Snowflake Streams are used to track and record Data Manipulation Language (DML) changes made to a table. Streams capture changes such as inserts, updates, and deletes, which can then be processed by other Snowflake objects or external applications.
* Creating a Stream:
CREATE OR REPLACE STREAM my_stream ON TABLE my_table;
* Using Streams: Streams provide a way to process changes incrementally, making it easier to build efficient data pipelines.
* Consuming Stream Data: The captured changes can be consumed using SQL queries or Snowflake tasks.
References:
* Snowflake Documentation: Using Streams
* Snowflake Documentation: Change Data Capture (CDC) with Streams

When using the ALLOW_CLIENT_MFA_CACHING parameter, a cached Multi-Factor Authentication (MFA) token is valid for up to 4 hours. This allows for continuous, secure connectivity without users needing to respond to an MFA prompt at the start of each connection attempt to Snowflake within this timeframe2.

When the DROP MANAGED ACCOUNT command is executed in Snowflake, it removes the managed account, including all objects created within the account, and access to the account is immediately restricted2.
References: [COF-C02] SnowPro Core Certification Exam Study Guide

Python worksheets in Snowsight enable users to perform data manipulations and transformations using the Python programming language directly within the Snowflake environment. This feature integrates the power of Python with Snowflake's data warehousing capabilities, allowing for sophisticated data analysis and manipulation.
Introduction to Python Worksheets:
Python worksheets provide an interactive environment to write and execute Python code.
They are designed to facilitate data science and data engineering tasks.
Functionality:
Users can run Python scripts to manipulate data stored in Snowflake.
It allows for leveraging Python's extensive libraries for data analysis, machine learning, and more.
Integration with Snowflake:
Python worksheets run on Snowflake's compute infrastructure, ensuring scalability and performance.
They can access and manipulate Snowflake tables directly, making them a powerful tool for data transformation.
Snowflake Documentation: Snowsight Python Worksheets