Monte Carlo and Snowflake Fundamentals

Start Monitoring Snowflake Data and Set Up Customizable Data Alerts

What you'll learn
Connect Monte Carlo to Snowflake
Monitor Data Anomalies in Monte Carlo
Configure Customizable Data Notifications
Custom SQL Data Monitors
Field Health Monitors
JSON Schema Monitors
Volume and Freshness Monitors
Infrastructure as Code
Github Actions for CI/CD
Useful Snowflake Monitors for All Organizations

Requirements
SQL
git
Ability to work in the command line
Description
Background

Monte Carlo is an incredibly powerful Data Observability tool for your data stack that monitors and alerts for data issues across your data warehouses, data lakes, ETL, and business intelligence. The platform uses machine learning to infer and learn your data, proactively identify data issues, assess their impact, and notify those who need to know. Beyond their ML monitoring, Monte Carlo offers robust customizable data monitoring and alerting so you can set up all types of data alerts for your organization - whether they are for data issues that need to be addressed, or simply for alerts that a specific metric has reached a certain threshold.

What you'll learn

By the end of the class, you'll have completely connected your own Monte Carlo and Snowflake accounts following best practices, and you'll be able to monitor and set up alerts on your Snowflake objects. Some of these skills you'll gain include

Configuring customizable monitors based on any data in your warehouse

Ensuring your data pipelines remain fresh with monitoring and alerting

Setting up useful Snowflake monitors to enhance the monitoring of your Snowflake

Configuring notifications through Slack or email

Managing all of the monitoring infrastructure through code

Setting up github actions to preview the infrastructure changes before deployment, and automatically deploy on merge requests

Why you should use Monte Carlo to monitor your Snowflake account

Snowflake is an incredible data warehouse critical to thousands of organizations. But effectively monitoring Snowflake at scale has been difficult, until we start taking advantage of Monte Carlo.

Some of the benefits of using Monte Carlo with Snowflake include

Automatically monitoring all relevant data with Monte Carlo's ML monitoring

Detect data quality issues in your pipeline before they reach downstream reports

Identify and manage data anomalies by assigning an owner to each data incident that needs investigation

Essentially, Monte Carlo allows you to use Infrastructure as Code to have full control over monitoring your Snowflake account. By establishing a process for identifying and triaging data incidents, you can efficiently manage your Snowflake account knowing that you have the monitors and alerts in place to let you know about any issues.

About Monte Carlo

Monte Carlo lets you monitor other platforms as well including other Data Warehouses, Data Lakes, and even BI Tools like Tableau. They're working to reduce data downtime for organizations and are continually pushing to help data teams measure the health of their applications.

Who this course is for
Data Analysts and Engineers looking to monitor their data in Snowflake
Data Analysts and Engineers looking to set up custom data notifications