

We take data observability for granted as a product category today, but that wasn’t always the case. We can thank Monte Carlo, and its CEO and co-founder Barr Moses, for doing much of the work to make data observability an accepted part of the modern data stack.
We recently caught up with Moses, who is one of our Datanami People to Watch for 2023. Here is what she had to say:
Datanami: Monte Carlo has emerged as one of the leaders of a new space called data observability. What do you attribute your success to?
Barr Moses: At the end of the day, I attribute 100 percent of our company’s success to our customers. One of our core values at Monte Carlo is “customer impact.” What can we ship today to make our customers as happy as possible? How can we make them successful in their data platform journey?
In fact, there wouldn’t be a data observability category without our customers. Before launching Monte Carlo, my co-founder, Lior [Gavish], and I spoke with hundreds of data teams across industries to distill what their core challenges were – what was keeping them up at night? Time and again, the issue that rose to the top of the list was this problem of data downtime. Data downtime refers to periods of time when data is missing, inaccurate, or otherwise erroneous, and it affects nearly every company. In fact, just last year, Wakefield Research reported that data teams spend two days per week firefighting data quality issues, and that inaccurate data impacts 12-27 percent of a company’s revenue.
This is a very real problem for data teams, and with the guidance and support of our customers, I’m excited to see what’s in store for the future of the category.
Datanami: Do you get the sense that companies are aware of their data observability challenges and are working to solve them? Or is it more of a case of ‘what we don’t know can’t hurt us?’
Moses: Data teams are facing a crisis. Over the past several years, they’ve spent millions of dollars in data infrastructure, investing in great tools to store and process large volumes of data like never before and hiring scores of data engineers and analysts to become data driven. But we’re at a crossroads: data teams are still struggling to earn the trust of their stakeholders.
Take Equifax, for example, who issued inaccurate credit scores to millions of its customers back in the spring of 2022, all due to a problem with bad data on a legacy on-prem server. And Unity Technologies, who lost more than $100 million in revenue when a data quality incident produced flaws in its advertising monetization tool.
These examples, and several others, highlight the importance of data quality, and the diligence that needs to be shown to prevent data downtime and improve data reliability. Data teams need to be closer to the business – and the only way to get there is by knowing (1) what data matters (2) who is using this data and (3) whether or not this data can be trusted.
The good news is that over 95 percent of data leaders intend to invest in data quality solutions in the next 12 months, if they aren’t already. I anticipate that we’ll see even more advancement and innovation in this category over the coming year – and I’m here for it.
Datanami: Can you give us a preview of what we’ll see from Monte Carlo in 2023?
Moses: Our product roadmap aligns with where our customers are going, and this means leaning into cloud-native data stack technologies. Last year, we announced support for Databricks and became Premier Snowflake partners, with over 150 mutual customers. Over the past few years, we’ve launched integrations with dbt Core and Cloud, Airflow, Prefect, Looker, and Tableau.
In 2023, we intend to expand end-to-end data observability coverage across the stack, with richer integrations with orchestrator and data lake technologies. We’re also excited to release new functionalities that reduce the time to resolution for data issues, with additional root cause analysis functionalities and a more seamless workflow for troubleshooting data issues in a central dashboard. And finally, we’re working on capabilities that provide both high-level and granular visibility into data quality over time so teams can improve reliability at scale and communicate health to stakeholders.
Datanami: Outside of the professional sphere, what can you share about yourself that your colleagues might be surprised to learn – any unique hobbies or stories?
Moses: I meditate for 10 minutes every morning. My mom is a yoga instructor and meditation teacher, and she instilled in me the importance of mindfulness early on. As a CEO and co-founder, these 10 minutes are critical to staying grounded and keeping things in perspective.
You can read the rest of the interviews with the Datanami 2023 People to Watch here.
October 3, 2023
- LogicMonitor Launches Dexda, AI for Hybrid Observability
- Integral Launches Privacy Workbench to Advance Data Quality and Certification
- The Linux Foundation Launches New Event: AI.dev: Open Source GenAI & ML Summit
- SnapLogic Leverages Amazon Bedrock to Make Anthropic’s Claude Available in SnapGPT
- data.world Integrates with Sigma Computing to Bring Explainability and Trust to Enterprise Data Analytics
- CERN Breaks New Ground with an Exabyte of Storage, Empowering Scientific Endeavors with Robust Data Capabilities
- New Edition of Esri’s ArcGIS Pro Guide Is Revised and Streamlined for Learning Latest Workflows
October 2, 2023
- Sapio Sciences Launches Scientific Data Cloud Made for Scientists, Sapio Jarvis
- Nextdata Closes $12M in Seed Funding to Unlock the AI Revolution by Decentralizing Data at Scale
- Databento Adds Raw Market Data in PCAP Format to Its Offering
- RavenDB Launches Version 6.0 Lightning Fast Queries, Data Integrations, Corax Indexing Engine, and Sharding
- Teradata and UiPath Partner to Help Businesses Automate Data-Driven Insights for ESG Initiatives
- R Street Institute Launches Cybersecurity-Artificial Intelligence Working Group
September 28, 2023
- Adverity Announces Gen AI Integration in Latest Product Strategy
- Springboard Launches New, 100% Online Machine Learning Engineering and AI Bootcamp for University Partners
- Revefi Unveils Data Operations Cloud to Redefine Data Quality and Cost Management
- Aporia Unveils New Guardrails Solution to Control Generative AI Performance
- Cornelis Networks and StorIT Announce Strategic Partnership to Bring AI and HPC Offerings to the Middle East and North Africa
- SAP Announces New Generative AI Assistant Joule
September 27, 2023
Most Read Features
- Databricks Versus Snowflake: Comparing Data Giants
- Data Mesh Vs. Data Fabric: Understanding the Differences
- How the Coronavirus Response Is Aided by Analytics
- Big Data File Formats Demystified
- What Is MosaicML, and Why Is Databricks Buying It For $1.3B?
- Tabular Plows Ahead with Iceberg Data Service, $26M Round
- Quantum Computing and AI: A Leap Forward or a Distant Dream?
- There Are Many Paths to the Data Lakehouse. Choose Wisely
- How Generative AI Is Transforming the Call Center Market
- AI Ethics Issues Will Not Go Away
- More Features…
Most Read News In Brief
- Mathematica Helps Crack Zodiac Killer’s Code
- GenAI Debuts Atop Gartner’s 2023 Hype Cycle
- Top 10 In-Demand GenAI Skills
- Oracle Introduces Integrated Vector Database for Generative AI
- GenAI Adoption, By the Numbers
- Starburst Brings Dataframes Into Trino Platform
- Data Fabric Firm Denodo Raises $336 Million
- Is ChatGPT Getting Dumber?
- Data Prep Still Dominates Data Scientists’ Time, Survey Finds
- Dataiku Introduces LLM Mesh with Key Partners
- More News In Brief…
Most Read This Just In
- DataStax Unveils New JSON API for Astra DB, Catering to 13M Global JavaScript Developers
- Salesforce and Snowflake Make Data Sharing-Based Integration Generally Available
- Salesforce and AWS Deepen Generative AI Partnership with Harmonized Customer Profile Offerings
- Salesforce Signs Definitive Agreement to Acquire Airkit.ai
- Dataiku Announces Breakthroughs in Generative AI Enterprise Applications, Safety, and Tooling
- Salesforce Announces the New Einstein 1 Platform
- Teradata Launches ask.ai, Brings Generative AI Capabilities to VantageCloud Lake
- Quantum Announces Next-Gen Cold Data Storage Solutions, Simplifying Cloud Integration
- Dataiku Unveils LLM Mesh and Announces LLM Mesh Launch Partners Snowflake, Pinecone, and AI21 Labs
- Google Cloud Unveils New Generative AI Innovations and Partnerships at Next ’23
- More This Just In…
Sponsored Partner Content
Sponsored Whitepapers
Contributors
Featured Events
-
AI in Healthcare Summit
November 14 - November 15 -
The AI Summit New York
December 6 - December 7