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Microsoft Power BI (business intelligence) suite has powerful tools and services that enable businesses to have a deeper understanding of business data with strong data analytics and visualizations. With Power BI, data no longer sits in the large databases never to be used. Power BI integrated solutions encompass diverse data sources and visualization types.
Power BI supports a wide range of data sources such as Flat Files, Databases, OData Feed, Blank Query, AZURE, Cloud platform, online services, and other data sources such as Hadoop, Exchange, or Active directory.
Power BI has a powerful natural language processing and recognition engine named Cortana. Customers can analyze their data by asking questions in natural language with no special code or syntax required. Customers navigate their data by just asking questions.
Power BI Quick Insights are the most valuable feature; the end user can search datasets or dashboard tiles for interesting insights automatically within seconds. Quick Insights are used for outliers, correlations, trends, change points in trends, and major factors right from the dashboard tiles.
One of the most valuable features of Power BI supported data sources is applying any sort of transformation to data source objects. When changing a column’s data type, one or more multiple M expressions are created. These M expressions are automatically copied to M documents and stored within the Power BI desktop file as queries. M is a functional programming language like F#, and it is important for Power BI developers to become familiar with analyzing, writing and enhancing the Mcode that supports their queries.
Power BI allows users to access real-time datasets and provides immediate visibility into business processes and events as the data is created. Power BI data modeling engine reflects the latest SQL Server Analysis Services (SSAS) features, including the enhanced Direct Query mode for SSAS 2016, it becomes feasible to design Direct Query models in the Power BI Desktop and thus avoid the scalability limitations and scheduled refresh requirements of import-based models.
This feature is the heart of Business Intelligence. Power BI supports rich filtering capabilities across the query components, data model components & visualization components. As many scenarios use the Query editor and M functions to filter at the Query Level. It reduces the workload of Import and Direct Query Data Models. Query Editor GUI can be used to configure filter conditions and M Function filter conditions.
Power BI integrates multiple queries using Power BI merges and append functions. Using this feature users can retrieve and consolidate files from multiple network locations or integrate data from more than one source. Reports can be implemented efficiently and securely. SQL and ETL developers are familiar with join types and data transformation patterns and the same will be achieved with the M Language.
Power BI includes a Data Modeling Feature, and Data Analysis Expressions (DAX) that can be used to support Many-Many modeling relationships for multiple business requirements. Power BI data models contain bidirectional relationships, as well as DAX measures, which contain relationship filter logic through new CROSSFILTER () Function.
Power BI provides advanced analytics including forecasting, clustering and quick insights of historical data. Many valuable mathematical and statistical analysis are possible by embedding the logic of these methods/functions into DAX measures. This analyses can be used to generate new insights and provide the maximum level of validations and confidence in business decisions.
Power BI Reports are available for IOS, Android and Windows devices. Wherever users access the internet, the user will be able to view reports instantly.
Power BI will allow the user to extract the data from all supported data sources. Once connected to all required data sources, the user consolidates it into a Dataset and can begin building their visual reports.
Power BI allows the user to share the data visualizations with others.
Using drag-and-drop functionality, end-users will be able to create their own ad-hoc reports in minutes.
A feature that allows users to go deeper into more specific data or information being analyzed. The user immediately drills into the visualization and can look at the data that comprises it.
A feature that allows the user to schedule their data refresh to hourly or daily or any specific time.