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Barr Moses

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Lior Gavish

As companies depend more on data to improve digital products and make informed decisions, it’s crucial that the data they use be accurate and reliable. MonteCarlo, the data reliability company, is the creator of the industry’s first end-to-end data observability platform. Barr Moses and Lior Gavish are the founders of Monte Carlo and they join us today. Sean’s been an academic, startup founder, and Googler. He has published works covering a wide range of topics from information visualization to quantum computing. Currently, Sean is Head of Marketing and Developer Relations at Skyflow and host of the podcast Partially Redacted, a podcast about privacy and security engineering. You can connect with Sean on Twitter @seanfalconer .   Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post Data Reliability with Barr Moses and Lior Gavish appeared first on Software Engineering Daily.

As companies depend more on data to improve digital products and make informed decisions, it’s crucial that the data they use be accurate and reliable. <a href="https://www.montecarlodata.com/" rel="nofollow" target="_blank">MonteCarlo</a>, the data reliability company, is the creator of the industry’s first end-to-end data observability platform. <a href="https://twitter.com/BM_DataDowntime?ref_src=twsrc%5Egoogle%7Ctwcamp%5Eserp%7Ctwgr%5Eauthor" rel="nofollow" target="_blank">Barr Moses</a> and <a href="https://twitter.com/lgavish?lang=en" rel="nofollow" target="_blank">Lior Gavish</a> are the founders of Monte Carlo and they join us today. <a href="https://i0.wp.com/softwareengineeringdaily.com/wp-content/uploads/2022/05/Sean-Falconer.png" rel="nofollow" target="_blank"></a>Sean’s been an academic, startup founder, and Googler. He has published works covering a wide range of topics from information visualization to quantum computing. Currently, Sean is Head of Marketing and Developer Relations at <a href="https://www.skyflow.com/" rel="nofollow" target="_blank">Skyflow</a> and host of the podcast Partially Redacted, a podcast about privacy and security engineering. You can connect with Sean on Twitter <a href="https://twitter.com/seanfalconer" rel="nofollow" target="_blank">@seanfalconer .</a> Sponsorship inquiries: <a href="https://cms.megaphone.fm/organizations/619b680e-d813-11ea-9750-e7ecac406436/podcasts/e60108fe-e328-11ea-b2b6-1348249f900a/episodes/3913370a-bc44-11ed-ace6-8b1f96d82bba/sponsor@softwareengineeringdaily.com" rel="noopener noreferrer nofollow" target="_blank">sponsor@softwareengineeringdaily.com</a> The post <a href="https://softwareengineeringdaily.com/2023/06/12/data-reliability/" rel="nofollow" target="_blank">Data Reliability with Barr Moses and Lior Gavish</a> appeared first on <a href="https://softwareengineeringdaily.com" rel="nofollow" target="_blank">Software Engineering Daily</a>.

Data Reliability with Barr Moses and Lior Gavish

Barr Moses is a consultant turned CEO &amp; Co-Founder of Monte Carlo, a data reliability company. She started her career as a management consultant at Bain &amp; Company and a research assistant at the Statistics Department at Stanford University. Later, she became VP of Customer Operations at customer success company Gainsight, where she built the data and analytics team. She also served in the Israeli Air Force as a commander of an intelligence data analyst unit. Barr graduated from Stanford with a B.Sc. in Mathematical and Computational Science. Today, we’ll talk about Barr’s career journey, data reliability and observability, and what it means for data teams. If you enjoy the show, subscribe to the channel and leave a 5-star review. Subscribe to Daliana's newsletter on www.dalianaliu.com for more on data science.  Barr's LinkedIn: https://www.linkedin.com/in/barrmoses/ Daliana's Twitter: https://twitter.com/DalianaLiu Daliana's LinkedIn: https://www.linkedin.com/in/dalianaliu  (00:00:00) Introduction (00:01:24) How did she got into data science (00:08:26) Frameworks for data-driven decisions (00:11:20) Is customer support ticket always bad? (00:15:20) How to quickly find out what is true (00:20:17) Struggles in the data team (00:23:37) Daliana’s story about lineage (00:28:00) People stressed about data (00:28:09) Netflix was down because of wrong data (00:30:40) Common issues with data quality (00:33:14) 5 pillars of data observability (00:39:14) How does Monte Carlo help data scientists (00:43:08) Build in-house vs adopt tools (00:45:48) How Daliana fixed a data quality issue (01:02:44) How to measure the impact of the data team (01:09:09) Mistakes she made (01:15:28) Beat the odds

The Data Scientist Show

Barr Moses is a consultant turned CEO &amp; Co-Founder of Monte Carlo, a data reliability company. She started her career as a management consultant at Bain &amp; Company and a research assistant at the Statistics Department at Stanford University. Later, she became VP of Customer Operations at customer success company Gainsight, where she built the data and analytics team. She also served in the Israeli Air Force as a commander of an intelligence data analyst unit. Barr graduated from Stanford with a <a href="http://B.Sc" rel="nofollow" target="_blank">B.Sc</a>. in Mathematical and Computational Science. Today, we’ll talk about Barr’s career journey, data reliability and observability, and what it means for data teams. If you enjoy the show, subscribe to the channel and leave a 5-star review. Subscribe to Daliana's newsletter on <a href="http://www.dalianaliu.com" rel="nofollow" target="_blank">www.dalianaliu.com</a> for more on data science. Barr's LinkedIn: <a href="https://www.linkedin.com/in/barrmoses/" rel="nofollow" target="_blank">https://www.linkedin.com/in/barrmoses/</a> Daliana's Twitter: <a href="https://twitter.com/DalianaLiu" rel="nofollow" target="_blank">https://twitter.com/DalianaLiu</a> Daliana's LinkedIn: <a href="https://www.linkedin.com/in/dalianaliu" rel="nofollow" target="_blank">https://www.linkedin.com/in/dalianaliu</a> (00:00:00) Introduction (00:01:24) How did she got into data science (00:08:26) Frameworks for data-driven decisions (00:11:20) Is customer support ticket always bad? (00:15:20) How to quickly find out what is true (00:20:17) Struggles in the data team (00:23:37) Daliana’s story about lineage (00:28:00) People stressed about data (00:28:09) Netflix was down because of wrong data (00:30:40) Common issues with data quality (00:33:14) 5 pillars of data observability (00:39:14) How does Monte Carlo help data scientists (00:43:08) Build in-house vs adopt tools (00:45:48) How Daliana fixed a data quality issue (01:02:44) How to measure the impact of the data team (01:09:09) Mistakes she made (01:15:28) Beat the odds

Tackling data quality issues, 5 pillars of data observability, from management consultant to CEO of Monte Carlo - Barr Moses -The Data Scientist Show #062

“The problem of data trust is ubiquitous. The number one thing people told us was ‘the data is wrong and that leads us to a place where we can’t trust it, and we can’t use it…’” Live streamed on LinkedIn than on-demand, episode 14 of the #TrueDataOps podcast welcomed Barr Moses, Data Observability pioneer, CEO, and co-founder of Monte Carlo, who joined host Kent ‘The Data Warrior’ Graziano to discuss all things data and DataOps. “We can’t afford to ignore the implications of bad data - and this is where data observability comes in. Today, you not only have a lot more data, you also have a lot more people using the data…” Barr Moses LinkedIn: https://www.linkedin.com/in/barrmoses/  Check out Monte Carlo here: https://www.montecarlodata.com

#TrueDataOps

“The problem of data trust is ubiquitous. The number one thing people told us was ‘the data is wrong and that leads us to a place where we can’t trust it, and we can’t use it…’” Live streamed on LinkedIn than on-demand, episode 14 of the #TrueDataOps podcast welcomed Barr Moses, Data Observability pioneer, CEO, and co-founder of Monte Carlo, who joined host Kent ‘The Data Warrior’ Graziano to discuss all things data and DataOps. “We can’t afford to ignore the implications of bad data - and this is where data observability comes in. Today, you not only have a lot more data, you also have a lot more people using the data…” Barr Moses LinkedIn: <a href="https://www.linkedin.com/in/barrmoses/" rel="nofollow" target="_blank">https://www.linkedin.com/in/barrmoses/ </a> Check out Monte Carlo here: <a href="https://www.montecarlodata.com" rel="nofollow" target="_blank">https://www.montecarlodata.com</a>

Barr Moses - #TrueDataOps Podcast Ep #14

Barr Moses, CEO of Monte Carlo explains the difference between data quality and data observability, and how to make sure your data is accurate in a world where so many different teams are accessing it.

The Data Engineering Show

Barr Moses, CEO of Monte Carlo explains the difference between data quality and data observability, and how to make sure your data is accurate in a world where so many different teams are accessing it.

Data Observability with Millions of Users - Barr Moses

Welcome Barr Moses CEO &amp; Co-Founder of Monte Carlo, a data reliability company.  We talk detection, resolution, prevention and the 5 pillars of data observability.   Great dialog.Show Notes03:53 : Zero defect data06:02 : Customer success learnings 10:42 : Delivering value with data14:00 : Monte Carlo, the name18:20 : Data observability23:38 : Detection, resolution, prevention31:12 : Duplicate data brings Netflix down34:22 : 5 pillars of data observability36:22 : "Building data like a product"39:37 : Monte Carlo's differentiationFind Barr : linkedin.com/in/barrmosesWebsite : https://www.montecarlodata.com/Want to be featured as a guest on Making Data Simple?  Reach out to us at almartintalksdata@gmail.com and tell us why you should be next.  The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple &amp; fun.

Welcome Barr Moses CEO &amp; Co-Founder of Monte Carlo, a data reliability company.  We talk detection, resolution, prevention and the 5 pillars of data observability.   Great dialog.Show Notes03:53 : Zero defect data06:02 : Customer success learnings 10:42 : Delivering value with data14:00 : Monte Carlo, the name18:20 : Data observability23:38 : Detection, resolution, prevention31:12 : Duplicate data brings Netflix down34:22 : 5 pillars of data observability36:22 : "Building data like a product"39:37 : Monte Carlo's differentiationFind Barr : <a href="http://linkedin.com/in/barrmoses" rel="nofollow" target="_blank">linkedin.com/in/barrmoses</a>Website : <a href="https://www.montecarlodata.com/" rel="nofollow" target="_blank">https://www.montecarlodata.com/</a>Want to be featured as a guest on Making Data Simple?  Reach out to us at almartintalksdata@gmail.com and tell us why you should be next.  The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple &amp; fun.

Data Reliability: Detection, Resolution, Prevention.  With Barr Moses, CEO & Founder of Monte Carlo

This bonus episode features conversations from season 2 of the Open||Source||Data podcast. In this episode, you’ll hear from Barr Moses, Co-founder and CEO at Monte Carlo; Einat Orr, Co-founder and CEO at Treeverse; and Shinji Kim, Founder and CEO at Select Star.Sam sat down with each guest to discuss data observability. You can listen to the full episodes from Barr Moses, Einat Orr, and Shinji Kim by clicking the links below.-------------------Episode Timestamps:(00:35): Barr Moses(01:21): Einat Orr(02:07): Shinji Kim-------------------Links:Listen to Barr’s episodeListen to Einat’s episodeListen to Shinji’s episode

Open||Source||Data

This bonus episode features conversations from season 2 of the Open||Source||Data podcast. In this episode, you’ll hear from Barr Moses, Co-founder and CEO at Monte Carlo; Einat Orr, Co-founder and CEO at Treeverse; and Shinji Kim, Founder and CEO at Select Star.Sam sat down with each guest to discuss data observability. You can listen to the full episodes from Barr Moses, Einat Orr, and Shinji Kim by clicking the links below.-------------------Episode Timestamps:(00:35): Barr Moses(01:21): Einat Orr(02:07): Shinji Kim-------------------Links:<a href="https://www.datastax.com/resources/podcast/observability-customer-led-growth-confidence" rel="nofollow" target="_blank">Listen to Barr’s episode</a><a href="https://www.datastax.com/resources/podcast/Git-Like-Branch-Merge-for-Data" rel="nofollow" target="_blank">Listen to Einat’s episode</a><a href="https://www.datastax.com/resources/podcast/discoverability-products-userdiversity" rel="nofollow" target="_blank">Listen to Shinji’s episode</a>

Data Observability with Barr Moses, Einat Orr, and Shinji Kim

Highlights from this week’s conversation include:Barr’s background and career journey (2:12)Trust: a technical or human problem? (9:47)Behind the name “Monte Carlo” (15:41)Defining data accuracy and reliability (17:36)How much can be done with standardization (22:27)How to avoid frustration when generating data about data (25:49)Defining “resolution” (28:59)Understanding the concept of SLAs (33:25)Building a company for a category that doesn’t exist yet (37:40)What it looks like to use Monte Carlo (44:07)The best part about working with data teams (47:28)The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.

The Data Stack Show

Highlights from this week’s conversation include:<ul><li>Barr’s background and career journey (2:12)</li><li>Trust: a technical or human problem? (9:47)</li><li>Behind the name “Monte Carlo” (15:41)</li><li>Defining data accuracy and reliability (17:36)</li><li>How much can be done with standardization (22:27)</li><li>How to avoid frustration when generating data about data (25:49)</li><li>Defining “resolution” (28:59)</li><li>Understanding the concept of SLAs (33:25)</li><li>Building a company for a category that doesn’t exist yet (37:40)</li><li>What it looks like to use Monte Carlo (44:07)</li><li>The best part about working with data teams (47:28)</li></ul>The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit <a href="http://rudderstack.com" rel="nofollow" target="_blank">rudderstack.com</a>.

85: You Can Stop Doing Data Fire Drills with Barr Moses of Monte Carlo

Some of our topic highlights include:The history and background of Monte CarloWhy the planning process is so important for data teamsHow to set (and crush) a data goalThe difference between being obsessed with systems and being obsesses with goalsHow data teams waste timeHow often data downtime and data issues are tied to a lack of knowledge transfer and process within an orgHow we can continue to improve the corporate culture around dataAs always, I'd love to hear your thoughts on the episode over on Twitter @borisjabes.Want to discuss the best practices we covered in this episode? Come hang out in The Operational Analytics Club, where all your favorite data leaders gather. Know someone that you think would be an awesome guest on The Show (hint: you can totally nominate yourself)? Reach out to our content and community team. Resources:Barr Moses on LinkedIn Barr Moses on Twitter Barr Moses on MediumMonte Carlo on Twitter Monte Carlo on LinkedIn Monte Carlo's websiteMusic by the talented Joe Stevens. 

The Sequel Show

Some of our topic highlights include:<ul><li>The history and background of Monte Carlo</li><li>Why the planning process is so important for data teams</li><li>How to set (and crush) a data goal</li><li>The difference between being obsessed with systems and being obsesses with goals</li><li>How data teams waste time</li><li>How often data downtime and data issues are tied to a lack of knowledge transfer and process within an org</li><li>How we can continue to improve the corporate culture around data</li></ul>As always, I'd love to hear your thoughts on the episode over on Twitter <a href="https://twitter.com/borisjabes" rel="nofollow" target="_blank">@borisjabes</a>.Want to discuss the best practices we covered in this episode? Come hang out in <a href="https://www.operationalanalytics.club/" rel="nofollow" target="_blank">The Operational Analytics Club</a>, where all your favorite data leaders gather. Know someone that you think would be an awesome guest on The Show (hint: you can totally nominate yourself)? <a href="mailto:allie@getcensus.com">Reach out to our content and community team. </a>Resources:<ul><li><a href="https://www.linkedin.com/in/barrmoses/" rel="nofollow" target="_blank">Barr Moses on LinkedIn </a></li><li><a href="https://twitter.com/BM_DataDowntime" rel="nofollow" target="_blank">Barr Moses on Twitter </a></li><li><a href="https://barrmoses.medium.com/" rel="nofollow" target="_blank">Barr Moses on Medium</a></li><li><a href="https://twitter.com/montecarlodata" rel="nofollow" target="_blank">Monte Carlo on Twitter </a></li><li><a href="https://www.linkedin.com/company/monte-carlo-data/" rel="nofollow" target="_blank">Monte Carlo on LinkedIn </a></li><li><a href="https://www.montecarlodata.com/" rel="nofollow" target="_blank">Monte Carlo's website</a></li></ul>Music by the talented <a href="https://www.joestevenssound.com/" rel="nofollow" target="_blank">Joe Stevens. </a>