Microsoft Fabric Introduction
Microsoft Fabric is an all-in-one analytics solution for enterprises that covers everything from data movement to data science, Real-Time Analytics, and business intelligence. It offers a comprehensive suite of services, including data lake, data engineering, and data integration, all in one place.
Why Fabric
To bridge the gap between data and intelligence Microsoft presents, Microsoft Fabric. It is an open and governed human-centered solution that integrates all your data and tools.
- With Microsoft Fabric data engineers can visually integrate data from multiple sources.
- Data scientists can model and transform data.
- Data analysts can bring together more datasets and enable deeper insights.
- Data stewards can govern data and eliminate sprawl.
- Business users can work directly with data uncovering and shaping the intelligence they need to make critical decisions that drive innovation.
By breaking down every barrier and equipping every data professional with access to every tool your organization creates intelligence faster. - AI-powered features like Copilot, help your teams connect data sources, build machine learning models, and visualize results at the speed of thought.
- Now your teams can all work seamlessly from a single data foundation in Microsoft Fabric, with consistency across all your analytics workloads.
There are 6 major components in Azure Fabric.
Data Factory provides more than 90+ connectors to ingest data to cloud and on-premises data sources using Data Pipeline which is based on Azure Synapse Analytics Pipelines, also provides 300+ connectors in the Dataflows for data transformation which are based on Power Query.
Data Engineering experience provides a world-class Spark platform with great authoring experiences, enabling data engineers to perform large-scale data transformation and democratize data through the lakehouse. Microsoft Fabric Spark’s integration with Data Factory enables notebooks and spark jobs to be scheduled and orchestrated.
Data Warehouse experience provides a powerful compute engine based on a serverless SQL relational engine with industry-leading SQL performance and scale. It fully separates compute from storage, enabling independent scaling of both components. Additionally, it natively stores data in the open Delta Lake format.
Data Science experience provides an end-to-end workflow for data scientists to build sophisticated AI models, collaborate, deploy, and manage machine learning models seamlessly within Fabric.
Real-Time Analytics provides a complete streaming solution like the Internet of Things(IoT) data, logs, telemetry, and many more inside Microsoft Fabric based on Kusto. Including a KQL Database engine and a capability called eventstream. Which can be used to ingest streaming data.
Power BI is the world’s leading Business Intelligence platform. It ensures that business owners can access all the data in Fabric quickly and intuitively to make better decisions with data. Microsoft Fabric introduces a new Power BI mode called “See-through” mode, which allows Power BI to use the data that is stored locally in OneLake.
OneLake
OneLake is the “OneDrive for data” built on top of ADLS (Azure Data Lake Storage) Gen2. It provides a single SaaS experience and a tenant-wide store for data that serves both professional and citizen developers.
- OneLake is core to Fabric’s lake-centric approach.
- The data lake is the foundation on which all the Fabric services are built.
- The OneLake SaaS experience simplifies the experiences, eliminating the need for users to understand any infrastructure concepts such as resource groups, RBAC (Role-Based Access Control), Azure Resource Manager, redundancy, or regions. Additionally, it doesn’t require the user to even have an Azure account.
- OneLake eliminates today’s pervasive and chaotic data silos, which individual developers create when they provision and configure their own isolated storage accounts.
I have tried my best to explain Microsoft Fabric in Nutshell. Let’s discuss OneLake in detail in an upcoming post.
Feedback is always appreciated. cheers 🥂
Reference- Microsoft
