The Data Downtime Blog

The latest trends and news in data observability.

Most recent

Monte Carlo Recognized as the #1 Leader in Data Observability and Data Quality by G2

G2 bases their rankings on real feedback and reviews from customers, so this recognition means the world to us.

The Comprehensive Guide to Data Reconciliation

Interpreting the Gartner Data Observability Market Guide

Mission Lane: Continuous Compliance Monitoring

Snowflake Summit 2024 Keynote Recap: The Era of Enterprise AI

What is a Data Mesh — and How Not to Mesh it Up

The Ultimate Guide To Data Lineage

What is Data Observability? 5 Key Pillars To Know

Data Observability

17 Valuable Use Cases for Automated Data Lineage

Learn how today's data teams apply automated lineage to boost productivity, reduce time to incident resolution, and more.

Download

Why Data Quality for AI Matters

How Skyscanner Enabled Data & AI Governance with Monte Carlo

Scaling Data Quality Management for Business Rules & Baseline Rules

Tales from the Pipeline: 4 Data Horror Stories To Keep You Up at Night

How Roche Built Trust in the Data Mesh with Data Observability

Measuring Data Quality at the Use Case Level

Data Platforms

They Handle 500B Events Daily. Here’s Their Data Engineering Architecture.

4 Native Snowflake Data Quality Checks & Features You Should Know

Cheat Sheet: A Data Leader's Guide to Data Metrics

Access the must-have metrics today's data leaders use to measure data quality, platform ROI, team productivity, and more.

Download Your Copy

Top Enterprise Data Catalog Tools

What is a Data Mesh — and How Not to Mesh it Up

Just Launched: AI Monitor Recommendations for Proactive Data Quality Management

How to Treat Your Data As a Product

Generative AI

Top 10 Data Engineering & AI Trends for 2025

3 Tips for Achieving AI-Ready Data at Scale from a Fortune 500 Data Leader

What is an AI Data Engineer? 4 Important Skills, Responsibilities, & Tools

How WHOOP Built and Launched a Reliable GenAI Chatbot

RAG vs Fine Tuning: How to Choose the Right Method

Generative AI Use Case: Using LLMs to Score Customer Conversations

Data Culture

Top 10 Data Engineering & AI Trends for 2025

The Ultimate Guide to Data Product Management

Learn how to build, manage, and scale reliable data products in our latest how-to guide, written by and for data product managers.

Download

Monte Carlo Named to America’s Most Loved Workplaces List 2024

5 Data Lake Examples That Prove They’re Not Just a Buzzword

The Big Data London Guide: 2024 Edition

Databricks Data + AI Summit 2024 Keynote Recap: The 5 Biggest Announcements

2024 State of Reliable AI Survey

Data Reliability

The Smart Approach to ETL Monitoring

8 Essential Data Pipeline Design Patterns You Should Know

2023 Modern Data Leader's Playbook

Stay up-to-date with the latest technologies, trends, and processes shaping modern data management.

Access Today

Scaling Data Quality Management for Business Rules & Baseline Rules

Data Stewards vs Data Analysts: Who’s Doing What With Your Data?

Data Owner Responsibilities: Balancing Security, Access, and Sanity

The High Cost of Poor Data Warehouse Governance

Data Discovery

The Complete Guide to Data Uniqueness

The No-Panic Guide to Building a Data Engineering Pipeline That Actually Scales

Data Traceability 101: Benefits, Challenges, and Implementation

Implementing Data Lineage in Python: Manual Techniques & 3 Automated Tools

All About ETL Testing: Checklist, Tools, and 4 Useful SQL Queries

Data Catalog vs. Data Dictionary: 3 Essential Differences

Case Studies

How Skyscanner Enabled Data & AI Governance with Monte Carlo

How Much Does Bad Data Cost You?

Do you know the cost of data downtime? This guide will help you calculate the cost of bad data for your company.

Download

How an Enterprise Intelligence Platform Delivered Self-Service Data Trust with Data Observability

How Roche Built Trust in the Data Mesh with Data Observability

On-Demand Delivery Service Drives AI Success by Boosting Data Trust with Alation & Monte Carlo

How WHOOP Built and Launched a Reliable GenAI Chatbot

How a Fortune 500 CPG Leader Takes a Proactive Approach to Data Quality

Announcements

IMPACT 2024 Keynote Recap: Product Vision, Announcements, And More

Monte Carlo Launches Observability for Azure Data Factory, Informatica, and Databricks Workflows

Monte Carlo First To Detect Breaking Code Changes With New Databricks, GitLab Integrations

Monte Carlo Named to America’s Most Loved Workplaces List 2024

Monte Carlo Recognized as the #1 Data Observability Platform by G2 for 6th Consecutive Quarter

Monte Carlo Appoints Former Stack Overflow Exec Tim Miller as Chief Revenue Officer

Video resources

Data Mesh 101: How Not to Mesh It Up

What is Data Observability – and Do You Need It?

2023: The state of data quality

Did you know that bad data impacts 31% of a company’s revenue? And that 74% of data engineers say data quality issues are surfaced first by stakeholders? These stats and more in our recent survey with Wakefield Research.

Learn more

3 simple steps for Snowflake cost optimization without getting too crazy.

Snowflake cost optimization efforts need to be right sized. Learn how to get the most savings with investing too much of your team’s time.

Learn more

Data testing vs. data quality monitoring vs. data observability: What's right for your team?

In the fight against bad data and broken pipelines, there are a few popular options. But what makes the most sense for your data quality needs? We’ve got the answers.

Learn more

The Data Downtime Blog

Most recent

Monte Carlo Recognized as the #1 Leader in Data Observability and Data Quality by G2

3 Steps to AI-Ready Data

The Comprehensive Guide to Data Reconciliation

Featured

Interpreting the Gartner Data Observability Market Guide

Mission Lane: Continuous Compliance Monitoring

Snowflake Summit 2024 Keynote Recap: The Era of Enterprise AI

Editors picks

What is a Data Mesh — and How Not to Mesh it Up

The Ultimate Guide To Data Lineage

What is Data Observability? 5 Key Pillars To Know

Data Observability

17 Valuable Use Cases for Automated Data Lineage

Why Data Quality for AI Matters

How Skyscanner Enabled Data & AI Governance with Monte Carlo

Scaling Data Quality Management for Business Rules & Baseline Rules

Tales from the Pipeline: 4 Data Horror Stories To Keep You Up at Night

How Roche Built Trust in the Data Mesh with Data Observability

Measuring Data Quality at the Use Case Level

Data Platforms

They Handle 500B Events Daily. Here’s Their Data Engineering Architecture.

4 Native Snowflake Data Quality Checks & Features You Should Know

Cheat Sheet: A Data Leader's Guide to Data Metrics

Top Enterprise Data Catalog Tools

What is a Data Mesh — and How Not to Mesh it Up

Just Launched: AI Monitor Recommendations for Proactive Data Quality Management

How to Treat Your Data As a Product

Generative AI

Top 10 Data Engineering & AI Trends for 2025

3 Tips for Achieving AI-Ready Data at Scale from a Fortune 500 Data Leader

What is an AI Data Engineer? 4 Important Skills, Responsibilities, & Tools

How WHOOP Built and Launched a Reliable GenAI Chatbot

RAG vs Fine Tuning: How to Choose the Right Method

Generative AI Use Case: Using LLMs to Score Customer Conversations

Data Culture

Top 10 Data Engineering & AI Trends for 2025

The Ultimate Guide to Data Product Management

Monte Carlo Named to America’s Most Loved Workplaces List 2024

5 Data Lake Examples That Prove They’re Not Just a Buzzword

The Big Data London Guide: 2024 Edition

Databricks Data + AI Summit 2024 Keynote Recap: The 5 Biggest Announcements

2024 State of Reliable AI Survey

Data Reliability

The Smart Approach to ETL Monitoring

8 Essential Data Pipeline Design Patterns You Should Know

2023 Modern Data Leader's Playbook

Scaling Data Quality Management for Business Rules & Baseline Rules

Data Stewards vs Data Analysts: Who’s Doing What With Your Data?

Data Owner Responsibilities: Balancing Security, Access, and Sanity

The High Cost of Poor Data Warehouse Governance

Data Discovery

The Complete Guide to Data Uniqueness

The No-Panic Guide to Building a Data Engineering Pipeline That Actually Scales

Data Traceability 101: Benefits, Challenges, and Implementation

Implementing Data Lineage in Python: Manual Techniques & 3 Automated Tools

All About ETL Testing: Checklist, Tools, and 4 Useful SQL Queries

Data Catalog vs. Data Dictionary: 3 Essential Differences

Case Studies

How Skyscanner Enabled Data & AI Governance with Monte Carlo

How Much Does Bad Data Cost You?

How an Enterprise Intelligence Platform Delivered Self-Service Data Trust with Data Observability

How Roche Built Trust in the Data Mesh with Data Observability

On-Demand Delivery Service Drives AI Success by Boosting Data Trust with Alation & Monte Carlo

How WHOOP Built and Launched a Reliable GenAI Chatbot

How a Fortune 500 CPG Leader Takes a Proactive Approach to Data Quality

Announcements

IMPACT 2024 Keynote Recap: Product Vision, Announcements, And More

Monte Carlo Launches Observability for Azure Data Factory, Informatica, and Databricks Workflows

Monte Carlo First To Detect Breaking Code Changes With New Databricks, GitLab Integrations

Monte Carlo Named to America’s Most Loved Workplaces List 2024

Monte Carlo Recognized as the #1 Data Observability Platform by G2 for 6th Consecutive Quarter

Monte Carlo Appoints Former Stack Overflow Exec Tim Miller as Chief Revenue Officer

Video resources

Data Mesh 101: How Not to Mesh It Up

What is Data Observability – and Do You Need It?

The Top 6 Data Trends in 2023

Related resources

2023: The state of data quality