Generative AI and the Future of Data Engineering
Generative AI is taking the world by storm - here’s what it means for data engineering and why data observability…
How Backcountry Increases Data Team Efficiency by 30% with Monte Carlo
Learn how Backcountry reduced time to detection and resolution for data quality issues while increasing data team efficiency with Monte…
Data Ticket Takers or Decision Makers?
Assessing the characteristics and value of reactive vs. proactive data teams, and what makes the most sense for your org.
Scaling Data Trust and Collaboration with Monte Carlo and Atlan’s New Integration
With Monte Carlo and Atlan's new integration, data teams can easily access up-to-date information about the quality of data assets…
How Assurance Achieves Data Trust at Scale for Financial Services with Data Observability
Learn how FinServ leader Assurance leveraged data observability to mitigate the risk and financial impact of data quality issues at…
61 Data Observability Use Cases From Real Data Teams
We reviewed hundreds of real world deployments to highlight 61 ways data teams are finding value from data observability use…
How Monte Carlo’s New GitHub Integration Helps Data Teams Detect, Resolve, and Prevent Breaking Changes Faster
Discover Monte Carlo's new GitHub integration to investigate breaking changes and understand the downstream impact of new pull requests.
Scaling Data Observability to Transactional Databases with Monte Carlo’s Postgres, MySQL, and Microsoft SQL Server Integrations
Monte Carlo’s new integrations with Postgres, MySQL, and Microsoft SQL Server enable customers to deploy custom monitors across popular transactional…
How Swimply Built Its Hyper Growth Data Stack with Snowflake, Fivetran, and Monte Carlo
Learn how Swimply, the two-sided experiences marketplace, delivers reliable, trustworthy data with Monte Carlo, Snowflake, and Fivetran.
Monte Carlo’s Data Observability Platform Recognized for Best Estimated ROI by G2
Monte Carlo takes home 10 spring 2023 G2 awards, including Easiest Setup, Easiest To Do Business With, and Users Love…
The Annual State of Data Quality Survey
Check out some of the stunning statistics in our annual data quality survey such as how data quality impacts 31%…
Monte Carlo’s New Sigma Integration Helps Data Teams Prevent Broken, Stale Dashboards
With this integration, Sigma and Monte Carlo users can be confident that the upstream data systems powering their analytics are…
The Composable Customer Data Platform: Everything You Need To Know
How and why organizations are turning to solutions like composable customer data platforms built directly on the data warehouse to…
Data Testing vs. Data Quality Monitoring vs. Data Observability: What’s Right for Your Team?
Struggling with data quality? You’re not alone. But how should you get started? We walk through the three most common…
The Next Big Crisis for Data Teams
Data teams are more important than ever before - but they need to get closer to the business. Here’s how…
17 Super Valuable Automated Data Lineage Use Cases With Examples
✔️ Simiplify SQL queries ✔️ Reducing data debt ✔️ Data collaboration ✔️ Transition to data mesh ✔️ Data warehouse migration…
Experimentation: How Data Leaders Can Generate Crystal Clear ROI
Data teams can drive quantifiable ROI by establishing a strong experimentation program. Here are the lessons we’ve learned at Airbnb,…
The Rise of Empty Queries OR Why You Can’t Always Just Re-Run That Failed Job
Empty queries are the triple threat of data issues: prevalent, difficult to troubleshoot, and impactful.
Monte Carlo Adds Fivetran Integration, Bringing Data Observability to the Orchestration Layer
As part of this announcement, Monte Carlo is now an official partner with the leading data automation movement platform.
Monte Carlo’s New Fivetran Integration Accelerates Data Incident Detection, Resolution
Monte Carlo is the only data observability platform with coverage from pipeline to BI, bringing data reliability to the orchestration…
Monte Carlo Achieves Google Cloud Ready – BigQuery Designation
Monte Carlo becomes the first data observability platform to achieve the Google Cloud Ready - BigQuery designation.
5 Proven Best Practices for Measuring Data Team ROI
Struggling to quantify the impact of your data team? You're not alone. Here are 5 strategies from the experts.
Ready or Not. The Post Modern Data Stack Is Coming.
Zero-ETL, AI, One Big Table, and other disruptors could radically change data engineering to create a post modern data stack.
How Best Egg Implemented a Reliable Data Mesh with Data Observability
See how the fast growing fintech marketplace has matured their data stack and driven increased levels of data quality, trust,…
How BlaBlaCar Built a Practical Data Mesh to Support Self-Service Analytics at Scale
See how BlaBlaCar reduced incidents and time to insights by enabling self service analytics and implementing data mesh.
Data Ingestion: 7 Challenges and 4 Best Practices
Data ingestion involves collecting data from source systems and moving it to a data warehouse or lake. Read on for…
Rise of the MLOps Engineer And 4 Critical ML Model Monitoring Techniques
MLOps engineers are automating ML model monitoring to quickly detect problems like pipeline issues, model drift, feature drift and more.
How Data Enablement Drives Sustainable Value at Upside
Upside leverages a model that emphasizes upfront investments in data enablement to create self-sustaining “data gardens.” Here’s how.
11 Ways To Stop Data Anomalies Dead In Their Tracks
11 proactive data quality practices for preventing data anomalies and stopping them before they occur.
The Chaos Data Engineering Manifesto: Spare The Rod, Spoil Prod
Chaos data engineering is another lesson we can learn from software engineers: break stuff to make it more reliable.
Data Fabric: The Future of Data Architecture
Is a data fabric architecture right for you? Learn why some of today's best teams are leveraging this approach.
How Mercari Operationalizes Data Reliability Engineering at Scale
6 best practices from Mercari’s data reliability engineering team for ensuring high quality data..
Introducing Table Health Dashboard, a Better Way to Track Data Quality Coverage at Scale
Monte Carlo’s Table Health Dashboard gives data teams visibility into the reliability and monitoring coverage of their most critical data…
How Vox Media Built a Post-Merger Data Stack with BigQuery, dbt, and Monte Carlo
Learn how the data engineering team at Vox Media built a reliable, scalable data platform with BigQuery, dbt, and Monte…
Data Vault Architecture, Data Quality Challenges, And How To Solve Them
How Pie Insurance improves data quality across their data vault architecture.
How Contentsquare Reduced Time to Data Incident Detection by 17 Percent with Monte Carlo
Like many hyper growth startups, Contentsquare is all about data. The company leverages AI to provide its users with actionable,…
Modern Data Quality Management: A Proven 6 Step Guide
This 6 step data quality management framework has helped hundreds of organizations achieve higher quality data across their modern data…
How Checkout.com Achieves Data Reliability at Scale with Monte Carlo
Learn how Checkout.com gained visibility into data across domains, scaled data quality checks, and achieved reliability at scale.
Data Contracts: Silver Bullet or False Panacea? 3 Open Questions
Three open questions data contracts still need to answer for engineering teams.
Monte Carlo Recognized as Winter 2023 Data Observability Leader by G2
Monte Carlo was recognized as a Winter 2023 Data Observability leader by G2, a leading peer-to-peer review site.
When to Build vs. Buy Your Data Warehouse (5 Key Factors)
There's no one-size fits all answer to building or buying your data warehouse, lake, or lakehouse. But answering a few…
Implementing Data Contracts in the Data Warehouse
Getting started with data contracts? Here's how to implement data contracts in your data warehouse across your critical production tables.
Data Fabric vs. Data Mesh: Everything You Need to Know
Building a data fabric? Here's everything you need to know about this emerging architecture taking the data world by storm.
The 31 Flavors of Data Lineage And Why Vanilla Doesn’t Cut It
4 critical reasons why your data observability solution needs to have data lineage.
How Blend Scales the Impact of Reliable Data with dbt Cloud and Monte Carlo
Discover how Blend’s data team leverages Monte Carlo and dbt Cloud to reduce compute costs and deliver more reliable data…
Why Data Governance Matters, Best Practices, and How to Build a Strategy
Building a data governance strategy? Here's everything you need to know.
Freshly’s Journey to Building Their 5-Layer Data Platform Architecture
How Freshly, a leading meal delivery service, built a more reliable data platform architecture with Snowflake, Fivetran, dbt, Looker, and…
Meaningful Product Experimentation: 5 Impactful Data Projects for Building Better Products
How data teams and product leaders can do product experimentation right and other impactful data projects for building better products.
How Collaborative Imaging Delivers Healthier Data Products with Monte Carlo
In healthcare, bad data can have severe implications. Here's how Collaborative Imaging uses Monte Carlo to drive data health at…
Top 5 Data Engineering Deep Dives in 2022
How do you engineer field-level lineage, data anomaly monitors, Spark lineage, or data pipeline circuit breakers? We’re glad you asked. …
Our Top 5 Data Mesh Articles In 2022
We focused on implementation best practices for one of our favorite data quality topics: the data mesh.
Barr Moses: My Top 5 Articles of 2022
Covering 2023 predictions, data self-service, KPIs, big data egos, underestimating data issues and other issues that are top of mind…
Our Top 5 Most Popular Data Engineering Articles In 2022
Data mesh, data observability, data contracts, data platforms and our other most popular data engineering articles.
Our Top 5 Articles on Data Teams in 2022
The data team is changing. We look into the future for roles like data engineers, data product managers, data reliability…
Data Quality Testing: 7 Essential Tests
Data reliability on your radar? Get started with these 7 must-have data quality tests, including null value, numeric distribution, and…
New Feature Recap: PowerBI Integration, Delta Lake Lineage, and Data Reliability Dashboard
Check out our latest product innovations including Databricks and PowerBI lineage; root cause analysis features; Data Reliability Dashboard, and more!…
How the GitLab Data Team Builds a Culture of Radical Transparency
How does GitLab build a culture of radical transparency? It starts - and ends - with reliable data.
How ELT Schedules Can Improve Root Cause Analysis For Data Engineers
Why Bayesian networks hold more promise segmentation analysis.
How PayJoy Drives Data Trust with Monte Carlo
Learn how the data team at PayJoy leverages data observability and end-to-end lineage to drive data trust at scale.
How To Implement Data Mesh: Top Tips From 4 Data Leaders
Four data leaders from leading organizations give their practical advice on how to implement data mesh.
How SeatGeek Reduced Data Incidents to Zero with Data Observability
In this video, SeatGeek's Brian London and Kyle Shannon share how data observability helped their data team reduce data incidents…
How Data and Finance Teams Can Be Friends (And Stop Being Frenemies)
Part one in a practical data leader series: how data leaders can better work with the finance team.
What’s Next for Data Engineering in 2023? 10 Predictions
Data trend predictions from two industry veterans who have made big bets on the future of data engineering.
3 Questions with Daniel Kahneman, Author of Thinking, Fast and Slow
Will AI develop empathy? Can AI and humans co-exist? Inquiring minds want to know, and Nobel Prize-winner Daniel Kahneman has…
The 7 Tenets Of Building A Data-Driven Culture
Check out the 7 rules that helped Cribl transform into a data-driven culture with critical assets used by 60% of…
Monte Carlo Announces Power BI Integration to Help Data Teams Triage and Prevent Data Incidents at Scale
Monte Carlo's new integration with Microsoft Power BI helps data teams detect, triage, and understand the downstream impact of data…
The Slow, Agonizing Death of the Customer Data Platform
Long live the composable customer data platform. Or, why marketing and data teams should be friends.
Where the Data Silos Are
You’ve heard of shadow IT, but what about shadow data? Read on to see where the data silos are and…
Announcing Monte Carlo’s Data Reliability Dashboard, a Better Way Understand the Health of Your Data
Data Reliability Dashboard gives data engineers the tools necessary to measure data uptime, drive operational improvements, and scale reliability.
5 Steps To A Successful Data Warehouse Migration
Real lessons from recent data warehouse migrations like Qubole to AWS EMR andMySQL to AWS Redshift.
The Fight for Controlled Freedom of the Data Warehouse
The data gatekeeper is dead, long live the…oh no what have we done?…
Monitoring for the dbt Semantic Layer and Beyond
Let’s talk about the dbt Semantic Layer as well as anomaly detection, resolution, and prevention across the data most important…
Why Data Cleaning is Failing Your ML Models – And What To Do About It
When it comes to achieving model accuracy, data cleaning alone is insufficient. Here’s why.
Organizing Talent: Return of the Data Center of Excellence
More organizations are leveraging a data center of excellence and central data platform to mitigate the risks inherent with the…
The Significance of O’Reilly’s Data Quality Fundamentals
O'Reilly Data Quality Fundamentals' is the publishing house’s first-ever book on data observability.
How Dr. Squatch Keeps Data Clean & Fresh with Monte Carlo
Data observability helps the groundbreaking men’s personal care product company maintain excellent data hygiene.
Big Data (Quality), Small Data Team: How Prefect Saved 20 Hours Per Week with Data Observability
Learn how Dylan Hughes and Prefect’s lean data team kept data reliability high and costs low with Monte Carlo.
Quartz Ranks Monte Carlo As Third Best Medium-Sized Company For Remote Workers
Monte Carlo one of 83 companies honored by the global business publication.
5 Predictions for the Future of the Data Platform
Maxime Beauchemin, the godfather of data engineering, shares his predictions for the future of the modern data stack.
How to Make Data Anomaly Resolution Less Cartoonish
Fixing broken data doesn’t have to be a game of whack-a-mole. Here’s how to speed up your data incident resolution…
New Feature Recap: Data Lakehouse Support, Anomalous Row Distribution Monitors, and More!
Highlighting Monte Carlo's latest product releases, including data lakehouse support, and anomalous row distribution monitors.
You Can’t Out-Architect Bad Data￼
Even with the most well-designed data platforms, systems will break. Without some measure of observability, you’re playing with fire.
5 Ways To Ensure High Functioning Data Engineering Teams
5 strategies for leading productive data teams and doing meaningful work.
Data Quality Monitoring – You’re Doing It Wrong
Monitoring just your “important” data only gets you so far. Here’s a better approach.
What is Data Discovery: Definitions & Overview
Data discovery is about surfacing relevant context and metadata across data sets so they can be easily found and effectively…
5 Steps to Operationalizing Data Observability with Monte Carlo￼
Driving early value with your new data observability platform doesn't have to be difficult. We share 5 tips for driving…
Daniel Kahneman and Nate Silver to Headline IMPACT: The Data Observability Summit
Other speakers include the CEOs and co-founders of Databricks, Confluent, and dbt Labs, as well as leaders at The New…
How to Build Data Products Your Company Will Actually Use
It takes more than a pretty dashboard to become data-driven. Afua Bruce, former Chief Program Officer at DataKind, shares how.
A Data Engineer’s Guide to Building Reliable Systems
Over the years, I’ve helped companies of all sizes build and maintain data systems—from my days as a data engineer…
Monte Carlo and dbt Labs Announce Partnership to Help Analytics Engineering Teams Achieve More Reliable Data
When it comes to trusting your data, Monte Carlo, the creator of the data observability category, and…
7 Steps for Building a Successful Data Team at Your Startup
When you’re the first data hire at a startup, the sky’s the limit—and that can be incredibly overwhelming. Who do…
Data Observability First, Data Catalog Second. Here’s Why.
You can’t realize the full value of a data catalog without observability. Here’s why.
How To Create Data Trust Within Your Organization
How to build data trust by preventing data incidents before they happen with the data uptime metric.
Data Engineers Spend Two Days Per Week Firefighting Bad Data, Data Quality Survey Says
Check out the results from our 2022 data quality survey and benchmark your data quality practices against 300 of your…
Monte Carlo and Databricks Partner to Help Companies Build More Reliable Data Lakehouses
Learn more about the Monte Carlo-Databricks partnership and how it brings end-to-end data observability and data quality automation tools to…
How We’re Implementing a Data Mesh at Sanne Group
Sanne Group's Head of Engineering shares his data mesh implementation plan and how they plan to adopt its four key…
Data Contracts and 4 Other Ways to Overcome Schema Changes
There are virtually an unlimited number of ways data can break. It could be a bad JOIN statement, an untriggered…
Using the Airflow ShortCircuitOperator to Stop Bad Data From Reaching ETL Pipelines
See how to leverage the Airflow ShortCircuitOperator to create data circuit breakers to prevent bad data from reaching your data…
Snowflake Data Mesh: Ensure Reliable Data with Data Observability
Here’s how Snowflake and Monte Carlo are working together to help data teams realize the potential of the data mesh…
How to Measure the Success of Your Data Team
It’s one thing to build a data team, but how do you measure it? We spoke with Jacob Follis at…
Monte Carlo Achieves Snowflake Premier Partner Status to Help Companies Accelerate the Adoption of Reliable Data
With over 70 mutual customers, Monte Carlo becomes the first data observability provider to achieve Snowflake Premier Partner status.
Is The Self Service Data Platform A Lie? Data Engineers Debate
Self-serve systems are a big priority for data leaders and a principle of nearly every modern data strategy, but what…
How to Set KPIs for Your Data Team
Six critical steps to setting the right KPIs for your data team - all while keeping a steady pulse on…
7 Lessons From GoCardless’ Implementation of Data Contracts
Data contracts define and enforce the schema and meaning of data to improve its reliability and usability.
Monte Carlo Announces Delta Lake, Unity Catalog Integrations To Bring End-to-End Data Observability to Databricks
To help organizations realize the full potential of their data lake and lakehouse investments, Monte Carlo, the data observability leader,…
Managing Big Data Quality And 4 Reasons To Go Smaller
Get proven strategies for managing big data quality and learn why, when it comes to big data quality, bigger isn't…
How to Build a Culture of Data Trust: A Conversation with Hilary Mason
We sat down with Hilary Mason, former GM of Machine Learning at Cloudera and co-founder of HackNY, to learn more…
Snowflake Summit 2022: For Customers, Less Than 25 Percent of Data Actually Lives on the Cloud
We surveyed over 200 data leaders at Snowflake Summit about how they're leveraging data in the cloud. Here's what we…
Snowflake Summit 2022 Keynote Recap: Disrupting Data Application Development in the Cloud
A view from the 10th row on Unistore, Python in Snowpark, and more exciting announcements from SFDC leadership.
Snowflake Observability and 4 Reasons Data Teams Should Invest In It
Snowflake is a gamechanger for your data strategy. With the right approach to Snowflake observability, you can unlock its full…
Building An External Data Product Is Different. Trust Me. (but read this anyway)
Developing an external data product is different, and let's face it harder, than serving internal customers. We dive into 5…
Measure The Impact Of Your Data Platform With These Metrics
Your team launched a new data platform. Great! How do you know it’s working?…
Building Spark Lineage For Data Lakes
Spark lineage has been a blindspot for the data engineering industry so we set off to engineer a solution. Here's…
How Monte Carlo and Snowflake Gave Vimeo a “Get Out Of Jail Free” Card For Data Fire Drills
See how Snowflake and Monte Carlo helped Vimeo achieve world-class data reliability on a massive scale.
Monte Carlo’s Series D and the Future of Data Observability
When it comes to building a category, it’s all about your customers. Here's our vision for the future of reliable…
Monte Carlo Raises $135M Series D to Accelerate the Rapid Growth of the Data Observability Category
Monte Carlo's latest round signals their commitment to bringing reliable data to companies everywhere.
Introducing the Next Class of Data Reliability Pioneers
A new wave of companies are adopting end-to-end data observability. Here are their stories. …
Data Stewards Have The Worst Seat At The Table
Data stewards have an impossible job. Here’s why and what we can do to empower them.
The Ultimate Guide To Data Lineage
Data lineage is a must-have feature of the modern data stack, yet we're struggling to derive value from it. Here's…
Tableau Field-level Lineage: A Data Analyst’s Dream Come True
We have extended coverage all the way to Tableau workbooks to better understand field-level relationships across the warehouse and BI…
Monte Carlo Named One of the Best Places to Work in the Bay Area for 2022
Monte Carlo was named the 6th Best Place to Work in the Bay Area for small businesses by Silicon Valley…