With Ashish Khandelwal, Mainframe Modernization Engineer at Microsoft, Mukesh Kumar, Principle Group Engineering Architecture Manager at Microsoft, and Tom Griggs, Global Partner Senior Manager at Qlik
The sequel to "How to measure the success of data teams," in which Montreal Analytics explains how to evaluate the performance of individual contributors in a data team.
Learn how Fivetran is addressing your high-volume database replication needs with our newest High Volume Agent connector for SQL Server.
Python is insanely popular among machine learning enthusiasts these days. Hence, anyone developing a machine learning model normally turns to Python. The real challenge arises at the deployment stage because you can use many frameworks. Figuring out which Python framework to use may add to the confusion. This post discusses two popular machine learning frameworks, Flask and Django. We’ll also compare them side by side, so that you can make the right choice.
Sometimes you may want to limit the amount of analytics data coming into Moesif. This could be because you want to exclude specific traffic, such as internal or health check traffic, or you may want to reduce unnecessary data to control cost. Dynamic Sampling, available to customers on our Enterprise plan, was built to do just this. Dynamic Sampling lets you control which API calls are logged to Moesif based on customer or API behavior.