In a world of data-driven decisions, collecting the right data, identifying key areas, analyzing data and turning insights into actions can help to uncover hidden patterns and make strategic decisions. Power BI facilitates the delivery of great and interactive reports and visuals as business answers in a 360-degree perspective for our customers.
Power BI represents a collection of services, apps, and connectors that helps us to easily connect with our data, transform and create great visualizations to share with the others. We can connect to a variety of datasets, both on-premise and from the Cloud and easily create our own reports.
Quick insights – With an excellent visualization library, we can run quick insights over an entire dataset or on a specific dashboard, in order to get interactive visuals based on your data. Power BI engine uses advanced analytical algorithms to generate categories outliners, time series, correlations, and trends.
Power Query M formula language – A data-mashup language – can help to create procedural steps and build your own query using various elements and built-in functions.
Reports can be accessed from Desktop, Mobile or Cloud.
Just because Power BI offers many capabilities in just one click, it doesn’t mean we should ignore data preparation and transformation. Power Query is the right tool to clean up, add data transformation steps or access the underlying query code. A well–structured data model should include tables that are dimension-type or fact-type. We are using additional concepts related to star schema design to achieve the best results because an optimal design is part science and part art.
Creating a data model for Business analysis is important but the goal is different compared to a database (which runs transactional jobs). The new data model should be designed to reflect business actions and answer business questions.
Once the reports and dashboards are ready, we need to focus on data privacy. Power BI offers Privacy levels as an isolation level that defines the isolation degree between data sources. There are different privacy levels available: Private, Organizational and Public, just perfect to implement the right data visibility across different organization levels.
Report performance can be tested at the end of the project but should be prioritized as a first step in the data modeling phase. We take care of the data volume – displaying only what’s needed, limit visuals to what is necessary and optimize our model.