Data Downtime Blog

Data Downtime

How to Meet Your Data Reliability OKRs with Monte Carlo’s Service-Level Indicators (SLIs)

Set data quality OKRs and achieve greater data trust with Monte Carlo's new SLIs.

Data Downtime

Monte Carlo and PagerDuty Integration Brings DevOps to Data Pipelines with End-to-End Data Observability

Monte Carlo's PagerDuty integration helps data engineering teams achieve greater visibility into the end-to-end health of their data pipelines.
Delivering More Reliable Data Pipelines with PagerDuty and Monte Carlo

As more companies rely on more data to drive their product development and strategic decision making, it’s never been more…
Scaling Data Trust: How Auto Trader Migrated to a Decentralized Data Platform with Monte Carlo

With Data Observability, Auto Trader scaled data trust and ownership across their self-service data platform.
Announcing the 2021 Data Platform Trends Report

Building a data platform? We've got you covered.
Monte Carlo Brings Data Observability to Data Lakes with New Databricks Integration

Monte Carlo's new Databricks integration allows data teams to achieve end-to-end observability and automated lineage across their data lake environments.
How Optoro Builds Data Trust – and Ownership – at Scale with Monte Carlo

Logistics leader Optoro saves 44 hours per week with end-to-end Data Observability.
Blinkist Chooses Monte Carlo to Deliver More Reliable Data Pipelines Through Data Observability

Blinkist saves 120 hours of engineering time per week with Monte Carlo.
Beyond Monitoring: The Rise of Observability

Modern data and machine learning systems need both monitoring and observability. Here’s why.
Case Study: How Mindbody Achieves End-to-End Data Trust with Monte Carlo

Here's how Mindbody leverages Monte Carlo to achieve end-to-end data trust and more reliable data pipelines.
How to Extract Data Observability Metrics from Snowflake Using SQL

Monitor the health of your Snowflake data pipelines with these 7 queries.
How to Conduct Incident Management for Data Teams

4 steps to identify, root cause, and fix data quality issues at scale…
Delivering End-to-End Data Trust with Snowflake and Monte Carlo

With Monte Carlo and Snowflake’s strategic partnership, teams can finally trust their data through end-to-end Data Observability.
Monte Carlo and Snowflake partner to help organizations achieve more trustworthy data

Monte Carlo’s Data Observability platform gives Snowflake customers added confidence that their data is reliable and trustworthy.
The Right Way to Measure ROI on Data Quality

Introducing a better approach for measuring the cost of bad data to your business.
How Resident Reduced Data Issues by 90% with Monte Carlo

With Data Observability, the Data Engineering team at Resident reduced their data downtime by 90% percent.
The Data Engineer’s Guide to Root Cause Analysis

Introducing a five-step approach used by some of the best data engineering teams to root cause your data quality issues.
Data Discovery: The Future of Data Catalogs for Data Lakes

How data catalogs are failing us and why data discovery can help.
[VIDEO] How Resident Drives Data Observability with Monte Carlo

When it comes to trusting your data, having end-to-end Data Observability across your stack is critical. Daniel Rimon, Head of…
Data Software-as-a-Service: The Case for a Hybrid Deployment Architecture

With the combined benefits of on-prem security and SaaS convenience, data and ML vendors with a hybrid deployment architecture give…
Data Observability in Practice: Data Monitoring at Scale with SQL and Machine Learning

How to make your own data observability monitors from scratch and leverage basic principles of machine learning to apply them…
The Ultimate Data Observability Checklist

For most teams, data observability is more than just setting up a bunch of pipeline tests and hoping for the…
Why Production Machine Learning Fails — And How To Fix It

Discussing applications of ML in theory is much different than actually applying ML models at scale in production. Here's the…
Monte Carlo is SOC 2 Certified

Monte Carlo’s SOC 2-certification takes our commitment to security and privacy one step further for customers.
The New Rules of Data Quality

Unit testing your data only gets you so far. Here’s a better way to manage data quality at scale.
Data Observability: How Blinkist Prevents Broken Data Pipelines at Scale with Monte Carlo

Here’s how the data engineering team at Blinkist, a book-summarizing subscription service, saves 120 hours per week and increases revenue…
Data Mesh 101: Everything You Need To Know to Get Started

Your company wants to build a data mesh. Great! Now what? Here’s a quick primer to get you started --…
Data Observability: How to Build Your Own Anomaly Detectors Using SQL

How to use metadata to understand the root cause of data anomalies and take your data quality testing to the…
Introducing the 2021 Pioneers of Data Reliability

The 2021 Data Reliability pioneers are charting a new course for what it means to be truly data driven in…
Monte Carlo Raises $25M Series B to Help Companies Achieve More Reliable Data

Monte Carlo announces $25M Series B funding round to help companies achieve more reliable data through data observability.
Why You Need to Set SLAs for Your Data Pipelines

How to set expectations around data quality and reliability for your company…
Must-have Priorities for Your Data Team in 2021

In 2021, it’s not just about having the “modern data stack.” It’s about having a modern approach to working with…
[VIDEO] How Yotpo Drives Data Observability with Monte Carlo

For Yotpo, a leading e-commerce marketing platform, data downtime led to sleepless nights, costly fire drills, and unreliable analytics dashboards.
[VIDEO] How Blinkist Increases Marketing ROI with Data Observability and Monte Carlo

For Blinkist, a global book insights subscription service, broken data pipelines led to unreliable marketing spend, costly data fire drills,…
Data Observability in Practice Using SQL

A step-by-step tutorial for creating your own data quality monitors to catch freshness and distribution anomalies in your data pipelines.
How to Prevent Bad Data in Your Perfectly Good Pipelines

Your data broke. Now what? Here's how some of the best data teams prevent data downtime and, in the process,…
Data Observability: How Yotpo Fixes Data Quality at Scale with Monte Carlo

Here's how the Yotpo leverages Data Observability to prevent broken analytics dashboards and increase trust in their data.
Why Testing Your Data Is Insufficient

Data is a dynamic, ever-evolving entity. So why aren't we treating it like one? Here's why a hybrid approach to…
How to Improve Data Engineering Workflows with End-to-End Data Observability

With data observability, data teams can now identify and prevent inaccurate, missing, or erroneous data from breaking your analytics dashboards,…
Incident Prevention for Data Teams: Introducing the 5 Pillars of Data Observability

By applying principles of DevOps Observability (think: traces, logs, and metrics), data teams can achieve similar levels of visibility into…
Metadata is Useless — Unless You Have a Use Case

Here's why having metadata and lineage without a clear business application is worse than having no metadata at all.
The Data Downtime Before Christmas

What happens when a freshness anomaly threatens to ruin Christmas? Turns out, even Santa Claus and his elves aren’t…
Data Catalogs Are Dead; Long Live Data Discovery

Data catalogs aren't cutting it any more when it comes to metadata management and data governance. Here's how data discovery…
How Compass is Reinventing Real Estate with Data Reliability in the Cloud

Learn how Compass leverages data observability to increase cost savings, facilitate better collaboration, and achieve data reliability in the cloud…
How to Set Up Your Company’s Data Quality Strategy for Success

5 essentials steps for accelerating the adoption of data at your company…
Monte Carlo Releases Data Observability Platform to Unlock the Potential of the Modern Data Stack

The Monte Carlo Data Observability Platform is the first end-to-end solution to prevent broken data pipelines and dashboards.
Data Lake vs. Warehouse: How to Choose the Right Solution for Your Stack

Data warehouse? Data lake? Data lakehouse? All of the above? Here’s what you need to know to make the right…
How to achieve more reliable analytics with the Monte Carlo integration for Looker

Monte Carlo is excited to announce our partnership with Looker, a leading business intelligence software and big data analytics platform,…
Bringing Reliable Data and AI to the Cloud: A Q&A with Databricks’ Matei Zaharia

An interview with Apache Spark creator Matei Zaharia on all things AI, the cloud, and data reliability…
Demystifying Data Observability

3 practical examples on how to get started with data observability…
On the 2020 Elections, Texas Hold’em Poker, and Monte Carlo Simulations

What do Texas Hold 'Em poker, Monte Carlo simulations, and the 2020 U.S. elections have in common? It's more than…
Data Observability: How to Fix Your Broken Data Pipelines

In 2020, data is the new software. While software needs to be highly available, data needs to be highly reliable.
How to Solve the “You’re Using THAT Table?!” Problem

How to keep track of your data warehouse's most critical table and reports…
Monte Carlo Raises $16M to Build the World’s First Data Reliability Platform

With customers such as Compass, Eventbrite, and Mindbody, Monte Carlo is spearheading the Data Reliability category and delivering end-to-end Data…
Introducing the Pioneers of Data Reliability

A thank you to Monte Carlo’s customers, design partners, and data leaders spearheading the data reliability movement.
Data Observability: The Next Frontier of Data Engineering

To keep pace with data’s clock speed of innovation, data engineers need to invest in data observability, the next frontier…
Introducing the New ABCs of Data

To help you keep pace with the evolving world of data, we put together the new essential alphabet for data…
[VIDEO] Introducing Data Downtime: From Firefighting to Winning

During a 2019 Data Council meetup, Monte Carlo Co-founder & CEO Barr Moses discusses why data downtime matters to the…
How to Calculate the Cost of Data Downtime

Introducing a better way to measure the financial impact of bad data on your company…
What is a Data Mesh — and How Not to Mesh it Up

A beginner’s guide to implementing the latest industry trend: a data mesh.
How to Fix Your Data Quality Problem

Introducing a better way to prevent bad data.
What is Data Reliability?

And how to use it to start trusting your data.
Bad Data, More Problems

And other important lessons for the data industry.
How to Migrate to Snowflake Like a Boss

3 things you need to know for a smooth migration.
What is Data Observability?

Hint: it’s not just data for DevOps.
Data Quality — You’re Measuring It Wrong

Introducing a better way: data downtime.
Good Pipelines, Bad Data

How to start trusting data in your company.
Every Company is a Data Company (But Not Every Company is Good at Data)

The inverse relationship between data appetite and data success.
Closing the Data Downtime Gap

How to get ahead of bad data.
The Rise of Data Downtime

Introducing “data downtime” and its importance to data teams.

Data Culture

How AutoTrader built a more reliable data platform with Monte Carlo

Here's how Ed Kent, Principal Developer at Auto Trader UK, is scaling his team's data platform with reliability and trust…
Monte Carlo Named a Best Workplace for 2021 By Inc. Magazine

The Data Observability leader was also recognized as a winner in the On the Rise category of emerging companies…
Building a Better Data Culture: An Interview with ThoughtSpot’s Cindi Howson

We sat down with Cindi Howson, Chief Data Strategy Officer at ThoughtSpot about common challenges organizations face on the road…
5 Things Every Data Engineer Needs to Know About Data Observability

With data observability, data engineers can think more strategically about tackling the "good pipelines, bad data" problem.
You’re Not Realizing the Full Value of Your Company’s Data

How to overcome five non-obvious roadblocks on your journey to data analytics excellence.
Monte Carlo Launches Chief Data Officer Advisory Board

Monte Carlo's CDO Advisory Board will help us better serve customers on their journeys to data trust and pioneer the…
Monte Carlo Recognized as a 2021 Enterprise Tech 30 Company

Monte Carlo was named a leader in data by the 2021 Enterprise Tech 30 list. Here's why.
How To Convert 100% of Your Proofs of Concept into Happy Customers

How Monte Carlo's approach to "treating prospects like your best customers" leads to successful PoCs and better happier users.
On Data Governance: Maria Villar, Head of Enterprise Data Strategy and Transformation

We sat down with Maria Villar, Head of Enterprise Data Strategy and Transformation at SAP, to learn how the best…
Fighting Churn with Data: An Interview with Zuora Chief Data Scientist Carl Gold

And why data reliability is top of mind for the Subscription Economy…
A Summer at Monte Carlo: Improving Data Pipeline Observability at Scale

How I spent my summer internship on Monte Carlo’s software engineering team…
Why Hiring a Data Analyst Won’t Solve Your Business Problems

Building a strong data culture is challenging for even the data teams. We partnered with Data Culture co-founders Gabi Steele…
What Every Data Team Needs to Know Before You IPO

We share 5 essential ways data teams can prepare their companies for a successful IPO.
Which of the Six Major Data Personas Are You?

Who is responsible for data reliability in your data organization? The answer may surprise you.
What Does it Take to Succeed as a CDO in the Age of COVID-19?

We share three key takeaways from the event and propose next steps for CDOs to retain their competitive edge in…
[VIDEO] 3 Best Practices for Data Organizations: Structure, ROI, & Communications

Barr Moses, Monte Carlo co-founder and CEO, discusses best practices for how to get started building your data team with…
4 Essential Tactics for Managing a Great Distributed Data Team

Everything data leaders need to know about managing distributed teams in our remote-first world.
How to Build Your Data Platform like a Product

We share advice for designing a data platform that will maximize the value and impact of data at your company.
Good Tales of Bad Data

When data breaks and no one hears it, does it make a sound? And other tales for data teams.
How to Scale Your Data Team with Confidence

Building a data-first culture in our remote-first world takes more than a few fancy algorithms.
What We Got Wrong About Data Governance

And how we can make it right.
4 Ways to Lead with Data During a Global Pandemic

Defining the role of data leaders during a pandemic.
How to Measure the ROI of Your Data Organization

A more pragmatic approach to measuring the value of your data team.
You Say You Want a (Data) Revolution

Lessons learned making data a priority for the enterprise.
3 Takeaways from the 2019 Chief Data Officer Symposium

What the world’s most innovative CDOs are up to.