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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.
Build vs Buy Your Data Warehouse, Lake, or Lakehouse
There's no one-size fits all answer to building or buying your data platform. In this piece we discuss the decision…
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…
The Build vs. Buy Guide for the Modern Data Stack
Building the data stack of your dreams? Nishith Agarwal, Head of Data at Lyra Health, discusses some initial considerations and…
7 Essential Data Quality Tests for Modern Data Pipelines
Data reliability on your radar? Get started with these 7 must-have data quality tests, including null value, numeric distribution, and…
Using Data Observability For Third-Party Data Validation
Third-party data validation and ingestion at scale is not easy. Here is one way to solve this challenge.
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
What is your name? What is your email address?…
Monte Carlo and dbt Labs Announce Partnership to Help Analytics Engineering Teams Achieve More Reliable Data
What is your name? What is your email address?…
7 Steps for Building a Successful Data Team at Your Startup
What is your name? What is your email address?…
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.
The Proactive Data Quality Metric You’re Not Using But Should
How to calculate data uptime and why it's the predictive data quality metric data engineers must start using.
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
What is your name? What is your email address?…
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 “Self-Service” Data’s Biggest Lie?
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…
3 Simple Steps For Snowflake Cost Optimization Without Getting Too Crazy
Snowflake cost optimization efforts need to be right sized. Read how to get the most savings without investing too much time…
Are DataOps Frameworks the Future Of the Modern Data Stack?
As data needs scale, teams need to start prioritizing reliability. Here’s why DataOps might be the answer—and how you can…
4 Native Snowflake Data Quality Checks & Features You Should Know
The bad news? Data breaks. The good news? These 4 Snowflake data quality checks & features can help!…
Don’t Make a Schema Change Before Answering These Five Questions
Not all schema changes are equal. Here is what to ask yourself before pushing your code off to production.
Is Modern Data Warehouse Architecture Broken?
The modern data warehouse architecture creates problems across many layers. Consider instead an immutable data warehouse for scale and usability.
5 Ways to Improve Data Quality with the New Monte Carlo Data Quality Trends Dashboard
The new Monte Carlo Dashboard incorporates data and visualization to provide actionable insights to users across data teams.
Vanquish Toil: 9 Data Engineering Processes Ripe For Automation
Data engineers must automate to survive. Especially these 9 data engineering processes.
Circuit Breakers: A New Way to Automatically Stop Broken Data Pipelines and Avoid Backfilling Costs
Monte Carlo launches Circuit Breakers to help data teams automatically stop broken data pipelines and avoid costly backfills.
Monte Carlo Announces Release of Observability Platform for Locally Sourced, Small-Batch Data
If you are part of the new wave of data engineers who are nostalgic for data platforms the way they…
You Have More Data Quality Issues Than You Think
On average, companies experience one data issue for every 15 tables in their warehouse. Here are 8 reasons why and…
The Cost of Bad Data Has Gone Up. Here Are 8 Reasons Why.
The rising cost of bad data and poor data quality has nothing to do with inflation and everything to do…
Data Observability Doesn’t Just Create Savings – It Drives Revenue, Too
If you think the benefits of data observability stop at cost cutting or avoiding bad outcomes, you’re only looking at…
What Good Data Product Managers Do – And Why You Probably Need One
A data product manager is responsible for data democratization and increasing the time to value for the data itself.
Treat Your Data Like An Engineering Problem: An Interview with Snowflake Director of Product Management Chris Child
Snowflake Director of Product Management Chris Child talks about the role of data observability solutions in the modern data stack…
Monte Carlo Named To Enterprise Tech 30 For Second Consecutive Year
Sponsored by Wing Ventures and Nasdaq, the prestigious award honors the best enterprise technology startups.
Data Observability for Developers: Announcing Monte Carlo’s Python SDK
Our Python SDK gives data engineers programmatic access to Monte Carlo to augment our platform’s lineage, cataloging, and monitoring functionalities.
Monte Carlo Data Observability Insights Now Available in the Snowflake Data Marketplace
Easily access data quality and usage metrics directly from your Snowflake environment with Monte Carlo.
eBook: The Modern Data Leader’s Playbook
Learn how top data leaders scale their teams, tech, and processes to meet the needs of the modern business.
Monte Carlo Announces dbt Core Integration to Help Companies Ship Reliable Data Faster
When it comes to achieving reliable data, Monte Carlo, the leading data observability platform and dbt, the data build tool,…
Announcing Monte Carlo’s End-to-End Field-Level Lineage to Help Teams Achieve Data Reliability
Monte Carlo’s field-level lineage functionality is now offered as part of our automated, end-to-end data observability platform. …
Unicorns, data mesh, category creation, and more reasons to attend IMPACT: The Data Observability Summit
Five reasons why you should attend IMPACT, the world's first Data Observability summit on Wednesday, November 3, 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.
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…
Reverse ETL and Data Observability: Solving Data’s “Last Mile” Problem
How Reverse ETL and Data Observability can help teams go the extra mile when it comes to trusting your data…
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.
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.
The Weekly ETL: How Do You “Thin Slice” a Data Pipeline?
What is your name? What is your email address?…
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.
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?…
Data Quality Solutions: Build or Buy? 4 Things To Know
Investing in a data quality solution? Here's everything you need to know.
Monte Carlo Launches Data Incident Management Feature, Incident IQ, to Help Organizations Achieve Data Trust
With Incident IQ, data teams using Monte Carlo’s Data Observability Platform can now easily and collaboratively identify, alert on, and…
Announcing Monte Carlo’s Incident IQ, a 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…
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
What is your name? What is your email address?…
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 AutoTrader UK 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
What is your name? What is your email address?…
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.
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.
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.
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 Snowflake Data Observability Metrics Using SQL in 5 Steps
Monitor the health of your Snowflake data pipelines with these 7 queries to extract Snowflake data observability metrics.
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 Data Incident Management for Data Teams
Conduct data incident management with 4 simple 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.
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 & Scientist’s Guide To Root Cause Analysis for Data Quality Issues
Introducing a five-step engineering root cause analysis approach used by some of the best data engineering and data science teams…
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 Reasons Data Discovery Platforms Are Best For Data Lakes
Here are 5 reasons why using a data discovery platform is a better alternative to data catalogs to ensure your…
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…
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 Observability: How to Build Your Own Data Anomaly Detectors Using SQL
How to use metadata to understand the root cause of data anomalies and take your data quality testing to the…
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…
[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.
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…
Data Observability Tools: Data Engineering’s Next Frontier
To keep pace with data’s clock speed of innovation, data engineers need to invest in data observability, the next frontier…
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.
7 Data Quality Checks in ETL Every Data Engineer Should Know
With the right data quality checks in ETL pipelines, you can identify and fix issues in near real-time and build…