total Cost of Ownership (TCO).

Microsoft Fabric simplifies this whole experience of purchasing and managing computing resources with its universal compute capacity, which uses capacity units (CUs), as shown in Figure 1.9. Universal capacities provide the computing resources for all the engines...

Summary

In this chapter, you have learned about Microsoft Fabric as a unified platform. It provides all the natively integrated capabilities with which to design and build end-to-end analytics systems, all the way from Data Factory (for data ingestion) and Data Engineering (for data transformation) to Data Science, Data Warehouse, Real-Time Analytics, and Power BI for data visualization.

You also learned about core capabilities, such as OneLake and OneCopy, and how they break data silos and remove the need for data redundancy across different systems by using data storage format standardization (the open source Delta Lake format), which is used by all Fabric engines, making the platform open at every layer and able to avoid vendor lock-ins. You learned about shortcuts and how they let you create data virtualization layers for all your enterprise data (with multi-cloud support), providing access without the need for data movement and copying.

Finally, you learned about how the...