Going to Snowflake Summit 2025? Don't Overlook the One Thing That Can Break It All: Data Observability

If you're heading to Snowflake Summit 2025, you're likely building cutting-edge analytics, real-time dashboards, or complex machine learning workflows on Snowflake's powerful cloud platform. You're also not alone. Thousands of data engineers, architects, and analytics leaders are converging in 2025 to discuss scale, speed, and innovation.

But here's a hard truth:

None of your insights matter if the data behind them is wrong.

In this blog, we'll break down:

• The most common data reliability pitfalls in Snowflake-based stacks
• Why traditional monitoring isn't enough
• How Data Observability solves the root of the problem
• Why Rakuten SixthSense is purpose-built for modern Snowflake teams

Let's dive in.

Snowflake Makes Data Powerful — But Also Complex

Snowflake brings a lot to the table:

• Instant scalability
• Cross-cloud compatibility
• Seamless integration with tools like dbt, Airflow, Looker, Tableau, and more

But as your team starts stitching together data from 20+ sources, layering transformation jobs, and running analytics 24/7, things break:

• A bad upstream join leads to inflated metrics
• A null-laden dimension silently breaks your sales dashboard
• An accidental schema change corrupts your AI models

Worse? You often find out after stakeholders have made decisions.

What is Data Observability (and How is it Different from Monitoring)?

Monitoring tells you if your pipeline ran. Data Observability tells you if your data is trustworthy.

It focuses on 5 core pillars:

1. Freshness – Did data arrive on time?
2. Volume – Did we receive enough records?
3. Schema – Did the structure change?
4. Distribution – Do values look statistically off?
5. Lineage – Where did this data come from?

For Snowflake users, this means catching issues before they reach dashboards, stakeholders, or ML models.

The Top 5 Snowflake Data Reliability Pitfalls

1. Stale Data, Fresh Dashboards

Querying data that looks real-time, but is hours or days old.

2. Silent Schema Changes

Auto-updated tables break transformations but don't crash the pipeline.

3. Incomplete Loads

A late batch results in 30% fewer rows—undetected.

4. Inconsistent Aggregates

Distribution anomalies result in metric inflation or deflation.

5. Untraceable Breakages

No lineage visibility = hours wasted chasing down where things broke.

These issues impact costs, trust, and time to decision.

Rakuten SixthSense: Built for Snowflake Observability

Rakuten SixthSense delivers end-to-end Data Observability—from ingestion to visualization.

Here's how:

✅ Real-Time Anomaly Detection

Detect null spikes, volume drops, schema drifts, and more in Snowflake tables.

🧠 AI-Powered Prioritization

We score issues by impact so you focus on what actually matters.

📊 Lineage + Root Cause

From raw load to dashboard, trace where the failure started.

⏳ Freshness Tracking

Get alerts when data is late, missing, or delayed.

🔹 Native Snowflake Integration

Plug in directly—fast, secure, and no engineering lift required.

🔍 Searchable Dashboards

See quality scores, KPIs, and trends in one clean view.

Real Use Case: Broken Reporting Fixed in Minutes

A global e-commerce firm using Snowflake noticed major inconsistencies in their weekly sales data.

SixthSense detected a schema mismatch in a promotion-related dimension that had gone unnoticed for weeks. Our platform:

• Flagged the issue in real-time
• Identified the downstream impact across 7 dashboards
• Provided a fix workflow that resolved it within 2 hours

That's the power of observability at scale.

Going to Snowflake Summit 2025? Ask These Questions:

• How are you ensuring trust in your Snowflake data?
• Do you know when dashboards are showing outdated or broken data?
• Can your team trace issues back to source in minutes?
• Are you wasting credits querying low-quality data?

If the answer to any is "no," it's time to rethink your observability strategy.

🚀 Try It Yourself — No Signup Required

See how Rakuten SixthSense solves Snowflake data trust at scale.

👉 Explore the Interactive Demo

Or dive deeper here: Rakuten SixthSense Data Observability

Final Word

Your team is investing in data. Your tools are scaling. But if your data breaks silently, none of it matters.

As you prep for Snowflake Summit 2025, consider this:

"Data Observability is the difference between knowing your data is working and assuming it is."

Rakuten SixthSense gives you that confidence.

✅ Real-time insights ✅ End-to-end coverage ✅ Built for Snowflake teams

Try our demo now and make data trust your competitive edge in 2025.