Microsoft Fabric offers a central data warehouse based on an enterprise-class distributed processing engine, providing industry-leading scale-out performance while eliminating the need for configuration and management. Through an easy-to-use SaaS environment that’s tightly integrated with Power BI for easy analysis and reporting, the Warehouse in Microsoft Fabric combines the data lake and data warehouse environments to significantly simplify organizations’ investment in their analytical resources.
Business analytics is a process that demands skills in acquiring, preparing, and analyzing data, creating business semantics, applying machine learning models, and preparing BI reports. It requires the collaboration of IT professionals, data engineers, business analysts, and data scientists across the organization. When data is shared, it needs to be secured and properly managed. Data Warehouse facilitates this through the following key features.
200 +
successful implementations500 +
satisfied customers1000 +
developed analyses10000 +
trained customersData Warehouse provides flexibility and easy scalability, allowing organizations to adjust resources to current analytical needs.
Microsoft Fabric service offers resource management flexibility, enabling dynamic adjustment of compute power and memory according to project needs, optimizing costs and performance.
Data Engineering in Microsoft Fabric guarantees a high level of data security and reliability in processing, using advanced access control mechanisms, ensuring full trust in analysis results.
The service seamlessly integrates with other Fabric services like Data Engineering, Real Time Analytics, and Power BI, making data analysis and advanced reporting easier.
With the rich set of tools in Data Engineering, advanced data transformation and cleansing operations can be performed, leading to more consistent and complete data in the analysis process.
Microsoft Fabric service allows easy data integration from different sources and supports various data formats, enabling organizations to use a full range of data for better and more comprehensive analysis.
