GPPB Natural Language PowerBI
- 1. Organized Globally, Held Locally GLOBAL POWER PLATFORM BOOTCAMP GLOBAL POWER PLATFORM BOOTCAMP Organized Globally, Held Locally @GPPBootcampBLR #GPPBootcampBLR #GlobalPowerPlatformBootcamp
- 2. Mitul Rana Let’s integrate natural language in your Power BI reports and Ask a question on your data. @mitul_rana Platform Specialist, Trelleborg Samik Roy @roy_samik Senior Developer, Born in the Cloud @GPPBootcampBLR #GPPBootcampBLR #GlobalPowerPlatformBootcamp
- 4. Agenda • Investment areas • Personas and capabilities Overview of AI in Power BI • AI visualizations • Natural language capabilities End User Insights • Automated ML • Cognitive services Analyst toolkit
- 5. AI in Power BI Sentiment Analysis Key Phrase Extraction Create ML models Explore predictionsPython Integration R IntegrationExtend with Azure ML Integrate into reports AI Visualizations Natural Language
- 6. AI in Power BI Sentiment Analysis Key Phrase Extraction Create ML models Explore predictionsPython Integration R IntegrationExtend with Azure ML Integrate into reports AI Visualizations Natural Language
- 8. AI in Power BI Sentiment Analysis Key Phrase Extraction Create ML models Explore predictionsPython Integration R IntegrationExtend with Azure ML Integrate into reports AI Visualizations Natural Language
- 9. AI in Power BI Sentiment Analysis Key Phrase Extraction Create ML models Explore predictionsPython Integration R IntegrationExtend with Azure ML Integrate into reports AI Visualizations Natural Language
- 11. Key Takeaways – AutoML POWER BI + AUTOMATED ML ENABLES YOU TO: AUTOMATE MOST OF THE STANDARD MACHINE LEARNING PRACTICES IN A NON-INTRUSIVE YET TRANSPARENT WAY AI IN POWER BI IS NOT ONLY ABOUT ACHIEVING GREAT ACCURACY BUT ABOUT EASY TRANSLATING THIS ACCURACY TO BUSINESS IMPACT
- 12. Key Takeaways – AutoML Automated ML in Power BI Automated ML in Azure Designed for the business analyst/BI professional Designed for for the data scientist/data engineer Skillset required is Power Query and Power BI dataflows (OOB point and click functions, M code) Skillset required is Azure, Python and Jupyter notebooks ML model lives completely inside Power BI and can only be used by Power BI ML model lives in Azure and can be consumed as a webservice by lots of different applications (including Power BI) Requires Power BI Premium and utilizes capacity Requires an Azure subscription and utilizes Azure consumption
- 14. Key Takeaways – Cognitive Services Cognitive services in Power BI Cognitive services in Azure Designed for the business analyst/BI professional Designed for for the data scientist/data engineer Skillset required is Power Query and Power BI dataflows (OOB point and click functions, M code) Skillset required is Azure, coding language (C#, Java, Node.js, Python) Lives completely inside Power BI and can only be used by Power BI Live in Azure and can be consumed as a webservice by lots of different applications Require Power BI Premium and utilizes capacity Require an Azure subscription and utilizes Azure consumption
- 15. Session takeaways Power BI + AI enables: Findings insights seamlessly and interacting with data in a natural way using language Gives analysts the opportunity to enrich their data using AI and build their own machine learning model without writing any code Extension points for data scientists to plug in their Python/R scripts or to bring in machine learning models they created elsewhere
- 16. Call to Action • Try some of our quick start guides to get started with Automated ML, Cognitive Services and Azure ML on dataflows: • https://docs.microsoft.com/en-us/power- bi/service-machine-learning-automated • Download the latest Power BI Desktop to try AI Visuals • https://powerbi.microsoft.com/en-us/desktop/ • Get in touch with the team to talk to us about your use cases, pain points, roadmap feedback (seriously we love hearing from you ): • Mitul.rana@gmail.com • Samik.n.roy@gmail.com
- 17. Any Questions?