Power BI Datasets are Semantic Data Models
Business intelligence (BI) has allowed organizations to move from intuition to using data and creating information, knowledge, and intelligence. One of BI’s primary and key components is data analysis, which involves collecting data from multiple sources such as databases, spreadsheets, and cloud-based systems and processing and analyzing it using statistical, mathematical and ML techniques to extract meaningful insights. BI can analyze external data sources, such as social media trends, news, and economic indicators, to provide a comprehensive view of the market landscape.
A Power BI dataset is a semantic data model primarily comprised of data source queries, relationship between fact and dimension tables, and measure calculations. Power Bi has a number of offerings. Power BI desktop is one of the ways users can connect to other services such as Azure Databricks clusters and SQL warehouses. From here, users can publish their Power BI reports. Power BI offers a cloud-based service, called Power BI Service, for creating and sharing dashboards and reports and collaborating on them in real time. There is also a Power BI application programming interface (API) that can also be used to create reports.
Naturally, Power BI benefits from seamless integrations with other Azure cloud services and Microsoft software. One example is the ability to create a Power BI dataset in Azure Synapse Studio.
Power BI can also integrate with some on-premises data sources. One example of this is its ability to integrate with an on-premises deployment of SQL Server Analysis Services. Once the user is able to connect the data source, he or she will be able to visualize the data in Power BI.
References
Deckler, Greg, Brett Powell, and Leon Gordon. Mastering Microsoft Power BI: Expert techniques to create interactive insights for effective data analytics and business intelligence. Packt Publishing Ltd, 2022.
Salgado, Bárbara Alexandra Ferreira. "{Unlocking Performance Potential: Power BI Implementation and its Transformative Impact on Proef's Business Intelligence." (2023).
Rosandic, Josip. "REAL-TIME STREAMING DATA MANAGEMENT, PROCESSING, ANALYSIS AND VISUALISATION."
Shah, Syed Tahoor Ullah. "Optimizing Data Warehouse Implementation on Azure: A Comparative Analysis of Efficient Data Warehousing Strategies on Azure." (2024).
MO, Cuddley. "Introduction to Microsoft Power BI." (2016).
