IMPACT 2024

From the Experts: Building the Blueprint for AI-Ready Data

IMPACT 2024 — Thu, 21 Nov 2024 05:34:55 GMT

[On-Demand] From the Experts: Building the Blueprint for AI-Ready Data

With data and AI reshaping industries, the need for reliable, high quality data is business critical. But, how are data teams actually driving data quality and reliability in practice?

We’re gathered a quorum of data leaders from SurveyMonkey, Grammarly and DraftKings to share how they’re tackling data quality head on. Tune in to learn best practices and lessons learned for how to approach implementing data quality management processes, technologies, and organizational changes to ensure their company can fly high with reliable data.

From Monolith to Microservices: Using Data Observability to Build a New Lending Platform

IMPACT 2024 — Thu, 21 Nov 2024 04:24:13 GMT

[On-Demand] From Monolith to Microservices: Using Data Observability to Build a New Lending Platform

For fintech company Earnest, high-quality, reliable data from end-to-end is absolutely essential. Join Bronte Baer, Manager of Data Platforms & Analytics Engineering at Earnest, as she dives into their transition from a monolithic data system to a microservices-based architecture and addresses the challenges of data migration, joining, monitoring, and validation in a new, decentralized environment.

She’ll share real strategies for leveraging data observability and metadata cataloging to ease the pain of a migration and how those strategies ultimately helped her team build a more reliable lending platform.

Going for Gold: A Conversation with U.S. Gold Medal Olympian Allyson Felix on Breaking Barriers with Data

IMPACT 2024 — Thu, 21 Nov 2024 04:14:17 GMT

[On-Demand] Going for Gold: A Conversation with U.S. Gold Medal Olympian Allyson Felix on Breaking Barriers with Data

Allyson Felix is the most decorated woman in track and field in history, winning 11 medals over 5 Olympics, including 7 golds, 3 silvers, and one bronze. In 2021, at the age of 35 and after giving birth to her daughter, she won bronze in the 400 meters and gold in the 4x400 meter relay. While Felix’s claim to fame was on the track, she was also one of the first Olympic athletes to leverage data to improve her performance, most notably to score her first gold in the 200m. Now, as an entrepreneur and activist, Felix uses data to advocate for improved maternal health outcomes for black mothers and conditions for postpartum athletes.

During this wide-ranging conversation, Felix and Monte Carlo will discuss her experience harnessing data to win gold, how advancements in AI have changed the game for modern athletes, and the role of data in advocacy.

Operationalizing Data Reliability in the Age of Generative AI

IMPACT 2024 — Thu, 21 Nov 2024 03:29:06 GMT

[On-Demand] Operationalizing Data Reliability in the Age of Generative AI

Earlier this year, Monte Carlo introduced the Trusted Data for AI (TDAI) Customer Advisory Council - an exclusive group of top technology leaders whose aim is to make the data powering AI more trustworthy and reliable.

In this special IMPACT session, hear from three TDAI Council members to get their blueprint for how they’ve fully embraced and operationalized data observability to drive their AI strategies at their organizations.

Garbage In, Garbage Out: The Real Impact of Bad Data on AI Models

IMPACT 2024 — Thu, 21 Nov 2024 03:26:06 GMT

[On-Demand] Garbage In, Garbage Out: The Real Impact of Bad Data on AI Models

We all know that poor data quality leads to poor performance when it comes to training and serving AI models. But how much garbage is too much garbage?

In this session, researcher and ex-Epic Games data leader Andrew Koller will share how AI model performance continually degrades as unreliable data is introduced, and outline what measures teams can take to ensure that AI stays accurate, trustworthy, and valuable at each stage of the development lifecycle. You’ll also hear from Data Analyst and Monte Carlo expert, Elle Pyatt, on how to prioritize data quality incidents, learn best practices for creating and managing alerts, and identify metrics for improving incident response times to get all the benefits of alerts (without the alert fatigue).

Powering Reliability for the AI Era: Leveraging AWS and Data Observability for Impactful Applications

IMPACT 2024 — Thu, 21 Nov 2024 03:15:04 GMT

[On-Demand] Powering Reliability for the AI Era: Leveraging AWS and Data Observability for Impactful Applications

As the leader in cloud computing, AWS powers 32 percent of the world’s cloud applications, including software, data products, and, of course, AI. AWS Bedrock, the company’s foundation model development platform, is charting the course for building impactful and scalable AI applications for customers worldwide. Leading the teams responsible for making these data organizations successful? Head of AI/ML and GenAI Specialist Solutions Architects, Slavik Dimitrovich. In this fireside chat with Monte Carlo Head of Solutions Engineering, Shohei Narron, Slavik discusses how real-world enterprises are driving successful outcomes on Bedrock, the role of data solutions like Amazon Redshift in the LLM equation, and how data observability partners like Monte Carlo ensure that these applications – and the RAG pipelines that augment them – are reliable and trustworthy.

Transforming Data into Value: Implementing Development Best Practices for High-ROI Data Products

IMPACT 2024 — Thu, 21 Nov 2024 03:12:39 GMT

[On-Demand] Transforming Data into Value: Implementing Development Best Practices for High-ROI Data Products

In today's data-driven business landscape, developing data products that maximize business value and productivity while achieving the highest ROI is crucial. This presentation will explore how integrating the Software Development Lifecycle (SDLC) with the principles outlined in Marty Cagan's seminal works (Inspired: How to Create Tech Products Customers Love and Empowered: Ordinary People, Extraordinary Products) can revolutionize data product development. By leveraging Cagan's methodologies, which emphasize customer-centric design, cross-functional collaboration, and agile practices, organizations can create data products that not only meet but exceed customer expectations.

This session will detail practical strategies for implementing these practices within the SDLC framework, ensuring that data products are both innovative and aligned with business goals. Attendees will gain insights into optimizing product management processes with tools like data observability, fostering a culture of empowerment, and driving continuous innovation to achieve sustainable business success.

Crafting Effective Data Quality Reports: Building Trust and Democratizing Data at Payoneer

IMPACT 2024 — Thu, 21 Nov 2024 03:06:37 GMT

[On-Demand] Crafting Effective Data Quality Reports: Building Trust and Democratizing Data at Payoneer

Payoneer, a global leader in cross-border payments, is at the forefront of transforming how data teams instill trust in data through a relentless focus on data quality and democratization. From defining clear goals and calculating data trust scores to implementing targeted strategies that improve satisfaction across user groups, Payoneer is setting a new benchmark for data-driven success in the financial sector.

Join Eli Genislaw, Senior Director of Data Engineering at Payoneer, to hear his approach to reporting on the state of data quality and democratization, and best practices for how you can implement these strategies at your organization.

Trust and Privacy by Design: Drata’s Ethical Use of Data in AI

IMPACT 2024 — Thu, 21 Nov 2024 03:03:54 GMT

[On-Demand] Trust and Privacy by Design: Drata’s Ethical Use of Data in AI

In the rapidly evolving world of compliance automation, safeguarding client data isn’t just a priority — it’s the cornerstone of trust, integrity, and it’s something that Lior Solomon, VP of Data Engineering at Drata, takes seriously.

In this session, Lior will explore how Drata’s responsible AI practices, combined with advanced data observability, set new standards for privacy, trust, and reliability in the industry. Discover how Drata integrates privacy by design, enforces strict data governance, and utilizes data observability to build AI systems that not only advance technology but also earn and maintain customer trust

The 13 Keys to Reliable Predictions: A Fireside Chat with Presidential Predictor Dr. Allan Lichtman

IMPACT 2024 — Thu, 21 Nov 2024 03:00:20 GMT

[On-Demand] The 13 Keys to Reliable Predictions: A Fireside Chat with Presidential Predictor Dr. Allan Lichtman

As data and AI leaders, we’re tasked with helping businesses and other organizations make better data-driven decisions. The same statistical models and modes of prediction can also be applied to elections - just ask Dr. Allan Lichtman. Lichthman is an award-winning historian and creator of the Keys to the White House Model, which uses 13 true/false criteria to predict whether the presidential candidate of the incumbent party will win or lose the election.

During this fireside chat, Dr. Lichtman will share how he developed his 13 Keys, the role of history vs. circumstance when it comes to data analysis, and how he’d revise his presidential prediction models almost 50 years later. We’ll also dive into the role of AI in electoral predictions and what this evolving technology means for the future of democracy.