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Tâm sự của Microsoft cho các bạn làm dữ liệu về công cụ mới Fabric

Xem như lời nói chuyện của Microsoft về giải pháp Fabric sẽ giúp cho bạn đỡ nhọc nhằn hơn trong việc quản lý dữ liệu. Microsoft Fabric là một bộ công cụ low-code và hướng tới no-code để xây dựng, quản trị và phát triển nền tảng dữ liệu của doanh nghiệp

Microsoft Fabric’s unified management and governance make it easier for data professionals to work together on data projects. Fabric removes data silos and the need for access to multiple systems, enhancing collaboration between data professionals.

Traditionally, the data engineer and data analyst role separation meant that there was an extra conversation that needed to happen to ensure that the engineer curated a perfect data model to help the analyst display data in an effective and insightful way for the business.

With Fabric, data professionals work together in the same SaaS product to better understand and identify needs of each other and the business. Further, data analysts now have greater context and ability to transform data further upstream with data factory.

Whether you’re a data engineer looking to simplify your data model curation or expanding your knowledge with data science techniques, Fabric provides a complete experience to serve your organization.

For data analysts, who may have had to perform extensive downstream data transformations before creating Power BI reports, you can now see the lineage and connect with data more directly with DirectLake mode.

Data scientists now have an easier way to integrate native data science techniques and then use Power BI’s interactive reporting to provide data-informed insights in a new way.

Because Fabric is a SaaS platform, it allows you to quickly and easily provision and run any type of workload or job without needing pre-approval or planning. This means that you can scale resources up or down as needed, and be more agile and responsive to changing business needs.

Lastly, Fabric is bringing the low-to-no-code concept, functionality, and approach that has successfully empowered many users on the Power Platform to its own SaaS offering. While it maintains scale and integrity for data science, data warehousing, data ingestion and prep, and analytics, it also offers many ways to visually represent code that previously blocked many from going further.