For decades, machine learning engineers have struggled to manage and automate ML pipelines in order to speed up model deployment in real business applications. Similar to how software developers leverage DevOps to increase efficiency and speed up release velocity, MLOps streamlines the ML development lifecycle by delivering automation, enabling collaboration across ML teams and improving the quality of ML models in production while addressing business requirements.

Many data providers who participate in Snowflake Data Marketplace are already using Snowflake Cloud Data Platform as their primary data store, and they can share secure slices of their data via Global Snowflake, Snowflake’s global data sharing feature, with any other Snowflake consumer regardless of which cloud or Snowflake region each is using. But other potential data providers, especially data enrichment companies, are not yet using Snowflake themselves.

Wire encryption protects data in motion, and Transport Layer Security (TLS) is the most widely used security protocol for wire encryption. TLS provides authentication, privacy and data integrity between applications communicating over a network by encrypting the packets transmitted between endpoints. Users interact with Hadoop clusters via browser or command line tools, while applications use REST APIs or Thrift.

The government's COVID-19 response is a good example of failed leadership from a data perspective. While government officials have access to a huge amount of data to help them make decisions they’ve fundamentally failed to use it to take people on a journey. There’s a huge lesson that businesses can learn from this on how to use data to change behaviors. What we’ve seen is governments responding to the outbreak at a very simplistic level.

Being more productive than your super competitive peer group is hard. Being 10 times more productive might sound like an impossibility, an exaggeration.... or even a myth (unicorn, you say?). A 10x data scientist is literally 10 times more productive than the average data scientist. The skillsets of these data scientists create better career opportunities, higher peer recognition, and more interesting projects to work on.