I'm interested in learning more about how you leverages self-serve analytics and natural language processing (NLP) capabilities to extract insights from data. Could you share your experiences and best practices? Specifically, I'm curious about: 1. Tools and Platforms: What tools or platforms do you use for self-serve analytics and NLP? How do they integrate with your existing data infrastructure? 2. Forums and Communities: Are there any forums or communities where IT and business groups discuss insights and collaborate on data-driven projects? 3. Challenges and Solutions: What challenges have you encountered while using these technologies, and how have you addressed them?

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Software Chief & Office Design Architect in Manufacturing8 months ago

Our Deep learning team confirmed that we do have a lot of experience using natural language processing (NLP) for various projects. Part of it is the use of large language models (LLMs) on our enterprise deployment. The other questions are too broad to answer properly in an email. Is there something more specific I can help with?  

CIO in Services (non-Government)8 months ago

I can share some answers but I think our FD/BI Team might better placed to fully answer (I will ask for additional comments)

1. Power BI, Snowflake and ADF, for the NLP we use the native capacity in Power BI and all of the teams find the native tools excellent. The usage is no split about 50:50 between curated reporting for the business and end user custom queries (most via NLP)
2. Mainly the Microsoft forums but there are also a number of really good PBI ones out there and I know they use these regularly in the beginning. As we are more mature users now we do not lean on the external resource as much anymore as we have grown our own 'experts'
3. Data, data, data, what where and how - getting this into a common platform and MDM etc was by far the hardest and most time consuming part, we are bout 70% of the way there making all of the data available. 

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