Components of Microsoft Fabric

Introduction

Microsoft Fabric offers a comprehensive suite of analytics experiences that can seamlessly work together. Each experience has been carefully designed to be tailored to specific personas and tasks, providing leading capabilities in various categories to meet your end-to-end analytical needs. Fabric provides a menu of experiences when you click on the ‘Microsoft Fabric’ persona present on the left pane down corner as shown in the image below.

Data Engineering

The Data Engineering experience in Microsoft Fabric offers a top-notch Spark platform with excellent capabilities. This empowers data engineers not only to perform large-scale data transformations but also to democratize data through the lakehouse. Data engineering enables users to design, build and maintain infrastructures and systems which can help them process and analyse huge amount of data. The Microsoft Fabric Spark can integrate Data Factory, allowing scheduling and orchestration of notebooks and spark jobs.

Data Factory

It helps users with a data integration to ingest, ETL data from various set of data sources like databases, data warehouses, lakehouse, streaming data etc. Azure Data Factory combines the simplicity of Power Query with the scalability and power of Azure Data Factory. With data factory in Microsoft fabric, you can utilize the fast copy capability on both data flows and data pipelines and move across datastores quickly. It supports over 200 native connectors to connect to data sources both on-premises and in the cloud.

• With Dataflows you can leverage more than 300 transformations in the dataflows designer and transform data easier and with more flexibility than any other tool including AI-based data transformations.
• Data pipelines lets you leverage the rich data orchestration capabilities to compose flexible data workflows that meet your enterprise needs.

Data Science

The Data Science experience in Microsoft Fabric enables you to seamlessly build, deploy, and operationalize machine learning models. There are wide range of activities which the users can complete across the entire datascience process, right from exploration, cleansing, modeling up until predictive insights to BI reports. It integrates with AzureML, providing built-in experiment tracking and model registry. Data scientists can enrich organizational data with predictions, allowing business analysts to integrate these predictions into their BI reports. This shift from descriptive to predictive insights enhances decision-making.

Data Warehouse

The Data Warehouse experience in Microsoft Fabric offers a unified product that will help users with SAAS based data, analytics, and AI Platform oriented workspace. It also can handle industry leading SQL performance and scalability for bigger volumes of data by leveraging OneLake as the central storage. It allows independent scaling of compute and storage components, providing flexibility. Additionally, it natively stores data in the open Delta Lake format. Microsoft fabric’s Data warehouse has the following advantages at the high level

• Lake centric SaaS experience
• Cross database querying from virtual warehouse
• Autonomous workload management
• Isolation between storage and compute
• Ingest. Load and transform at scale

Real-Time Analytics

Microsoft Fabric enables real-time analytics by collecting observational data from various sources including IoT, apps, biometrics etc. These are high volume data usually in sem-structured JSON format. This experience has items like EventStream, KQL database, KQL Queryset which when utilized can help in reducing complexity and can simplify data integration. The access to data insights can happen within seconds of provisioning with the help features inbuilt like automatic data streaming, indexing, on-demand query generation, visualizations etc.

Integration with other experiences

Summary

Understanding the components of Microsoft fabric is important to get into depths of Microsoft Fabric which we are going to see in upcoming articles as part of this Fabric series. The upcoming articles will focus on all features and components of Microsoft fabric from multiple perspectives.