UNIFIED BUSINESS INTELLIGENCE IN THE MICROSOFT FABRIC ENVIRONMENT
Data has become the strategic asset used to transform businesses to uncover new insights. Business Intelligence (BI) has been helping organizations across industries uncover insights from their data and turn them into actionable strategies. However, the world of data and BI is rapidly evolving in ways that are transforming the industry and motivating enterprises to consider new approaches of gaining insights. In this paper, Microsoft Fabric, as an innovative and holistic data analysis platform that integrates advanced business intelligence tools and enable organizations to transform big data into strategic insights, is presented. Microsoft Fabric is a cloud-based platform that provides a unified environment for data management and analytics, including data engineering, data science, data warehouse, real-time intelligence, business intelligence and artificial intelligence. To demonstrate effectiveness and capabilities of Microsoft Fabric platform for end-to-end analytics, the complete cloud-based BI solution was designed and deployed. The solution is based on a single, unified, logical data lake capable to processes large volumes of data from various sources. Several real-world datasets were integrated via Data Factory pipelines into the lake-centric Synapse data warehouse. To equip business users with actionable insights, various dashboards, reports, and machine learning models are designed and deployed in cloud for collaborative analytics and decision making. By employing such analytical platform and solution, organizations can quickly adapt to changing market conditions, increase productivity, and develop strategies based on deep insights, which ultimately gives them competitive advantage.
Authors
- Andrijana Gaborović (ORCID: https://orcid.org/0000-0002-3465-6150)
- Nenad Stefanović (ORCID: https://orcid.org/0000-0002-0339-3474)
- Jelena Plašić (ORCID: https://orcid.org/0000-0003-0404-6682)
Publication Details
- Published
- 2025-01-01
- DOI
- https://doi.org/10.46793/ebm24.407p
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00