Pickles — Handcrafted Indian Pickles

I need to turn the raw data I already generate in Power BI and Dynamics AX into actionable insight through AWS-based machine-learning workflows. My priority is the AWS side: getting the data into the cloud, preparing it efficiently, and training models that I can push back to my reporting layer.

Here is what success looks like for me:
• A repeatable pipeline that lands data from AX/Power BI exports into S3 (or another AWS store you recommend), applies basic cleansing, and registers the results for downstream use.
• One end-to-end example in SageMaker (or a comparable AWS ML service) that trains, evaluates, and surfaces a prediction or classification relevant to my business.
• A brief, plain-English run-book so I can maintain and extend the solution after hand-over.

You’re welcome to choose the specific AWS services—Glue, Redshift, Athena, SageMaker Studio, Lambda, etc.—as long as they stay within the AWS ecosystem and keep future costs reasonable. I’m comfortable reading technical documentation but need you to handle the initial build and guide me through the final walkthrough.

If you have questions about the source data or want to suggest an alternative AWS architecture that could streamline the workflow, feel free to raise it in your first message.