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Azure Open Datasets - Simply Explained
14 de jul. de 2026 ·
16m 44s
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Azure Open Datasets - Simply Explained
Descripción
Learning data science but stuck without clean, interesting data to practice on? This episode explains Azure Open Datasets for beginners, analysts and ML learners: what is in the catalog, how...
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Learning data science but stuck without clean, interesting data to practice on? This episode explains Azure Open Datasets for beginners, analysts and ML learners: what is in the catalog, how to pull it into Python, Azure Machine Learning or Power BI, and what really costs money. You will be able to grab ready-to-use data in minutes without scraping or cleaning.
In this episode
Key takeaways
Worth quoting
“Here's the key point, the data itself is free and Microsoft pays for the storage always. You only pay for compute if you process it” – Mirko Peters (02:13)
“Most people think machine learning is just about the algorithm. But the real insight from Microsoft is that most machine learning problems are impacted by real world factors.” – Mirko Peters (04:17)
Explore more on M365.FM
Follow and rate M365.FM in your podcast app, and join the free M365 community at m365con.net.
Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-microsoft-365-azure-cloud-power-platform-ai--6704921/support.
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In this episode
- 00:00 – The missing-data problem
- 00:49 – What Azure Open Datasets actually is
- 02:54 – Discovery, preparation, scale and reproducibility
- 05:03 – Catalog: weather and holidays
- 06:39 – Catalog: census and labor data
- 07:56 – Catalog: taxi trips, public safety, COVID-19 and ML benchmarks
- 11:01 – Access via Python, Azure ML, Power BI, Synapse and Databricks
- 13:45 – The cost question: compute and egress
Key takeaways
- Azure Open Datasets is a free catalog of curated public data, such as NOAA weather, holidays, US Census and NYC taxi trips, that Microsoft cleans, stores in Parquet and keeps refreshed in Azure.
- You can load the data with the azureml-opendatasets Python package, register it in Azure Machine Learning, connect Power BI through the Blob Storage connector or query it with Synapse serverless SQL and Databricks.
- The data and its storage are free, but compute, egress and your own storage are not, so keep compute in the dataset's region and sample before you scale.
Worth quoting
“Here's the key point, the data itself is free and Microsoft pays for the storage always. You only pay for compute if you process it” – Mirko Peters (02:13)
“Most people think machine learning is just about the algorithm. But the real insight from Microsoft is that most machine learning problems are impacted by real world factors.” – Mirko Peters (04:17)
Explore more on M365.FM
- Episode page: the full episode with chapters, quotes and FAQ on free public data
- Azure Open Datasets – the free catalog of curated public data this episode explains, from weather to taxi trips
- Power BI – one access path discussed, connecting to dataset storage URLs through the Azure Blob Storage connector
- Microsoft Azure – the cloud where the datasets are stored and where compute and egress costs arise
- Related episode: Predictive Maintenance on Azure for Manufacturers: What You Actually Need Before the Model
Follow and rate M365.FM in your podcast app, and join the free M365 community at m365con.net.
Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-microsoft-365-azure-cloud-power-platform-ai--6704921/support.
Información
| Autor | Mirko Peters M365, Azure & AI |
| Organización | m365 FM |
| Página web | www.m365.fm |
| Etiquetas |
Copyright 2026 - Spreaker Inc. an iHeartMedia Company
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