Unlocking Insight from Text Using Azure AI Language Studio
Proposed session for SQLBits 2026TL; DR
Unstructured text holds valuable insight but is hard to analyse at scale. This session shows how Azure AI Language Studio can extract sentiment, key phrases, and opinions from text and visualise the results in Power BI. Ideal for data professionals.
Session Details
Organisations sit on vast amounts of textual data, such as customer feedback, reviews, and free-text comments, but extracting meaningful insight from that data is often slow and difficult. This session shows how Azure AI Language Studio can be used to analyse text quickly and at scale, turning unstructured text into actionable insight.
The session focuses on practical text analytics techniques, including key phrase extraction, sentiment analysis, and opinion mining. Using a real dataset of customer reviews, attendees will see how these AI capabilities can be applied to understand customer sentiment, identify common themes, and uncover what users are really saying.
Through live demonstrations, we will use Python to submit text data to the Azure AI Language Studio APIs, retrieve enriched results, and then feed those outputs into Power BI. The session concludes by visualising the analysed data in dashboards that break insights down by rating, location, and other dimensions, showing what a realistic end-to-end text analytics solution can look like.
This session is aimed at data professionals who want to understand how AI can be used to analyse unstructured text and integrate those insights into existing analytics and reporting platforms.
The session focuses on practical text analytics techniques, including key phrase extraction, sentiment analysis, and opinion mining. Using a real dataset of customer reviews, attendees will see how these AI capabilities can be applied to understand customer sentiment, identify common themes, and uncover what users are really saying.
Through live demonstrations, we will use Python to submit text data to the Azure AI Language Studio APIs, retrieve enriched results, and then feed those outputs into Power BI. The session concludes by visualising the analysed data in dashboards that break insights down by rating, location, and other dimensions, showing what a realistic end-to-end text analytics solution can look like.
This session is aimed at data professionals who want to understand how AI can be used to analyse unstructured text and integrate those insights into existing analytics and reporting platforms.
3 things you'll get out of this session
- understand how AI can be used to analyse unstructured text
-understand how to integrate those insights into existing analytics and reporting platforms.
Speakers
Lewis Prince's other proposed sessions for 2026
AI Beyond the Hype; Practical Solutions for Real Businesses - 2026
Automating Multilingual Document Translation with Microsoft Fabric and Azure AI - 2026
Demystifying AutoML; Building Machine Learning Models with Azure - 2026
Responsible AI in Practice for the Microsoft Data Platform - 2026
Using Microsoft Copilot Studio to Build Chatbots That Answer Questions and Take Action - 2026
Lewis Prince's previous sessions
Fast and Efficent Text Analysis using Azure's Language Cognitive Service
We will go on a whirlwind tour of Azure Cognitive Services Language Studio, to show the wealth of tools available there, and then talking in particular about Key Word Extraction, Sentiment Analysis and Opinion Mining. We will apply these concepts through Language Studio APIs via Python on Customer Reviews data to then feed into a Power BI report to show how we can really squeeze so much more useful data out of chunks of text!
Copilot Studio: Guiding Your Chatbot Takeoff with AI Aviation!
I will talk you through how I created the Copilot chatbot for the SQLBits website.
The SQLBits Website ChatBot with Copilot Studio: How I built the chatbot for this events website)
I will talk you through how I created the Copilot chatbot for the SQLBits website.
Model Creation in Azure AutoML and Ingestion Through Excel
We will go through a brief introduction to what Machine Learning is and some of its applications. we will then explore why AutoML should be used by all; as a great starting point for anyone new to Machine Learning, as well as a time saving tool for those more experienced. Finally, we will expose a model as an endpoint and understand how we can use it. Specifically in this case how to use it in excel via VBA.
Technologies I will demonstrate are:
- Azure Machine Learning Studio
- VS code (with Azure Machine Learning Studio extension)
- Python
- VBA