⏪ Snowflake Time Travel & Fail-safe | How to Recover Data (Practical Examples)

Welcome back to AI Data Studio — where we simplify Data, Cloud, and AI with clear, hands-on tutorials!

In this video, we explore one of Snowflake’s most powerful and often misunderstood features — Time Travel and Fail-safe.
You’ll learn how to recover deleted or changed data in Snowflake using real, practical examples that every data professional should know.

Whether you accidentally dropped a table, ran a bad UPDATE, or need to audit historical data, this tutorial shows you exactly how Snowflake helps you go back in time.

🧠 What You’ll Learn:

✅ What Snowflake Time Travel is and how it works
✅ How to query historical data using AT | BEFORE clauses
✅ Recovering deleted tables and schemas
✅ Restoring data after accidental UPDATE or DELETE
✅ Understanding Fail-safe and when it applies
✅ Key limitations, costs, and best practices

💻 Hands-On Examples:

Querying data from the past

Undropping tables and schemas

Comparing current vs historical data

Understanding Time Travel retention periods

🧰 Tools & Concepts Used:

Snowflake Web Console

Time Travel SQL commands

Snowflake Account & Table retention settings

Sample datasets

🪄 Why This Matters:

Mistakes happen — and Snowflake is designed for them.
Mastering Time Travel and Fail-safe can save hours of recovery work, prevent data loss, and protect your analytics pipelines.

📺 Watch Next:

▶️ Understanding Snowflake Storage vs Compute
▶️ Working with Stages: Internal vs External Stages
▶️ Loading Data into Snowflake: Bulk Load with COPY INTO

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