The Data Downtime Blog

The Future of the Data Engineer

A conversation with Maxime Beauchemin, creator of Apache Airflow and Apache Superset, on the state of data engineering in 2021.

Announcing O’Reilly’s Data Quality Fundamentals

Available today, Data Quality Fundamental's press release chapters dive into how some of the best teams are architecting for data…

4 Reasons Why I Joined Monte Carlo’s Data Science Team

Considering joining a data startup? Learn how and why Ryan Kearns turned his Monte Carlo internship into a job.

Monitors as Code: A New Way to Deploy Custom Data Quality Monitors From Your CI/CD Workflow

Monte Carlo releases Monitors as Code, allowing data engineers to easily configure new data quality monitors as part of their…

Data Observability: Five Quick Ways to Improve the Reliability of Your Data

Five common data observability use cases and how they can help your team improve data quality at scale and trust…

Bob Muglia, former Snowflake CEO, to Speak at IMPACT, the World’s First Data Observability Summit

Muglia will join the first Chief Data Scientist of the U.S., the founder of the data mesh, and the creator…

Data Mesh 101: How to Get Started

What is a data mesh? Do you even need one? Download this free guide to learn how some of the…

Anomaly Detection: Why Your Data Team Is Just Not That Into It

Delivering reliable data products doesn't have to be so painful. Introducing a more proactive approach to data quality: the Data…

Solving Data’s “Last Mile” Problem with Reverse ETL and Data Observability

How Reverse ETL and Data Observability can help teams go the extra mile when it comes to trusting your data…

Monte Carlo Recognized as a DataOps Leader by G2

Monte Carlo’s Data Observability Platform wins Best Support, Easiest To Do Business With, and High Performer for Summer and Fall…

What is a Data Incident Commander?

How data teams can build more resilient incident workflows with DevOps best practices.

How Vimeo Achieved End-to-End Visibility in Snowflake and Looker with Monte Carlo

Learn why the the data engineering team at Vimeo chose to partner with Monte Carlo for data observability.

The Ultimate Data Observability Checklist

Here are the 5 things every data observability strategy needs to help companies achieve end-to-end data trust.

Monte Carlo Raises Series C, Brings Funding to $101M to Help Companies Trust Their Data

Monte Carlo’s Series C highlights the rapid growth of the Data Observability category, our industry-defining customer adoption, and global expansion.

Celebrating the New Pioneers of Data Reliability

How today’s data leaders are prioritizing data trust and reliability at their companies.

Decoding the Data Mesh

Building a data mesh? Avoid these 7 common mesh-conceptions.

The Weekly ETL: How Do You “Thin Slice” a Data Pipeline?

In Monte Carlo’s Weekly ETL (Explanations Through Lior) series, Lior Gavish, Monte Carlo’s co-founder, and CTO answers a trending question…

Picture courtesy of Hotjar

How Hotjar Reduced Data Infrastructure Costs by 3x with Monte Carlo

To supplement data testing, Hotjar’s data engineering team chose to implement Monte Carlo for end-to-end data observability, monitoring, and field-level…

How PagerDuty Applies DevOps Best Practices to Achieve More Reliable Data at Scale

Here’s how the company pioneering DevOps handles data incident response at scale through end-to-end data observability.

Getting Started: Automatic Detection and Alerting for Data Incidents with Monte Carlo

Here’s how data teams get up and running with Monte Carlo to automatically detect and alert on data incidents with…

How The Farmer’s Dog Achieved Rapid ML-Based Anomaly Detection with Monte Carlo

Learn how The Farmer's Dog achieved fully automated anomaly detection out-of-the-box with Monte Carlo.

Kolibri Games’ 5-Year Journey to Building a Data-Driven Company

One startup's lessons learned learned building a data mesh—and distributed data team—from scratch.

soc

Monte Carlo is SOC 2 Type II Certified

Monte Carlo’s SOC 2 Type II certification ensures that our end-to-end data observability platform provides data security and privacy across…

What in the World is Going on with Data Catalogs?

Data catalogs are having an identity crisis. Here’s why.

The Weekly ETL: Will Data Engineering Ever Be Sexy like Data Science?

Data engineers are the backbone of the data team - so why can't they get the respect they deserve?…

4 Things You Need to Know When Solving for Data Quality

Investing in a data quality solution? Here's everything you need to know.

Monte Carlo Launches Incident IQ To Help Organizations Achieve End-to-End Data Trust

With Incident IQ, data teams using Monte Carlo’s Data Observability Platform can now easily and collaboratively identify, alert on, and…

Announcing Incident IQ, Monte Carlo’s Root Cause Analysis Workflow for Data Teams

How to get started with Incident IQ, Monte Carlo's all-in-one solution for troubleshooting and preventing broken data pipelines.

The Weekly ETL: How Do You Document Your Data Assets?

Lior Gavish, Monte Carlo's co-founder and CTO, answers a trending question on Reddit about some of the data industry's hottest…

The Ultimate Guide to Data Quality

What is data quality and why does it matter?…

The Quick and Dirty Guide to Building Your Data Platform

There are a lot of technologies you could use to build a data platform - but what do you really…

Monte Carlo announces integration with Snowflake’s Snowpark developer platform to deliver more secure data monitoring and observability

With Snowpark’s Java UDF support, Monte Carlo makes it faster and more secure for organizations to achieve end-to-end data trust…

A Tale of Baseball and Bad Data: Why I Joined Monte Carlo

I guess data runs in the family. Growing up as a kid in the ‘90s, I distinctly remember my father…

5 Non-Obvious Ways to Make Data Engineers Love Working For You

And how to become a better data leader in the process.

Monte Carlo Expands Leadership Team from Snowflake, Segment to Support Hypergrowth of Data Observability Category

Monte Carlo hires Snowflake, Segment go-to-market leaders to help companies accelerate the adoption of trustworthy and reliable data.

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.

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…

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.

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.

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 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…

How to Extract Data Observability Metrics from Snowflake Using SQL

Monitor the health of your Snowflake data pipelines with these 7 queries.

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…

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.

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…

Data Discovery: The Future of Data Catalogs for Data Lakes

How data catalogs are failing us and why data discovery can help.

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.

[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…

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.

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…

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…

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.

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.

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,…

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.

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

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 catalog

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…

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…

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.

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…

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,…

A Summer at Monte Carlo: Improving Data Pipeline Observability at Scale

How I spent my summer internship on Monte Carlo’s software engineering team…

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…

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…

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.

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.

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…

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…

[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…

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 Calculate the Cost of Data Downtime

Introducing a better way to measure the financial impact of bad data on your company…

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 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.

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.

Data Quality — You’re Measuring It Wrong

Introducing a better way: data downtime.

How to Measure the ROI of Your Data Organization

A more pragmatic approach to measuring the value of your data team.

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.

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.

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 Reliability Delivered.

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