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.
