Using insights generated from company data is essential when making business decisions. Having reliable data enables a company to make strategic decisions to optimize operations, track overall company performance, and observe valuable trends.
Power BI has proven to be a handy tool for businesses and provides many benefits, such as allowing the easy creation of intuitive visualizations, dashboards, and applications.
This article will discuss the benefits of Power BI in detail and how they can be most helpful to your company and you as a data analyst.
What benefits does power BI bring to your business?
One of the many features that attract data analysts and other users is Power BI's powerful and interactive dashboards.
With its easy-to-use, drag-and-drop interface, it allows for easily customizable visualizations. Furthermore, it offers several visualizations provided by the community of users who create and share visuals.
In addition, there are visuals available on Microsoft AppSource or the default visuals offered by Power BI.
It has powerful dashboards and data visualization
Dashboarding and data visualization plays a very vital role in the storytelling part of data analysis and business intelligence. Presenting goals, relevant KPIs, and the context in a way that's easy to understand by the target audience is essential, and visuals help with that.
Achieving this is easy as Power BI offers dashboards that give multi-perspective views of data and make it easier to draw insights.
Power BI dashboards offer the option to stream and regularly update data and schedule a refresh, which makes for straightforward analysis of real-time data.
Real-time streaming is consumed and visualized with the Power BI's REST API or PubNub. This feature removes the stress of manually refreshing data in your dashboard or reports.
It allows for collaboration
Power BI also supports collaboration and allows you to easily share your dashboards and reports with others within or outside the organization with the help of Power BI workspaces. You control who gets access to the reports and give permission to edit, make a copy, or share with coworkers.
Collaboration support allows teams to work on analytical reports and easily exchange information independently.
It uses data analysis expressions (DAX) language
Another feature loved by Power BI users is DAX, a language that gives extra formulas and functionalities similar to Excel, making reporting easier and more powerful. It also allows for custom calculations for calculated fields, providing functions that work with relational data and carry out dynamic aggregation.
These extra functions let you extract useful information from your data and improve your data model compared to the regular drag-and-drop. DAX also works as a query language, which proves useful in cases where you wish to extract a subset of data so you can take a closer look at it. It can also be helpful when you're evaluating a model for performance.
DAX offers over 250 handy functions such as CALCULATE, RELATED, AVERAGE, etc. These functions are pretty similar to Excel but with a bit of a difference; instead of working with cells, DAX works with tables and columns.
When carrying out data analysis, performing robust testing on measures before they're included in a model, etc., DAX helps you take things a step further. However, DAX doesn't have a functional language background, which may make it difficult for beginners and even some experts to understand at first.
It utilizes artificial intelligence
Power BI offers users access to artificial intelligence services such as image recognition, natural language processing, text analytics, etc. It also supports building machine learning models with the help of AutoML.
You can create a dataflow entity by using available data sources. Power BI can then suggest the field you want to predict and propose the type of ML models that you can build.
In the Power Query editor, AI Insights offers pre-trained machine learning models that may come in handy when carrying out data preparation.
Power BI also supports integration with Azure Cognitive Services directly as a premium feature. The services supported are sentiment analysis, key phrase extraction, language detection, and image tagging.
It also supports the Cortana or Bot Framework, which allows for the provisioning of results for the verbal data query given using natural language.
Finally, Power BI also offers four powerful AI visualizations, helpful in delving deeper into data, generating insights, and identifying trends that may be difficult to observe.
These visualizations include:
- Q&A visualization (capable of understanding natural language questions)
- Key influencers visualization (for identification of factors driving a KPI)
- Decomposition tree visualization (for visualization of data across multiple dimensions)
- Distribution change bar chart (for analysis of distribution in a subset of data)
Power BI is secure
Power BI offers four layers of security:
- Privacy levels in Power Query
- Row-level security (RLS) in Power BI
- Office 365 sensitivity label
- Power BI workspace security
Each covers a specific area that we'll briefly discuss.
Privacy levels in Power Query
Allow only authorized users to view sensitive data. Each level is defined by the level of privacy: private, organizational, and public. These levels prevent the leakage of sensitive data.
Row-level security in Power BI
Restricts data at the row level within a report. This provides filters that restrict access to rows in a database. Under this, there are also two main types of RLS: Static RLS and Dynamic RLS.
The sensitivity label in Office 365
Helpful when classifying content without using protection settings. This allows for certain parts of content to remain restricted. It also ensures sensitive data is kept hidden and protected when saved outside Power BI.
Power BI workspace security
Controls access to reports and datasets that are published by implementing permissions and roles. Workspace has four roles: admin, member, contributor, and viewer.
Some security best practices while using Power BI include:
- Using Azure AD Conditional Access to turn on multifactor authentication (MFA)
- Restriction of user access from locations that aren't trusted
- Being selective about permissions you grant in workspaces
All these ensure your dashboards, reports, and applications are shared and published safely within or outside the organization.
It allows for integration of various data sources
Finally, another benefit of Power BI is the seamless integration of other data from different sources and its support for different types.
This integration includes Microsoft applications such as:
- Azure (Azure Data Warehouse)
- Office 365
- Dynamics 365
However, integration with non-Microsoft products such as Dropbox, Google Analytics, and Salesforce is also easy.
Power BI also integrates common file data sources such as Excel spreadsheets, CSV files, and data located on-premises such as SQL databases.
Lastly, it also supports database sources like Oracle database and Snowflake. Furthermore, it easily supports connecting multiple data sources and adding new sources with the help of the Power Query editor.
When creating a common data model or combining data from different sources, they are all stored in a centralized location, making it easily accessible.
Power BI comes with other significant benefits such as R integrations, interactive visualizations, regular monthly updates, no constraints in terms of memory and speed, and others.
The platform continues to grow in popularity among data analysts. Users enjoy the ease of putting together and sharing reports, dashboards, and applications from various data sources.