Among the freshest trends in the technology market, which are streamlining the work of corporations, managing data, and creating clever analytics, the integration of Generative Artificial Intelligence (GenAI) with Business Intelligence systems deserves special attention. Together, they form Generative BI (GenBI), a combination of technologies that use AI capabilities to improve data analysis decision-making processes and extract value from large sets of information. Through this Power BI – Generative AI combination, organizations can discover new insights and innovate their business strategies.
What is Generative BI?
“Generative BI” refers to using generative AI techniques, such as Large Language Models (LLMs) with business intelligence. This synergy allows for faster creation of more sophisticated models, data analysis automation, and actionable insights generation. With the development of GenBI, companies can move from manual descriptive and diagnostic analysis to predictive and prescriptive analysis, providing a competitive advantage. AI-powered business intelligence is also a tremendous help for non-technical employees interacting with data, who, thanks to chatbots, can gain knowledge from the data and obtain visualization of it by asking simple questions.
AI in Power BI can automatically detect trends and correlations in large data sets, giving users more profound insights into their activities. This capability is precious for organizations that want to optimize performance and make data-driven decisions. Combining Artificial Intelligence with Power BI improves the accuracy of data analysis and enables users to uncover hidden opportunities and potential risks.
Power BI – AI Features to make data clear for everyone
Among the capabilities of Power BI are AI features that enhance its functionality and make it a powerful data analysis tool. One of the key AI features in Power BI is using natural language processing (NLP) to interact with an organization’s data. This allows users to ask chat questions in ordinary human language and receive answers in visualized form – charts, graphs, or reports. A user can type “What were the sales results for last month?” and Power BI will generate a GenAI-based data visualization. Each report can still be modified accordingly – ask for it in the chat. What makes PowerBI even more streamlined is relevant suggestions or question prompts. This makes the work of non-technical users more efficient.
Other noteworthy Power BI AI features are sentiment analysis based on customer feedback, forecasting trends, correlations and tendencies based on data, or anomaly detection with explanation.
Power BI – AI Visuals to better understand your data
Power BI AI Visuals are a vital component of AI capabilities. These visualizations use artificial intelligence to provide a more impactful and interactive presentation of data. One example of an AI-based visualization is Key Influencers, which helps identify factors that affect various metrics in the data. These visualizations use ML algorithms to analyze the data and highlight the most critical variables, making it easier for users to understand the underlying influencers.
Another example is the decomposition tree, which allows users to decompose data into factors. This interactive visualization can help explore hierarchical data, providing detailed insights into how different variables affect the overall factor. This allows users to analyze the data, gain better and deeper insights, and share them.
Power BI – AI Insights to become data-driven
Power BI AI Insights provides users with advanced analysis capabilities to detect hidden patterns and trends in their data. One of the main functionalities is automated inference, where Power BI analyzes data and generates conclusions without manual intervention. It is possible to automatically detect anomalies in sales data and alert users to potential issues requiring attention.
In addition, Power BI offers advanced analysis tools such as sentiment analysis and predictive analysis. Sentiment analysis can assess customer sentiment based on textual data, such as reviews and social media posts, providing vital information about customer preferences. Predictive analysis uses historical data to forecast future trends and performance, helping companies make proactive decisions.
Power BI – AI Builder to create your own models
Power BI AI Builder is a tool that allows users to create and deploy their own AI models in the Power BI environment. It offers a user-friendly interface for building machine learning models without requiring extended programming knowledge. Users can create models for tasks such as form processing, object detection, and content classification and then integrate them into their Power BI reports and dashboards.
Companies can also use an AI builder to create a model that automatically generates information from invoices and populates the database, streamlining the payment process. Another use could be developing models to classify customer feedback, allowing companies to identify the most common problems and areas for improvement quickly.
AI for Business Intelligence – what are the real benefits?
AI for Business Intelligence is changing how organizations approach data analysis and decision-making. By integrating artificial intelligence into business intelligence systems, companies can automate routine tasks, uncover hidden insights, and predict future trends more accurately. Power BI generative AI illustrates this integration by enabling users to leverage advanced AI models in a familiar BI environment.
Power BI and AI combination improves data visualization and reporting and allows users to perform more advanced analyses without requiring in-depth data science knowledge. This seamless integration of artificial intelligence with business analytics tools such as Power BI enables more informed decision-making, enabling companies to maintain an edge in a competitive market.
