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Whether using interactive dashboards, consolidating key metrics, or rich reports to connect datasets, Power BI engages with business data and takes it from a broad range of disparate sources, enabling intelligent data-driven decisions.
Power BI is an intuitive tool for interacting with data and turning it into insights easily. Below are the top 6 reasons to use Power BI for business data analytics and self-service analytics.
Power BI makes it easy to bring your data together into one place with greater accessibility and visibility in your reporting efforts. The tool supports up to 120+ connectors that can load data from a wide range of highly used cloud-based sources such as DropBox, Google Analytics, OneDrive, and SalesForce, in addition to Excel spreadsheets, CSV files, and much more. You can load pre-built Power BI dashboards in seconds and get powerful data analysis within minutes. Users can also customize elements further.
Power BI’s data modeling engine is a high-performing columnar database. It compresses databases and ensures they load fully into memory for the best possible performance.
Excel starts to slow down when dealing with large models, while Power BI is optimized to handle over 100 million records without breaking a sweat. It loads millions of records into memory, enabling a quicker and better data analysis for end-users.
Power BI comes with a lot of pre-packed standard data visuals to convert into your interactive reports. However, for that extra touch, you can take free custom visuals created by developers and share them with the Power BI community to represent your data the way you want.
With custom visual files, there comes a wide range of rich and complex visuals to use, including bullet graphs, correlation plots, decision trees, heatmaps, sparklines, and much more. If you wish to represent your data in a specific manner, Power BI makes it very simple to create your own visuals.
Power BI’s core strength lies in its advanced data expertise. It achieves this through its support from R and Python. It is an open-source programming language primarily used by data miners and statisticians.
R and Python scripts apply complex graphical techniques and statistical computing for data manipulation, machine learning & statistical modeling. With the native support from R and Python scripts, users can present more advanced business analytics & predictive trends.
Advanced Excel users can easily dig deeper into their data and discover patterns quickly with Power BI. The embedded self-service query tool makes it easy to ingest, transform, integrate, and enrich business data. Hence, Power BI’s powerful toolset will be quite elementary for MS Excel users, leveraging existing organizational expertise.
Power BI gives you security within the same interface. There’s no need to use other tools to ensure you meet stringent compliance and regulatory standards. It contains Azure Active Directory (AAD) built-in for user authentication, leveraging Single Sign-On (SSO), along with your regular Power BI login credentials.
Business Intelligence is growing in popularity among businesses for getting better insights, interactive dashboards, and rich reporting for the users. In this post-pandemic world, it has become quite essential to leverage the power of these tools and services that help you prepare for a successful Power BI adoption and improve your data insights into the organization.
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