There is a huge demand to get more insight from the data using AI and advanced analytics.
See how to use visuals in Power BI to get more insight from your data and how to use embedded AI features in Power BI.
Power BI is about helping our customers embrace a data culture, where every employee can make better decisions based on data. The growth of Power BI has been staggering – customers ingest more than 20PB of data to Power BI every month, lighting up over 30M reports and dashboards, and the Power BI service processes over 12M queries per hour.
Gartner named Microsoft a Leader in the Magic Quadrant for Analytics and BI Platforms for 12 consecutive years.
Power BI has led the way in infusing AI with BI through capabilities like Quick Insights which help unearth trends in data and Q&A which enable business users to get answers by simply asking questions.
Microsoft recently announced the general availability of Azure Cognitive Services and Azure ML dataflows integration, to provide analysts with a toolkit of powerful AI functions:
● Azure Cognitive Services are sophisticated pre-trained machine learning models for intelligent applications. Analysts can use these models to extract insights from images by detecting objects. Text fields like customer feedback can be analyzed for positive and negative sentiment as well as have key phrases extracted. All these AI enrichments can be easily consumed by end users through interactive Power BI reports.
● Azure Machine Learning is a powerful platform where data scientists can develop machine learning models. These models can now easily be shared and used by analysts. Power BI automatically discovers which models an analyst has permissions to and provides an intuitive point and click user interface to invoke them. Analysts can now easily collaborate with data scientists as well as visualize and use insights from the model in their reports.
Learn more about the general availability for cognitive services, Azure ML and the AI workload in Power BI Premium.
Some exciting new capabilities that will be available soon:
● Two new AI visuals—Distribution Changes analyzes what makes a distribution look different, and the Decomposition Tree enables users to drill into any dimension to understand what is driving a key metric.
● Expanding Power BI’s vision and text analytics capabilities and adding entity detection and text and handwriting recognition, enabling one-click transformations for insights on unstructured data.
● For enterprises that need custom lifecycle management or further tuning, models created in Power BI can be exported to Azure ML
● Extending Power BI’s natural language capabilities. The new updates include the ability to train Q&A so it understands and adapts to company-specific language like synonyms, phrasings, or specific domains, and the ability for report authors to see every natural-language question asked so they can adjust how Power BI responds.
Template apps are integrated packages of pre-built Power BI dashboards and reports, configured to connect to specific data sources. With them, Microsoft partners can quickly provide analytics for the apps and services they provide. Partners can also manage the Template Apps development lifecycle, from dev to marketplace to updates. With template apps, users can immediately begin exploring, learning, and acting on key data with off-the-shelf apps. Today, Template Apps become generally available. Users can find and install template apps on AppSource.
Embedded analytics keeps evolving
With Power BI embedded analytics, you can extend the value of Power BI Premium and Power BI Pro. Embed analytics in internal websites, applications, and portals to empower your organization to make data-driven decisions. Here is some of the exciting news we are sharing today:
● Service principals with Power BI are now generally available. With service principal, application developers can authenticate an external application to embed Power BI content or manage and automate Power BI operations with Power BI using an app-only token. Read the full article.
● Use the AI-based ‘Key Influencers’ visualization in your application to allow end users to see which factors affect the metric being analyzed and contrast the relative importance of these factors.
