Agenda

08:30

Registration & Breakfast

Hebrew
09:30

Opening remarks

Hebrew | Keynote
09:55

The Future of Data is Words

The world is changing, it’s pretty clear by this point.

With the advent of large language models (LLMs) and generative AI, we are witnessing the boundaries constantly being pushed on what is possible for a machine to understand and do, simply by using words. This revolution is not only reshaping technological possibilities but also redefining people’s expectations.
However, while this revolution is happening, our dear old friend SQL is officially celebrating its 50th birthday, proving itself once more as a survivor in the world of data.
So what is it going to be? Who will control the future of data? Words or SQL?

 

Let’s take a journey into the past, present and future of querying data.

We will talk about how SQL became so popular, how it survived for so long and what is still making it so sticky 50 years later. We will talk about the LLM revolution, the challenges of leveraging AI to transition from SQL to NLQ (Natural language querying) and some hints to the technologies that could get us closer such as RAG, Semantic Layers and Knowledge Graphs.
Lastly we will peek into the crystal ball and try to figure out what the future might bring, how it might change the way we see modern data platforms and data self service, and what all of this might mean for us data professionals.

Read more

Josef Goldstein

Data Platform R&D Manager, Wix

The data and culture guy. Currently leading the Big Data Platform R&D at Wix. Josef has over a decade of experience building data intensive SaaS applications and growing the awesome teams that make them. He believes that the secret sauce for creating sustainable complex systems is good design practices, effective communication between people, and automating everything. In his day to day he works tirelessly on building the culture necessary to support these values and propagate them to others, one pep-talk at a time.

The data and culture guy. Currently leading the Big Data Platform R&D at Wix. Josef has over a decade of experience building data intensive SaaS applications and growing the awesome teams that make them. He believes that the secret sauce for creating sustainable complex systems is good design practices, effective communication between people, and automating everything. In his day to day he works tirelessly on building the culture necessary to support these values and propagate them to others, one pep-talk at a time.

Hebrew
10:25

Panel: TBD

10:55

Coffee break

Hebrew | Data Engineering
11:10

Sparkless Patterns: The New Data Stack and Modern Data Architecture

In recent years, we have witnessed the emergence of powerful frameworks and libraries, such as Apache DataFusion, DuckDB, and Polars, that enable us to query and transform vast amounts of data at blazing speeds, even with modest compute resources. These frameworks not only enhance our capabilities but also pave the way for new kinds of data architectures and design patterns that challenge the traditional design of our ETL processes and query infrastructure. Workloads that once required a distributed Spark cluster to complete in a reasonable time, or queries that needed data warehouses to scan vast datasets, can now be processed more efficiently and with less overhead.

 

In this session, I will focus on three major frameworks: DuckDB, Apache DataFusion, and Polars, which are central to what many refer to as the ‘new data stack’ and its transformative capabilities. We will discuss the significant advantages these frameworks offer to data engineers, especially in cloud-native environments, and demonstrate the new data design patterns they enable through real use cases that utilize them.

Read more

Alon Agmon

Engineering Group Manager, AppsFlyer

Alon is an engineering group manager at AppsFlyer. Alon has been managing data engineering teams over the past few years, and handling exceptions for almost two decades. Intrigued by distributed systems, the big data ecosystem, and technological disruption. Fearless adopter and supporter of cutting edge data technologies.

Alon is an engineering group manager at AppsFlyer. Alon has been managing data engineering teams over the past few years, and handling exceptions for almost two decades. Intrigued by distributed systems, the big data ecosystem, and technological disruption. Fearless adopter and supporter of cutting edge data technologies.

English | Data Engineering
11:45

Boosting Cost Efficiency by Cost Aware Architecture

In this session, we explore the critical role of cost-aware architecture in achieving optimal cost efficiency for modern software systems. As organizations increasingly rely on cloud services, microservices, and distributed computing, understanding and managing costs becomes paramount.

 

We will discuss the shift from traditional architecture to cost-aware design and explore how architectural decisions impact operational expenses. We will showcase a real life example and the lessons learned when evaluating the different cloud providers and their services – based on cost models and show how rearchitecting the solution with cost in mind made the difference.

Attendees will gain insights into designing cost-efficient systems that balance performance, scalability, and financial constraints. By adopting a cost-aware mindset, organizations can optimize their architecture and drive sustainable growth.

Read more

Doron Hoffman

Chief Architect, Contentsquare

Doron Hoffman is a Chief Architect at Contentsquare. He has 30 years of experience as a software architect, technical leader, manager, and individual contributor. He specializes in designing and implementing complex, scalable, and cost-efficient solutions within AWS and Azure. He loves speaking in front of an audience and sharing his knowledge.

Doron Hoffman is a Chief Architect at Contentsquare. He has 30 years of experience as a software architect, technical leader, manager, and individual contributor. He specializes in designing and implementing complex, scalable, and cost-efficient solutions within AWS and Azure. He loves speaking in front of an audience and sharing his knowledge.

Hebrew | Data Engineering
12:05

Personalizing User Content - The Power of a Vector & Search DB

As a user explores the open web, our mission is to recommend the most suitable content for them to read next out of millions of potential items. Our goal is optimizing for clicks and conversions – And we have to do so (very) very fast.

 

In this talk, we’re gonna talk about how in Taboola we reduced this problem by leveraging the power of Vespa – a high scale Vector DB. Unlike other DBs – Vespa is both a search AND a vector DB. We’ll discuss Vespa’s architecture, topology and ranking features. How we implemented near real time data updates (using Debezium, Kafka and in-house mirroring), filters to reduce the document space, the optimizations we implemented along the way – and the tools and techniques we used to measure their impact, and how we embedded deep learning model estimations into simple 32-bit vectors to generate CTR and CVR estimations to use in ranking.

Read more

Shelli Glick

Infrastructure Engineering Team Lead, Taboola

Coding for over a decade, in the past few years I’ve been part of Taboola infrastructure engineering group working on some very large scale systems and making them better faster stronger

Coding for over a decade, in the past few years I’ve been part of Taboola infrastructure engineering group working on some very large scale systems and making them better faster stronger

Hebrew | Ignite
12:40

Ooops... I Deleted the Whole Production Table. What Did I Learn From It?

I got some new gray hair on the spot.

After that, I took a deep breath and called my tech lead to discuss the issue. We ended up recovering in less than half a day to just coin our motto: “Write your code as if you’re going to delete production”.

Let me take you through this nightmare that taught me 3 important lessons. 3 lessons that separate tech leads from the others.

Read more

Yerachmiel Feltzman

Senior Big Data Engineer, Tikal

6+ years of experience in data-centric positions; worked on both sides of the pipeline, with a demonstrated history of working with distributed systems for data pipelines, from architecture design to implementation, through performance debugging, monitoring, and deployment.

6+ years of experience in data-centric positions; worked on both sides of the pipeline, with a demonstrated history of working with distributed systems for data pipelines, from architecture design to implementation, through performance debugging, monitoring, and deployment.

English | Ignite
12:45

Out Of Distribution (OOD) for Classification Problems

Classification model inference is relatively a straight forward issue unless the real world input data contains examples from classes the model has not seen before. In this case, the feature vector of an ‘unseen’ input might coincide with one of typical vectors of a class the model was trained on. In this case, an unseen class might have a prediction with hight certainty level. We shall discuss this problem and it’s possible and popular solutions.

Read more

Yana Segal

Algo Team Lead, Nielsen

Currently Algorithms Team Lead at Nielsen, with versatile experience in ML fields such as Computer Vision and Recommendation Systems, both from engineering and DS perspectives. In the day-to-day employing technologies such as Pytorch and TensorFlow in the cloud environment. Sumo enthusiast.

Currently Algorithms Team Lead at Nielsen, with versatile experience in ML fields such as Computer Vision and Recommendation Systems, both from engineering and DS perspectives. In the day-to-day employing technologies such as Pytorch and TensorFlow in the cloud environment. Sumo enthusiast.

Hebrew | Ignite
12:50

From Scaling APIs to Scaling Data to Scaling Your Team

Forget the titles, no one is born a Data Engineer. With the right guidance, attitude and passion, the transition to data engineering is not only possible, but also brings many advantages. In this talk, I will take you through my own journey of leaving the world of APIs and services as a backend engineer to enter the world of variety and scale as a data engineer. I will cover why I was passionate about this transition, the challenges I faced, the change in perception, and the benefits of being a data engineer with a background in backend engineering. By the end of this talk, you will be convinced that one of the best ways to scale your team is by incorporating new talent from various backgrounds, giving your team a diverse set of knowledge and skills.

Read more

Shani Aharoni

Data Engineer, Finout

A software engineer, an 8200 alumni and for the last 7 years solving problems, sometimes by code. Currently, building the next-generation FinOps platform to manage and reduce cloud costs as a data engineer. When I’m not creating bugs, you can find me cooking, at the beach or even sweating my head off at the gym.

A software engineer, an 8200 alumni and for the last 7 years solving problems, sometimes by code. Currently, building the next-generation FinOps platform to manage and reduce cloud costs as a data engineer. When I’m not creating bugs, you can find me cooking, at the beach or even sweating my head off at the gym.

Hebrew | Ignite
12:55

Congratulations! Meet Your New Little Brother

As you all know, data professions have become some of the most required professions in the world.

We at the Ministry of Education felt an obligation to prepare the students for this important field, therefore we established the National Data Analysis Major for High Schools in Israel.

 

In this talk, we’ll tell you about the dilemmas we’ve had about what should be taught in the data analysis program and what skills would prepare the student best to be data analysis-oriented.

We will tell you about the global interest in our Major and the research being done worldwide on our groundbreaking program.
Above all, we will tell you about you- data people, and your enormous contribution to upgrading and improving the Major.

Read more

Ronit Nehemia

Supervises a High School Data Analyst Program, Ministry of Education

Ronit Nehemia is a data science education leader and innovator in Israel. Ronit supervises information and data trends and conducts data analysis on K12 education at Israel’s Ministry of Education. In the past, she was a National Information and Communications Technology Inspector, responsible for implementing a national plan to adapt the education system to the 21st century. She was also the Director of the Technological Trends Fair and a teacher in the education system. Ronit has a master's degree in information studies from Bar Ilan University.

Ronit Nehemia is a data science education leader and innovator in Israel. Ronit supervises information and data trends and conducts data analysis on K12 education at Israel’s Ministry of Education. In the past, she was a National Information and Communications Technology Inspector, responsible for implementing a national plan to adapt the education system to the 21st century. She was also the Director of the Technological Trends Fair and a teacher in the education system. Ronit has a master's degree in information studies from Bar Ilan University.

Hebrew | Ignite
13:00

It’s Just an Alert, Don’t Wake Up!

You have a very important job, you need to keep production up & running 24/7! You setup alerts so you will know when something is wrong with it, but now there are alerts! Some of them are very important! So important that you need to leave everything that you do and start to handle them but some of them are less important and you can look at them in the morning or even ignore them.

Maybe we have too many alerts?
Or maybe we are missing alerts?
What is the purpose of an alert?

Did you try to think about the KPI of a good alert? How do we measure if an alert is good or bad?
In this talk we are going to define what is a good alert, how to create a KPI on alerts so you can make better alerts that are more accurate and help keep production up & running.

Read more

Alon Nativ

Head of Data, Tomorrow.io

Alon is a developer at heart and a monitoring freak, for the last 15 years he has been building systems as developers, managing large teams and hacking systems. he's passionate about building large scale systems, and the process of making an impact, always looking for a way to improve the development process and optimize the system. Public speaker Talking about development in reversim podcast (for ~8 years) Mentoring managers & speakers And most important father of 3 kids and husband of an amazing wife :)"

Alon is a developer at heart and a monitoring freak, for the last 15 years he has been building systems as developers, managing large teams and hacking systems. he's passionate about building large scale systems, and the process of making an impact, always looking for a way to improve the development process and optimize the system. Public speaker Talking about development in reversim podcast (for ~8 years) Mentoring managers & speakers And most important father of 3 kids and husband of an amazing wife :)"

13:05

Lunch

Hebrew | Culture
14:00

Building a Data-Driven Culture: An Anthology of Strategies and Insights

In an era defined by data abundance, the ability to harness its potential has become a competitive imperative. From startups to multinational corporations, the pursuit of a data-driven culture has never been more urgent. But amidst the buzzwords and promises, what truly distinguishes success and failure?

 

This talk offers an anthology of real-world stories that illuminate the journey toward building and sustaining a data-driven culture. Through some narratives drawn from diverse industries, we uncover the challenges, fails, triumphs, and transformative strategies employed by organizations committed to unleashing the power of their data.

 

Attendees will gain invaluable insights into practical approaches that have proven effective in fostering a data-driven culture, as well as lessons learned from initiatives that fell short of expectations, ensuring that attendees leave equipped with real-world knowledge that can be applied immediately within their organizations.

Read more

Mor Nitzan

Team Lead Product Analytics, JFrog

With over 12 years of dedicated experience in the realm of data, I have navigated through diverse industries including fintech, adtech, and cybersecurity. From startups to corporate environments, I've spearheaded technical and strategic data initiatives, driving impactful results through meticulous analysis and process optimization. As a full-stack analyst, I possess a unique ability to visualize comprehensive data landscapes, managing them end-to-end to deliver tangible value to businesses.

With over 12 years of dedicated experience in the realm of data, I have navigated through diverse industries including fintech, adtech, and cybersecurity. From startups to corporate environments, I've spearheaded technical and strategic data initiatives, driving impactful results through meticulous analysis and process optimization. As a full-stack analyst, I possess a unique ability to visualize comprehensive data landscapes, managing them end-to-end to deliver tangible value to businesses.

Hebrew | Data Engineering
14:20

Live in the Data Wild West: The Data Contracts Sheriff

In today’s data-driven world, managing vast amounts of data from various online and offline sources to various destinations is both a challenge and an opportunity. At Riskified, we have established a robust data contracts platform to ensure trust and quality across our data ecosystem.

 

In this session, we will explore how we have built comprehensive data contracts that include strict testing, detailed documentation, and an extensive data catalog based on open-source products like DBT, Datahub, Great Expectations, and Elementary.

We will share our methodologies for maintaining data integrity, the tools we use for quality assurance, and the best practices for documenting and cataloging data pipelines and tables.

 

Join us to discover how our approach to data contracts can enhance data reliability and support informed decision-making within your organization.

Read more

Tal Peretz

Data Platform Engineer, Riskified

Tal Peretz is a Data Engineer at Riskified. His expertise lies in developing data pipelines, building scalable infrastructure, data science and implementing data quality frameworks, enabling Riskified to make data-driven decisions and prevent fraud effectively. As a Harry Potter and data engineering fan, Tal combines his love for technology and entertainment, appreciates the magic of storytelling, and strives to contribute to the data engineering field.

Tal Peretz is a Data Engineer at Riskified. His expertise lies in developing data pipelines, building scalable infrastructure, data science and implementing data quality frameworks, enabling Riskified to make data-driven decisions and prevent fraud effectively. As a Harry Potter and data engineering fan, Tal combines his love for technology and entertainment, appreciates the magic of storytelling, and strives to contribute to the data engineering field.

Hebrew | Data Engineering
14:55

Dropping Doesn’t Mean Losing

As engineers, we are used to keeping the data we produce, usually within the guidelines of our business needs (like when we create retention as the data is too old to be used) or limitations (we cannot afford more than X TB of data).

 

However, sometimes we might create “too much” data, which we just cannot support, and an instant drop of the data is in order.
In Outbrain, as part of the data democratization strategy, a developer is free to send (almost) any kind of log/message that he wants/needs from his microservice/application. Therefore, we had to impose mechanisms to potentially drop data base on various dimensions of the sent message (and the sending rate/volume).

 

In this session I will present the idea behind the system and how it works.

Read more

Daniel Gur

SRE Team Lead, Outbrain

With over 20 years of experience in the fields of IT, Linux and Devops, Now I'm leading the SRE team at Outbrain, dealing with Outbrain's huge scaling challenges.

With over 20 years of experience in the fields of IT, Linux and Devops, Now I'm leading the SRE team at Outbrain, dealing with Outbrain's huge scaling challenges.

Hebrew | Data Engineering
15:15

Exploring the Depths of Apache Iceberg's Metadata Capabilities

Apache Iceberg provides a powerful framework for managing large-scale data with advanced features that are crucial for today’s data-intensive applications. This talk will focus on the various metadata tables that Iceberg offers and how they can be leveraged to enhance data management practices across diverse use cases, such as compaction, incremental processing, and even monitoring.

Read more

Amit Gilad

Founding Engineer, Lakeway

Seasoned data engineer with over eight years of experience architecting and managing large-scale data systems. He currently leads the pioneering migration to Apache Iceberg at Cloudinary. Over the past two years, Amit has played an instrumental role in spearheading Cloudinary's transition to the cutting-edge Apache Iceberg distributed data table format, leveraging his deep expertise in optimizing data storage, enhancing data retrieval processes, and ensuring seamless data operations within cloud environments.

Seasoned data engineer with over eight years of experience architecting and managing large-scale data systems. He currently leads the pioneering migration to Apache Iceberg at Cloudinary. Over the past two years, Amit has played an instrumental role in spearheading Cloudinary's transition to the cutting-edge Apache Iceberg distributed data table format, leveraging his deep expertise in optimizing data storage, enhancing data retrieval processes, and ensuring seamless data operations within cloud environments.

15:30

Coffee break

Hebrew | Data Engineering
15:45

Unifying Real-Time and Data Lake: Yotpo's Transition from Chaos to Coherence

Real Time and Data Lakes are becoming a single beast, these worlds are converging. Kafka became the de facto streaming platform, integrating with modern data lakes. Flink became super popular and adopted by big vendors such as Amazon, Microsoft and Alibaba. Confluent, not only adapted flink but also introduced TableFlow solution that allows to seamlessly create data lake tables based on kafka topics.

This convergence signifies the necessity for real-time and data lake systems to share a common language and standards

 

In this talk, I will share Yotpo’s journey in data generation and ingestion into the lake. Beginning with the transition from operational databases to daily snapshotting for lake availability, we progressed to implementing DB-to-lake streaming using CDC and Debezium. Currently, we are advancing towards well-defined Async APIs and a unified architecture ensuring better performance and cost efficiency while treating data as a first-class citizen from the very beginning of a service design. I will delve into the key components enabling this architecture, including Kafka, Outbox pattern, Flink, Cloudevents, and AsyncApi, explaining why and how we decided to put everything together in order to execute this exciting transition.

If you think the real-time layer should cooperate better with data lake, this talk is for you.

Read more

Victor Perepelitsky

Tech Lead, Yotpo

Passionate backend tech lead and architect with a knack for creating significant impact and solving complex challenges. Currently working as the Infra Tech Lead at Yotpo. In this role, together with my amazing team, we are taking Yotpo engineering to the next level by defining standards and best practices, introducing innovative solutions, and assisting product teams with their challenges. Love sports, travelling, and sharing moments with my beloved wife and daughter.

Passionate backend tech lead and architect with a knack for creating significant impact and solving complex challenges. Currently working as the Infra Tech Lead at Yotpo. In this role, together with my amazing team, we are taking Yotpo engineering to the next level by defining standards and best practices, introducing innovative solutions, and assisting product teams with their challenges. Love sports, travelling, and sharing moments with my beloved wife and daughter.

English | Data Engineering
16:20

Big Data Processing With GPUs

In this talk, we present our successful optimization of Spark-based big data pipelines at PayPal, achieving 70% of cost reductions through strategic GPU utilization. We discuss the key challenges we encountered in our big data and machine learning domains, and how we used Spark RAPIDS to solve them. In addition, we’ll share a glimpse of the new GPU-accelerated data processing domain.

Read more

Ilay Chen

Software Engineer, PayPal

Experienced engineer with vast experience in designing, developing and optimizing big data infrastructures and machine learning solutions.

Experienced engineer with vast experience in designing, developing and optimizing big data infrastructures and machine learning solutions.

English | Keynote
16:40

How to Decipher User Uncertainty with GenAI and Vector Search

User expectations are sky-high, while at the same time users have increasing difficulty articulating their complex needs in a simple search bar on a website. This talk dives into leveraging generative AI and vector search to transform vague user queries into results the user actually wanted, even if they did not know initially what they clearly wanted. We will explore why traditional search methods fall short in grasping user intent and address the common problems users face with ambiguous search queries.

 

Learn how GenAI generates embeddings to capture the context and semantics of queries. This talk though is not only about the theory. In the talk you will be shown practical examples of how to generate embeddings, and how to set up vector indexes.

See how these advanced search capabilities can transform user interaction and, as a result, business outcomes, making user uncertainty into certainty with GenAI and vector search.

Read more

Ben Greenberg

Senior Developer Advocate, Couchbase

Ben previously spent a decade in adult education, community organizing, and non-profit management before transitioning to software development. He works as a Senior Developer Advocate at Couchbase and is a member of the board of Ruby Central. Ben actively contributes to open source projects and writes regularly on the intersection of tech, ethics, and community. Originally from Southern California and a long-time resident of New York City, Ben now lives in Israel.

Ben previously spent a decade in adult education, community organizing, and non-profit management before transitioning to software development. He works as a Senior Developer Advocate at Couchbase and is a member of the board of Ruby Central. Ben actively contributes to open source projects and writes regularly on the intersection of tech, ethics, and community. Originally from Southern California and a long-time resident of New York City, Ben now lives in Israel.

Hebrew | Data Analytics & BI
11:10

The Hitchhiker's Guide to Advanced A/B Testing Techniques

Reliable data influences your business operations at nearly every level, but what if your testing is misleading you? Join us for a deep dive into the world of A/B testing where we unravel the complexities of advanced techniques that drive better decision-making in business environments.

This 30-minute session will focus on state-of-the-art methodologies such as parallel testing, CUPED (Controlled Experiment Using Pre-Experiment Data), sequential testing, and sample ratio mismatch. Designed for data scientists, and analysts, this talk will provide actionable insights and frameworks to scale your tests, improve accuracy, and better understand the impact of your treatments.

Whether you’re looking to refine your current A/B testing practices or explore advanced approaches, this session will equip you with the knowledge to implement these techniques effectively in your A/B testing.

Read more

Allon Korem

CEO, Bell Statistics

Allon is a seasoned executive with over 10 years of experience in statistical analysis and A/B testing methodologies. He has held impactful roles at companies like Google, Wix.com, and now leads Bell Statistics as CEO. His expertise encompasses the development and refinement of A/B testing protocols and the integration of advanced statistical techniques into business strategies. Allon holds a Master's degree in Statistics from Tel Aviv University and a Bachelor's degree in Philosophy, Political Science, and Economics from The Hebrew University.

Allon is a seasoned executive with over 10 years of experience in statistical analysis and A/B testing methodologies. He has held impactful roles at companies like Google, Wix.com, and now leads Bell Statistics as CEO. His expertise encompasses the development and refinement of A/B testing protocols and the integration of advanced statistical techniques into business strategies. Allon holds a Master's degree in Statistics from Tel Aviv University and a Bachelor's degree in Philosophy, Political Science, and Economics from The Hebrew University.

Hebrew | Data Analytics & BI
11:45

Democratizing Data Pipelines: Introducing the AI-Powered ETL Assistant

This session introduces an innovative ETL assistant designed to democratize data processing and significantly reduce the barrier for handling organizational data requirements. This tool we developed, leverages AI to simplify entire Data Pipelines generation and management, making it accessible even to those with minimal data engineering skills. It integrates cutting-edge technologies like OpenMetadata, Streamlit, and the OpenAI assistant, enabling users to efficiently manage data pipelines with ease.

 

The ETL Assistant automates DDL and pipeline generation, while ensuring strict adherence to schema requirements. This automation not only significantly reduces the setup time, but also minimizes the need for specialized data engineering knowledge, thus accelerating project timelines and reducing overhead costs. Join us to discover how AI can transform the way you manage data pipelines, making these processes more intuitive and reducing bottlenecks for the organization.

Read more

Haya Axelrod Stern

Data Director, Natural Intelligence

Software developer and (Haya)Data Leader with nearly a decade in the big data field. Passionate about coding and delivering scalable data platforms and products.

Software developer and (Haya)Data Leader with nearly a decade in the big data field. Passionate about coding and delivering scalable data platforms and products.

Hebrew | Data Analytics & BI
12:05

Metric Store

Imagine this: You confidently walk into a crucial meeting armed with diligently prepared numbers from your trusted analyst. Midway through your presentation, a disruptive interruption arises. A member of the audience boldly claims to have a completely different set of numbers, challenging the accuracy and validity of your analysis…

 

In today’s world of distributed and autonomous teams, the abundance of diverse data sources has created a pressing need for a unified and reliable metrics solution. This is where the concept of a metrics store comes into play. During the presentation, I will delve deep into the strategies and provide invaluable insights into their advantages, drawbacks, complexity, and crucial considerations for implementation. Moreover, I will explore the optimal timing for adoption, effective techniques for maximizing adoption and long-term retention, and the essential maintenance practices to keep the metrics store running smoothly.

Read more

Ben Hababo

Senior BI Engineer, monday.com

Senior BI Engineer at Monday.com, leading the development and execution of cutting-edge analytics applications, ensuring their availability and performance, while also playing an active role in shaping our data strategy. My expertise in data architecture, large language models, and business intelligence enables me to enhance data operations and drive efficiency across the organization.

Senior BI Engineer at Monday.com, leading the development and execution of cutting-edge analytics applications, ensuring their availability and performance, while also playing an active role in shaping our data strategy. My expertise in data architecture, large language models, and business intelligence enables me to enhance data operations and drive efficiency across the organization.

Mickey Rozen

BI Group Lead, monday.com

Hi, I'm Mickey, and I have a deep passion for all things data. With more than 12 years of experience in diverse data areas ranging from analytics to data modeling, I currently hold a leadership position in the Business Intelligence (BI) department at monday. Throughout my career, I have worked on a variety of projects, leveraging data to drive insights and empower decision-making. Develop robust data models, implement effective analytics strategies, and collaborate with cross-functional teams.

Hi, I'm Mickey, and I have a deep passion for all things data. With more than 12 years of experience in diverse data areas ranging from analytics to data modeling, I currently hold a leadership position in the Business Intelligence (BI) department at monday. Throughout my career, I have worked on a variety of projects, leveraging data to drive insights and empower decision-making. Develop robust data models, implement effective analytics strategies, and collaborate with cross-functional teams.

Hebrew | Data Analytics & BI
12:40

Data Driven Advocacy: Using Vizualization Skills for Hasbara

Crisis communication during a complex conflict, like the one that erupted on October 7th, requires clear and concise messaging, especially when reaching an international audience.

Nir and Omer, data visualization experts, leveraged Tableau to create impactful data stories that cut through the noise and resonated with a global audience during this conflict. Their biggest challenge? Choosing the right narrative to effectively convey the story while maintaining data integrity.

 

In this talk, they’ll share their experiences in distilling complex messages into compelling visuals. By presenting real cases of visualizations developed to support Israeli advocacy during the conflict, they will provide a high-level overview of data visualization best practices and how to incorporate impactful ‘data storytelling’ in the context of Hasbara but not only.

Read more

Nir Smilga

Data Visualization Manager, monday.com

Nir Smilga is a Data Visualization Manager at Monday.com Passionate about data, he dedicates his efforts to crafting public data visualizations. Nir is recognized as one of only two Tableau Public Ambassadors in Israel and is the only Tableau Featured Author in the country. In addition to these roles, he actively engages in consulting and lectures, sharing his expertise in Tableau and data visualization

Nir Smilga is a Data Visualization Manager at Monday.com Passionate about data, he dedicates his efforts to crafting public data visualizations. Nir is recognized as one of only two Tableau Public Ambassadors in Israel and is the only Tableau Featured Author in the country. In addition to these roles, he actively engages in consulting and lectures, sharing his expertise in Tableau and data visualization

Omer Biber

Head of BI, Superplay

Omer started working with data in 2014. Since then, he has worked in Business Intelligence and Analysis at companies like Playtika, Hibob, and PayEm. Now, he is the Head of BI at Superplay. He also teaches and creates courses for the Data Analysis program at Jolt Academy. Omer won the Tableau IL Iron Viz contest in 2023.

Omer started working with data in 2014. Since then, he has worked in Business Intelligence and Analysis at companies like Playtika, Hibob, and PayEm. Now, he is the Head of BI at Superplay. He also teaches and creates courses for the Data Analysis program at Jolt Academy. Omer won the Tableau IL Iron Viz contest in 2023.

12:55

Lunch

Hebrew | Data Analytics & BI
14:00

Beyond Empowerment: Data Accuracy Challenges in Self-Service BI

Self-service BI unlocks data for everyone, but ensuring accuracy can be tricky. This session explores how a simple “BI Validated” logo tackles this challenge, addressing a common pitfall of self-service BI.

Maria Yanson

BI Team Lead, Pagaya

My journey in data began with a passion for mathematics. This passion fueled my academic choices, leading me to a major in economics and finance, followed by a degree in financial mathematics. It was this foundation that brought me to Pagaya 4.5 years ago. Pagaya offered the perfect environment to merge my love of numbers with real-world application. I started as a Data Analyst in the operations department and transitioned into a BI Developer role. This wasn't just a career move; it was an opportunity to create something new. Later on, the chance to build a BI team from scratch presented itself, and I was eager to lead the charge. Leading this team has been immensely rewarding, fostering a collaborative environment where we empower others to leverage the power of data.

My journey in data began with a passion for mathematics. This passion fueled my academic choices, leading me to a major in economics and finance, followed by a degree in financial mathematics. It was this foundation that brought me to Pagaya 4.5 years ago. Pagaya offered the perfect environment to merge my love of numbers with real-world application. I started as a Data Analyst in the operations department and transitioned into a BI Developer role. This wasn't just a career move; it was an opportunity to create something new. Later on, the chance to build a BI team from scratch presented itself, and I was eager to lead the charge. Leading this team has been immensely rewarding, fostering a collaborative environment where we empower others to leverage the power of data.

Hebrew | Data Analytics & BI
14:20

Battle of the Titans: Python vs. Tableau in Live EDA

In the rapidly evolving field of data analytics, the choice between mastering Python or Tableau remains a prevalent dilemma among professionals. This session aims to settle the debate through a dynamic, live demonstration of exploratory data analysis (EDA) with the same dataset! On one side of the ring, Efrat will master Tableau to swiftly create and manipulate visual analytics, while on the other Shuki will live code Python scientific packages, both wrestling for the best insights. Join us for a captivating session where you will judge and vote for the best EDA weapon.

Read more

Shuki Cohen

Director of Data, AI21 Labs

Seasoned Data Scientist with an emphasis on NLP, classical ML, visualization and experimentation. Driven by great passion for the field, I am inspired by unintuitive insights and inferences made by smart algorithms. In my talks, I try to convey my typical spirit and enthusiasm while delivering crisp takeaways.

Seasoned Data Scientist with an emphasis on NLP, classical ML, visualization and experimentation. Driven by great passion for the field, I am inspired by unintuitive insights and inferences made by smart algorithms. In my talks, I try to convey my typical spirit and enthusiasm while delivering crisp takeaways.

Efrat Aran

Product Data Scientist, AI21 Labs

Efrat has a BA and MA in Hebrew literature from BGU, But after a short career in the fields of NGO’s and Renewal Judaism, she successfully Retrained and became a fraud analyst at Paypal. After 3 years there she moved to Lightricks, and after additional 3 years she started to work at AI21 Labs and there she is still working as a product data scientist in the Platform team. Efrat also performs as a spoken word poet.

Efrat has a BA and MA in Hebrew literature from BGU, But after a short career in the fields of NGO’s and Renewal Judaism, she successfully Retrained and became a fraud analyst at Paypal. After 3 years there she moved to Lightricks, and after additional 3 years she started to work at AI21 Labs and there she is still working as a product data scientist in the Platform team. Efrat also performs as a spoken word poet.

Hebrew | Culture
14:55

Here, There and Everywhere: Spotting Data Opportunities 101

This talk is not about data.
It’s about a data state of mind – it’s about the thrill of discovering hidden opportunities and the ingenuity to turn them into impactful solutions. Everyday we are facing unique challenges and inefficiencies – both in our professional and personal life. Most if not all of those problems can be solved or prevented by using a data-centric mindset.

 

In this talk we will walk you through real life stories that will demonstrate how I was able to identify, develop and implement innovative solutions in a low-tech, non-data driven environment – which was eventually credited as relevant data science and analytics experience at the beginning of my career.

You will leave this talk with practical takeaways: Gain actionable strategies to identify the data opportunities, select the relevant tools to enhance efficiency and drive impactful changes in your organization.

Read more

Mor Hananovitz

Head of Data, Parazero

Head of Data and Data scientists at Parazero, IoT and signal processing expert. Community lead and Mentor in WiDS. MSc mechanical engineering, researching fluid dynamic models.

Head of Data and Data scientists at Parazero, IoT and signal processing expert. Community lead and Mentor in WiDS. MSc mechanical engineering, researching fluid dynamic models.

Hebrew | Data Analytics & BI
15:15

Revolutionizing Business Intelligence: Unlocking the Power of AI for Seamless Self-Service BI Transfer

Over the last year, AI has emerged as a transformative force, reshaping industries and redefining our approach to data. In this session, I will specify how we can leverage AI in the Business Intelligence (BI) landscape – from revolutionizing development processes and documentation to facilitating knowledge sharing. A focal point of our discussion will be the advent of user-friendly, self-service BI tools. These innovations empower users to engage with data analytics directly, simplifying complex processes and democratizing data insights.

 

Join us as I navigate through the exciting intersections of AI and BI, unveiling the future of data-driven decision-making, and walk away with fresh insights and actionable tactics to implement AI, setting a new pace for progress and innovation in your domain.

Read more

Eyal El Bahar

VP BI & Analytics, Lightricks

With over 20 years of experience in the business intelligence (BI) and analytics landscape. For the last 3.5 years, I am leading the BI and Analytics group at Lightricks. My passion lies in adopting new technologies and advancing my team both technically and in alignment with business objectives. Previously, I have taught various BI courses at leading colleges and have certified numerous professionals in the field, contributing to the development of expertise in the analytics community.

With over 20 years of experience in the business intelligence (BI) and analytics landscape. For the last 3.5 years, I am leading the BI and Analytics group at Lightricks. My passion lies in adopting new technologies and advancing my team both technically and in alignment with business objectives. Previously, I have taught various BI courses at leading colleges and have certified numerous professionals in the field, contributing to the development of expertise in the analytics community.

15:30

Coffee break

English | Data Analytics & BI
15:45

Threat Hunting Powered by Efficient and Straightforward Anomaly Detection on Your Data Lake

Effective monitoring and anomaly detection are crucial in today’s data-driven landscape. At Imperva Threat Research, our data lake serves as the backbone for a range of critical functions like threat hunting, risk analysis, and trend detection. With daily additions of terabytes of data and thousands of tables, these tasks are complex and resource-intensive.
How do you find interesting anomalies in large datasets? What baseline do you use? To address these challenges, we created a platform where users define the baseline data points they want to track over time. We applied various anomaly detection techniques and enabled push notifications for actionable monitoring and threat insights.
Our framework is both fast and easy to use as it relies on configuration files and aggregated data stored in dedicated tables. Join us to learn about our framework, including a hands-on example, and see a demo of our anomalies search engine powered by LLM.
Read more

Ori Nakar

Principal Engineer, Threat Research, Imperva

Ori Nakar is a principal cyber-security researcher, a data engineer and a data scientist at Imperva Threat Research group. Ori has a many years experience as a software engineer and engineering manager, focused on cloud technologies and big data infrastructure. At the Threat Research group Ori is responsible for the data infrastructure and involved in analytics projects, machine learning and innovation projects.

Ori Nakar is a principal cyber-security researcher, a data engineer and a data scientist at Imperva Threat Research group. Ori has a many years experience as a software engineer and engineering manager, focused on cloud technologies and big data infrastructure. At the Threat Research group Ori is responsible for the data infrastructure and involved in analytics projects, machine learning and innovation projects.

Hebrew | Data Analytics & BI
16:20

Dating With a Super Model: Why Good Prompt Engineering for Data Monitoring Requires Some Flirting

Mastering prompts for automatic monitoring of trends and data events is a fine art. This talk reveals the top 3 lessons I learned while building automatic data monitoring for my product tailored to multiple different business models and tens of use cases. And like everything in life – why is it done so much better with love.

Read more

Reut Vilek

CTO, Rupert

Holding two MSc degrees in Biology and Computer Science, I began my career as a software engineer and team lead for network classification at Cisco. Over the following years, I advanced to the role of Engineering Director and Group Manager at Nexar, where I led the development of Nexar's smart dashcam technology and AI live map solution. Currently, as the CTO at Rupert, I am on a mission to activate data through the discovery of automatic data signals and the generation of business playbooks. In addition I am a mother to baby Noga, previous Reshet Bet radio show co-host, blog writer and a former carb enthusiast.

Holding two MSc degrees in Biology and Computer Science, I began my career as a software engineer and team lead for network classification at Cisco. Over the following years, I advanced to the role of Engineering Director and Group Manager at Nexar, where I led the development of Nexar's smart dashcam technology and AI live map solution. Currently, as the CTO at Rupert, I am on a mission to activate data through the discovery of automatic data signals and the generation of business playbooks. In addition I am a mother to baby Noga, previous Reshet Bet radio show co-host, blog writer and a former carb enthusiast.

Hebrew | Data Science
11:10

Evaluating the Unseen: Semi-supervised Solutions for Unlabeled Data Analysis

In today’s complex and unstructured environment, many machine-learning problems involve unlabeled data. Evaluating online models requires innovative approaches to minimize manual labeling, which requires intensive resources and is usually not scalable.

 

In this talk, we will learn how to leverage the semi-supervised classification approach usually used for training to generate pseudo-labels for evaluation. Using pseudo-labels can enable an in-depth evaluation of online models to detect areas of underperformance or data shifts.

We will walk through the use of this approach in the identity resolution clustering task and inspire how we can use the method in other complex data science domains, such as LLM text summarization or RAG chatbots.

Get ready for a practical guide to make data evaluation simpler and more effective.

Read more

Ben Harel, PhD

Data Scientist, Riskified

Ben Harel, Ph.D., is a Data Scientist at Riskified. As a Policy Protection Data Science team member, Ben is working on models for identity resolution and abuser detection. Before working at Riskified, Ben was researching the development of a robotic sweet pepper harvester as part of his Ph.D. Ben likes cooking, surfing, and organizing things, from friend events to optimizing the order in the closet.

Ben Harel, Ph.D., is a Data Scientist at Riskified. As a Policy Protection Data Science team member, Ben is working on models for identity resolution and abuser detection. Before working at Riskified, Ben was researching the development of a robotic sweet pepper harvester as part of his Ph.D. Ben likes cooking, surfing, and organizing things, from friend events to optimizing the order in the closet.

Hebrew | Data Science
11:45

Tailor-Made LLM Evaluations: How to Create Custom Evaluations for Your LLM

In the ever-changing world of Generative AI, new LLMs are being released on a daily basis, and while there are standardized scoring approaches for evaluating them, they don’t always evaluate based on what is important to us. In this talk, we will go over the two main approaches to evaluate LLMs – Benchmarking and LLM-as-a-judge. We will discuss which one to choose and how to create custom evaluations that suit our own use cases. Lastly, we will go over a set of best practices on how to create the best possible evaluation that produces an objective and deterministic score.

Read more

Linoy Cohen

Data Scientist, Intuit

Linoy Cohen is a Data Scientist at Intuit in the NLP team. As part of her job, she is responsible for creating automatic evaluations for LLM’s that provide an objective method to measure the capabilities of LLM’s based on specific custom criteria and needs.

Linoy Cohen is a Data Scientist at Intuit in the NLP team. As part of her job, she is responsible for creating automatic evaluations for LLM’s that provide an objective method to measure the capabilities of LLM’s based on specific custom criteria and needs.

English | Data Science
12:05

Correlation Sucks - Long Live Causality! Mastering Causal Inference in Data Science

In today’s data-driven world, distinguishing correlation from causation is a competitive advantage. Businesses using causal inference can attribute outcomes to actions, leading to more effective strategies and clearer insights.

 

This session delves into the realm of causal inference, exploring foundational concepts like potential outcomes, causal graphs, and the challenges of confounders, colliders, and mediators. Attendees will learn robust methodologies for establishing causality, from A/B testing to advanced techniques like IPTW (Inverse Probability of Treatment Weighting). We’ll showcase real-world applications with case studies in product development and marketing strategies, demonstrating how causal inference informs decision-making in tech industries.

 

By the end of this session, participants will understand how to critically appraise and construct causal hypotheses, turning complex data into actionable insights for strategic advantage.

Read more

Amit Sasson

Causal Inference expert, Bell Statistics

Amit is a Causal Inference expert, an experienced statistician and a proud winner of the #2020EpiCookieChallenge. She has a strong theoretical background and vast experience in applying statistical models to real-world problems. Amit currently leads all causal analysis initiatives at Bell, including the strategic application of Marketing Mix Models (MMM), Geo Tests, and other advanced techniques to refine marketing strategies, optimize resource allocation, and deliver data-driven insights that directly impact clients' bottom line.

Amit is a Causal Inference expert, an experienced statistician and a proud winner of the #2020EpiCookieChallenge. She has a strong theoretical background and vast experience in applying statistical models to real-world problems. Amit currently leads all causal analysis initiatives at Bell, including the strategic application of Marketing Mix Models (MMM), Geo Tests, and other advanced techniques to refine marketing strategies, optimize resource allocation, and deliver data-driven insights that directly impact clients' bottom line.

English | Data Science
12:40

Learning the Ropes of Synthetic Data

This talk will cover the basics and applications of synthetic data across various fields, emphasizing its importance in maintaining privacy while retaining data utility. It will start with a definition of synthetic data, its creation process, and how it differs from traditional de-identification techniques. The talk will then explore applications for tabular data use cases using an open data set to illustrate privacy and utility considerations.

Read more

Noa Zamstein, PhD

Senior Data Science Researcher, Earnix

Noa Zamstein is a senior data science researcher at Earnix Ltd. Previously, she was the senior data scientist at MDClone, where she contributed to the development of the synthetic data engine and its implementation at customers sites. Noa holds a PhD in computational chemistry from the Weizmann Institute of Science.

Noa Zamstein is a senior data science researcher at Earnix Ltd. Previously, she was the senior data scientist at MDClone, where she contributed to the development of the synthetic data engine and its implementation at customers sites. Noa holds a PhD in computational chemistry from the Weizmann Institute of Science.

12:55

Lunch

Hebrew | Data Science
14:00

LLMs and Knowledge Graphs: A Case Study in Blue(y)

In this talk, we will explore how LLMs and knowledge graphs can be integrated to enhance accuracy and relevance over naïve RAG. Using the TV show “Bluey” as a proof of concept, we’ll illustrate the workflows for generating a knowledge graph from unstructured data and designing an ontology and extraction pipeline. We will also discuss strategies to leverage the knowledge graph to improve the contextual understanding, accuracy and traceability of LLM responses, highlighting applications in various domains.

Read more

Stav Shamir

Team Lead, 2bprecise

Born and raised in Eilat, BSc and MSc in biotechnology engineering in BGU. Developing software and data enthusiast in the past 7 years. Husband and father of 2.

Born and raised in Eilat, BSc and MSc in biotechnology engineering in BGU. Developing software and data enthusiast in the past 7 years. Husband and father of 2.

Hebrew | Data Science
14:20

Beyond Opt-Outs: Quantifying User Notification Harm

This talk presents a holistic framework for quantifying user notification harm, developed through a cross-functional collaboration at Google spanning data science, user experience research and stakeholders from Google Photos, Google Maps, Google Search and Youtube.

Previously, user notification harm was something measured via a balance between clicks and opt-outs, which are both measurable qualities, but do not clearly express the end-user’s experience or motivations. As opt-outs are infrequent, relying on them as a measure of notification harm is ineffective in A/B testing. Furthermore, opt-outs can underestimate harm in users who tolerate or ignore unwanted notifications without opting out. To create a positive digital environment, we need a scalable way to measure and understand the potential harm of poorly designed or excessive notifications.

We combined quantitative and qualitative approaches to uncover the root causes of notification dissatisfaction. This involved feature engineering, ML modeling, and analyzing user feedback – particularly free-text survey responses processed with LLM technology – to better understand our end-user experience and motivations. The research revealed key indicators of user harm from notifications, giving Google product teams tools to refine their strategies and create a more positive and respectful user experience.

Read more

Orna Amir, PhD

Growth and Notifications, Data Science Lead, Google

Orna Amir leads the Data Science team in Google's Growth and Notifications Teams. Her work leverages modeling, analytics, and A/B testing to enhance notification quality and growth for Google Photos, Google Maps, and YouTube. Previously at Waze, she developed DL models and monitoring methods to improve ETA and navigation. Orna holds a Ph.D. in Applied Mathematics and brings over 15 years of experience in machine learning, statistical modeling, and optimization across various industries.

Orna Amir leads the Data Science team in Google's Growth and Notifications Teams. Her work leverages modeling, analytics, and A/B testing to enhance notification quality and growth for Google Photos, Google Maps, and YouTube. Previously at Waze, she developed DL models and monitoring methods to improve ETA and navigation. Orna holds a Ph.D. in Applied Mathematics and brings over 15 years of experience in machine learning, statistical modeling, and optimization across various industries.

Hila Kantor

Senior Data Scientist, Google

Hila Kantor is a data science tech lead on Google's Notifications team, driving initiatives in digital wellbeing and the team success metrics. With 6.5 years at Google, she specializes in notification value / harm analysis, measurement frameworks, and product analytics using data science and big data techniques. Prior to Google, she led product analytics and BI consulting at Sisense. Hila holds an MSc in Technology and Information Systems specializing in data science and business analytics.

Hila Kantor is a data science tech lead on Google's Notifications team, driving initiatives in digital wellbeing and the team success metrics. With 6.5 years at Google, she specializes in notification value / harm analysis, measurement frameworks, and product analytics using data science and big data techniques. Prior to Google, she led product analytics and BI consulting at Sisense. Hila holds an MSc in Technology and Information Systems specializing in data science and business analytics.

Hebrew | Data Science
14:55

Navigating the Uncharted: Ensuring Prompt Quality in the Age of Language Models

In today’s era dominated by large language models, the quality of prompts is crucial for effective utilization of these powerful tools. This talk, led by Ortal, a Senior Researcher specializing in Natural Language Processing (NLP) at Gong’s AI division, will delve into the challenges of understanding prompt impact, navigating upgrades to foundation models, and selecting the most suitable models for specific tasks. I will share strategies for evaluating prompt performance, discuss methods to identify and address pitfalls, and explore decision-making processes in this ever-evolving landscape. Join me for insights into prompt quality assurance in the age of language models.

Read more

Ortal Ashkenazi

Data Scientist, Gong

Ortal is a Senior Researcher specializing in Natural Language Processing (NLP) in Gong's AI division. She holds an MSc from the Technion and shares her experiences in conferences and meetups.

Ortal is a Senior Researcher specializing in Natural Language Processing (NLP) in Gong's AI division. She holds an MSc from the Technion and shares her experiences in conferences and meetups.

Hebrew | Culture
15:15

Redefining Agile for Data Science: Navigating Uncertainty with Explicit Planning

“Agile methodologies weren’t built for data science teams and projects…” This sentiment resonates with many data scientists. The belief is that the exploratory and uncertain nature of data science clashes with Agile’s short-cycle, flexible approach, creating inefficiencies and ambiguities.

In this talk, I will present the challenges of applying Agile’s iterative cycles to data science projects without compromising their inherently exploratory nature. By emphasizing explicit task definitions and meticulous planning, this approach transforms broad goals into specific, measurable actions, ensuring clarity and focus throughout the research process.

This practical framework enhances both individual and team efficiency, fostering higher transparency, collaboration, and productivity. This talk is essential for team leads and individual contributors seeking to streamline their workflow and deliver more consistent, reliable results.

Read more

Andres Asaravicius

AI & ML Expert

Andres has more than 10 years of experience in Data Science, leading data science and multidisciplinary teams. Throughout his career, he has been instrumental in building robust data science infrastructures and spearheading end-to-end research projects and ML products. Andres is passionate about leveraging machine learning technology to transform complex data into actionable insights. His expertise spans developing cutting-edge machine learning solutions, mentoring teams, and implementing Agile methodologies in Data Science teams. In addition to his professional pursuits, Andres is an amateur basketball player who achieved the unique statistic of having more fouls than points during the last season.

Andres has more than 10 years of experience in Data Science, leading data science and multidisciplinary teams. Throughout his career, he has been instrumental in building robust data science infrastructures and spearheading end-to-end research projects and ML products. Andres is passionate about leveraging machine learning technology to transform complex data into actionable insights. His expertise spans developing cutting-edge machine learning solutions, mentoring teams, and implementing Agile methodologies in Data Science teams. In addition to his professional pursuits, Andres is an amateur basketball player who achieved the unique statistic of having more fouls than points during the last season.

15:30

Coffee break

Hebrew | Data Science
15:45

I Want to Build a RAG System, Now What?

Many organizations are looking into building a RAG system either for internal use or as features in their products. In this session, we will discuss the engineering and data science involved in building RAG systems in the real world. We will also share key lessons learned from the past two years, working with over 5,000 customers to develop various AI products.

Read more

Roy Miara

Engineering Manager, Generative Search, Pinecone

Roy leads the Generative AI team at Pinecone, and have been working in the last 2 years on generative search and generation augmentation, releasing the Canopy open source and working on new frontier of knowledge intensive GenAI products. Previously, Roy lead the data engineering group at Explorium and other startups in the field of data engineering and data science.

Roy leads the Generative AI team at Pinecone, and have been working in the last 2 years on generative search and generation augmentation, releasing the Canopy open source and working on new frontier of knowledge intensive GenAI products. Previously, Roy lead the data engineering group at Explorium and other startups in the field of data engineering and data science.

Hebrew | Data Science
16:20

Transforming Medical Records Into a Heart Attack Prediction Model

Every 34 seconds, a US citizen dies from cardiovascular disease (CVD), often preventable with early detection. Despite 47% of adults having high blood pressure, over 80% are not managing it. Hello Heart aims to bridge this gap by collecting daily blood pressure readings, medication intake, and symptoms through a mobile app. We use this data and clinical records to train ML models that alert users at risk of heart attacks or strokes.

In this talk, I’ll discuss transforming raw Electronic Health Records (EHR) into aggregated features for training and inference. EHRs, while valuable for research and model development, pose significant challenges. Key considerations for the data representation include the ideal modeling approach, hardware resources, data sparsity, and label validation.

Whether you’re a data scientist, engineer, or product manager, these decisions are crucial for extracting valuable insights from raw medical data and ensuring a proof-of-concept analysis reaches production. Join me to explore our journey from raw data to prediction and prevention!

Read more

Shiri Gaber

Senior Data Scientist, Hello Heart

Shiri is a senior data scientist at Hello Heart, a startup whose goal is to empower people to understand and improve their heart health using technology and behavioral science. With over 10 years industry experience, Shiri has worked at several startups as well as large corporations. Her academic background includes BSc in Physics and MSc in Computational Neuroscience. She enjoys coming up with solutions to problems that have real-world applications, and working as part of a team of professionals she can learn from.

Shiri is a senior data scientist at Hello Heart, a startup whose goal is to empower people to understand and improve their heart health using technology and behavioral science. With over 10 years industry experience, Shiri has worked at several startups as well as large corporations. Her academic background includes BSc in Physics and MSc in Computational Neuroscience. She enjoys coming up with solutions to problems that have real-world applications, and working as part of a team of professionals she can learn from.

Hebrew | DATA ANALYTICS & BI
11:10

Discover the Modern Way to Build Real-Time Analytics Solutions at Any Scale

Delve into the realm of big data analytics, with a specific focus on the challenges inherent in large-scale Real-time Analytics. Explore how contemporary technologies like SingleStore offer potential solutions to these complexities.

Walk away with actionable strategies to overcome common big data hurdles, drive business value and discover how innovative architecture and advanced features can enhance your analytics capabilities.

Key topics to be covered include:
  • Strategies for achieving Real-time data freshness in analytics.
  • How analytical queries can deliver sub-second response times, even when dealing with many billions of records with highly concurrent queries.
  • Simplifying architecture by leveraging the flexibility of schema, semi-structured data (JSON and BSON), and the capabilities of a relational database management system (RDBMS) in the same platform.
  • Addressing data discrepancies at their root cause.
  • Identifying the optimal scenarios for utilizing SingleStore, Elasticsearch, MongoDB, and Big Query.
  • Effectively combining vector similarity search with analytics, RAG, and hybrid search for more accurate GenAI results.
  • Real-life production use cases will also be discussed.
Read more

Golan Nahum

CEO, Twingo

Golan is the CEO and founder at Twingo, and is an expert data leader with 20 years of experience in database, Big Data, and project management. Golan started as a DBA in SRL, where he managed a group of 40 DBA experts and managed large, complex projects for Microsoft Israel. The vast experience Golan has with Big Data solutions and architecture makes him an expert in the field. Golan holds both a BA degree in Computer Science and an MBA in business with a specialization in High-tech Management.

Golan is the CEO and founder at Twingo, and is an expert data leader with 20 years of experience in database, Big Data, and project management. Golan started as a DBA in SRL, where he managed a group of 40 DBA experts and managed large, complex projects for Microsoft Israel. The vast experience Golan has with Big Data solutions and architecture makes him an expert in the field. Golan holds both a BA degree in Computer Science and an MBA in business with a specialization in High-tech Management.

Ilya Gulman

CTO, Twingo

Ilya oversees the training, high-level consulting, employee induction, and professional workshops. He is an expert Big Data architect and has vast experience in software development, databases, and Big Data. Ilya specializes in HP Vertica and holds Expert Trainer qualifications. Ilya has delivered and managed highly complex Big Data projects. He holds a degree in Computer Science from Tel Aviv University. Ilya has successfully completed the AWS Certification requirements and has achieved his: AWS Certified Big Data – Specialty.

Ilya oversees the training, high-level consulting, employee induction, and professional workshops. He is an expert Big Data architect and has vast experience in software development, databases, and Big Data. Ilya specializes in HP Vertica and holds Expert Trainer qualifications. Ilya has delivered and managed highly complex Big Data projects. He holds a degree in Computer Science from Tel Aviv University. Ilya has successfully completed the AWS Certification requirements and has achieved his: AWS Certified Big Data – Specialty.

11:45

Accelerate Data Pipeline Development Time: Learn How to Unleash Rivery’s Gen AI for a 20X Leap

Even as data teams remain lean in 2024, data engineers are still expected to swiftly deliver data for various use cases. Adding new data sources and updating existing ones consumes nearly half of a data engineer’s time, hindering your organization’s data and AI-led goals. Rivery’s modern data platform solves this issue across all your data sources with an innovative blueprint engine and generative AI. Join this session to learn how to overcome unscalable data pipeline challenges and unlock the benefits of all of your Data.

Read more

Aviv Noy

Co-Founder, CPO & CTO, Rivery

Aviv Noy is the Co-Founder, CPO & CTO at Rivery. Prior to that, Aviv held various positions as a leading tech manager including Director of Product Management, Project Manager, and Big Data System Architect. Aviv is passionate about team building, creating a builder culture, technology, and products. Putting these together, Aviv likes solving complex challenges to make customers happy, especially by finding optimal solutions that combine ease of use and scale. He founded Rivery on the belief that data professionals shouldn't repeat data pipelines work and instead, spend their time adding more value to the business by focusing on the organization's unique business logic.

Aviv Noy is the Co-Founder, CPO & CTO at Rivery. Prior to that, Aviv held various positions as a leading tech manager including Director of Product Management, Project Manager, and Big Data System Architect. Aviv is passionate about team building, creating a builder culture, technology, and products. Putting these together, Aviv likes solving complex challenges to make customers happy, especially by finding optimal solutions that combine ease of use and scale. He founded Rivery on the belief that data professionals shouldn't repeat data pipelines work and instead, spend their time adding more value to the business by focusing on the organization's unique business logic.

12:05

TBD

English
12:40

A Brave New World: How New Lineage Technology Can Reduce Data Spend 40%

With Data increasingly viewed as a strategic asset, the ability to track data lineage is key for effective data management. The problem is that traditional lineage solutions are falling short in today’s complex data ecosystems.

 

In this presentation we will detail a multi-layered data lineage approach that delivers full visibility and insights for data management and optimization.

 

The Key Takeaways for Attendees Include:

 

  • How data usage analytics will help you figure out which data products are getting used, and how much, and which ones are just sitting there collecting dust. 
  • How to use data cost visibility to get a clear picture of which data products are costing you big $$$, to optimize budgets and cut wasteful spending.
  • Why Data product ownership attribution is essential to ensure accountability and enhanced collaboration. 
  • How full data lineage transparency shines a bright light on your data’s entire journey to properly govern and optimize every step.

 

This presentation is designed for data managers, and any professionals involved in data strategy and implementation looking to enhance their data management practices.

Read more

Guy Biecher

Co-Founder & CTO, Seemore Data

Guy Biecher is a seasoned data professional and visionary co-founder and Chief Technology Officer at Seemore Data in Tel Aviv, Israel. With a career dedicated to enhancing data value within organizations, Guy co-founded Seemore Data to help data leaders maximize ROI and transform data from a cost center into a growth engine. As CTO, he drives the development of Seemore Data’s full lineage visibility and root-cause analysis of data costs, enabling informed decision-making for business growth. Previously, Guy served as VP of Engineering at Aggua, developing a scalable data management application, and as Head of Data Engineering at PayU, where he led the creation of a robust Data Mesh environment supporting online payment processing. Passionate about leveraging data for organizational growth, Guy invites fellow data enthusiasts to connect and explore collaborative opportunities at guy@seemoredata.io or on LinkedIn.

Guy Biecher is a seasoned data professional and visionary co-founder and Chief Technology Officer at Seemore Data in Tel Aviv, Israel. With a career dedicated to enhancing data value within organizations, Guy co-founded Seemore Data to help data leaders maximize ROI and transform data from a cost center into a growth engine. As CTO, he drives the development of Seemore Data’s full lineage visibility and root-cause analysis of data costs, enabling informed decision-making for business growth. Previously, Guy served as VP of Engineering at Aggua, developing a scalable data management application, and as Head of Data Engineering at PayU, where he led the creation of a robust Data Mesh environment supporting online payment processing. Passionate about leveraging data for organizational growth, Guy invites fellow data enthusiasts to connect and explore collaborative opportunities at guy@seemoredata.io or on LinkedIn.

12:55

Lunch

English | Data Science
14:00

Deep Entity Matching for Improved E-commerce Experience

Connecting buyers and sellers in a meaningful and effective way is a critical challenge for all e-commerce marketplaces. Sellers often list items with incomplete and noisy information, complicating the process of matching them with potential buyers.

In this talk we’ll explore how we can overcome these obstacles to deliver more relevant results for buyers, and facilitate transactions for sellers. We developed an entity matching framework that integrates information retrieval and deep learning to accurately identify listed items and link them to their corresponding catalog products. By the end of this session, you will be able to apply this approach in your own domain, enhancing the overall e-commerce user experience with a quick and flexible solution.

Read more

Nati Ghatan

Applied Researcher, eBay

Nati is an applied researcher at eBay, where he currently specializes in entity matching to enhance user experience for buyers and sellers. Prior to eBay, he gained years of experience leading data science research efforts to tackle interesting challenges in a diverse range of domains - from gene discovery and neural encoding to scalable education and environmental solutions. Holding an M.Sc. in Computational Neuroscience from the Weizmann Institute of Science, Nati is a firm believer in the value of making science understandable and accessible to all. He taught at the Davidson Institute of Science Education, authored numerous articles and blogs, and regularly delivers community lectures about a variety of scientific subjects. He takes pleasure in the challenge of conveying complex concepts with a simple and compelling narrative, and making them accessible and engaging for all.

Nati is an applied researcher at eBay, where he currently specializes in entity matching to enhance user experience for buyers and sellers. Prior to eBay, he gained years of experience leading data science research efforts to tackle interesting challenges in a diverse range of domains - from gene discovery and neural encoding to scalable education and environmental solutions. Holding an M.Sc. in Computational Neuroscience from the Weizmann Institute of Science, Nati is a firm believer in the value of making science understandable and accessible to all. He taught at the Davidson Institute of Science Education, authored numerous articles and blogs, and regularly delivers community lectures about a variety of scientific subjects. He takes pleasure in the challenge of conveying complex concepts with a simple and compelling narrative, and making them accessible and engaging for all.

14:20

TBD

English | Data Engineering
14:55

How Similarweb Serves 100s of TBS to Their Worldwide Users in Milliseconds

If you want to scare a Data Engineer with four words, ‘big data, high concurrency’ will probably do it. As data moved from the realm of BI reporting to being a customer-facing commodity, serving huge volumes of data to thousands of unforgiving app users is no small challenge. In this session, Yoav Shmaria, VP R&D SaaS Platform at Similarweb will share how, using Firebolt, they serve data about millions of websites to their worldwide customers with consistent millisecond response times. He’ll demo how their newest market tool takes keyword analysis to the next level – running complex queries on TB-scale datasets instantly.

Read more

Yoav Shmaria

VP R&D SaaS Platform, Similarweb

Yoav is currently the VP R&D, SaaS Platform at Similarweb. Prior to their current role, Yoav was a Co-Founder at Marvilix and served as a Captain (reserve) in the Israel Defense Forces. Yoav also has experience as an R&D Team Leader and Frontend Engineer. Yoav graduated from Technion - Israel Institute of Technology with a Bachelor of Science (BSc) in Industrial Engineering.

Yoav is currently the VP R&D, SaaS Platform at Similarweb. Prior to their current role, Yoav was a Co-Founder at Marvilix and served as a Captain (reserve) in the Israel Defense Forces. Yoav also has experience as an R&D Team Leader and Frontend Engineer. Yoav graduated from Technion - Israel Institute of Technology with a Bachelor of Science (BSc) in Industrial Engineering.