Sneak Peek: Making Petabyte Scale Data Actionable with ADX Part 2
Coming Soon: Github Event Stream Processing, Queries and Visualization
TLDR; To celebrate the recent announcement of free private repos in github I wanted to release a sneak peak of a really cool project I’ve been working on for part two of this series.
Azure Data Explorer is a fast and highly scalable data exploration service for log and telemetry data. It helps you handle the many data streams emitted by modern software, so you can collect, store, and analyze data. Azure Data Explorer is ideal for analyzing large volumes of diverse data from any data source, such as websites, applications, IoT devices, and more.
Every thing in the post is self contained in open source Jupyter notebooks which can be run in the free Azure Notebook Service.
In the upcoming post you will learn how to:
- Link an EventHub to a ADX Cluster Programmatic Using ARM
- Ingest Stream Data from Git Hub Using Event Hubs, ACI and ADX
- Learn more complex ADX queries to track sentiment on the most popular Microsoft github repos, and identify the top contributors to the most popular repos by language.
- Link an ADX cluster to Grafana for real time visualization of stream queries
I don’t want to wait a week, where can I get a sneak peak of these skills?
Well in that case check out the following resources we’ll be covering them in more depth next week!
Looking forward to seeing you all next week if you are in Tel Aviv this week catch me on Tuesday at the Microsoft Ignite Tour.
About the Author
Aaron (Ari) Bornstein is an avid AI enthusiast with a passion for history, engaging with new technologies and computational medicine. As an Open Source Engineer at Microsoft’s Cloud Developer Advocacy team, he collaborates with Israeli Hi-Tech Community, to solve real world problems with game changing technologies that are then documented, open sourced, and shared with the rest of the world.
