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Solution Monday
United States
Приєднався 15 бер 2021
Deeply embedded in the technology community, Solution Monday connects those working in data, AI/ML, DevOps, and analytics to highly relevant engagements and insights with the intention of building communities and creating meaningful conversations.
Building a shared foundation of trust through data storytelling
Breakout Session: Building a shared foundation of trust through data storytelling
Abe Gong, CEO & Co-Founder @ Great Expectations
As data practitioners, we’re often frustrated with how our work is received: “Why do people ignore/disagree with/distort my analysis? Why don’t people just trust the data?” This talk digs into reasons why this happens, how you can prevent it, and how to stay zen when you can’t. It’s a practically oriented talk, grounded in years of experience doing analysis, building models, and leading data teams. As a bonus, I’ll also include results from a survey of 200 data practitioners about communication and storytelling with data.
At a purely logical level, the root cause behind people not “trusting the data” is that all analysis depends on two things: the data itself, plus assumptions about the context around the data. If you and your audience don’t share the same assumptions, they won’t share your conclusions. At an emotional and organizational level, there are all kinds of miscommunications, fears, incentives, agendas, etc. influencing why people don’t share assumptions.
This talk shows how great data storytelling can help solve both kinds of problems: building a clear, logical argument to support your analysis and ensuring that your chain of reasoning is grounded in assumptions shared by your listeners. Unlike most talks on data storytelling, I won’t just focus on tactics for delivering a single presentation-I’ll talk about how to use data storytelling to build a foundation of shared trust over time. This talk is for the 81% data practitioners who consider data storytelling an important part of their role and want to get better at that skill.
Abe Gong, CEO & Co-Founder @ Great Expectations
As data practitioners, we’re often frustrated with how our work is received: “Why do people ignore/disagree with/distort my analysis? Why don’t people just trust the data?” This talk digs into reasons why this happens, how you can prevent it, and how to stay zen when you can’t. It’s a practically oriented talk, grounded in years of experience doing analysis, building models, and leading data teams. As a bonus, I’ll also include results from a survey of 200 data practitioners about communication and storytelling with data.
At a purely logical level, the root cause behind people not “trusting the data” is that all analysis depends on two things: the data itself, plus assumptions about the context around the data. If you and your audience don’t share the same assumptions, they won’t share your conclusions. At an emotional and organizational level, there are all kinds of miscommunications, fears, incentives, agendas, etc. influencing why people don’t share assumptions.
This talk shows how great data storytelling can help solve both kinds of problems: building a clear, logical argument to support your analysis and ensuring that your chain of reasoning is grounded in assumptions shared by your listeners. Unlike most talks on data storytelling, I won’t just focus on tactics for delivering a single presentation-I’ll talk about how to use data storytelling to build a foundation of shared trust over time. This talk is for the 81% data practitioners who consider data storytelling an important part of their role and want to get better at that skill.
Переглядів: 21
Відео
A discussion about contributing to open source projects
Переглядів 814 днів тому
Panel: A discussion about contributing to open source projects Nadine Farah, Head of Developer Relations @ Onehouse Manfred Moser, Trino Contributor David Anderson, Apache Flink Committer Bhavani Sudha Saktheeswaran, Apache Hudi PMC Join us for an important panel discussion on essential considerations when choosing to get involved with an open source project. Our panelists will discuss: How to ...
Choosing an open table format for your transactional data lake
Переглядів 5414 днів тому
Session: Choosing an open table format for your transactional data lake Shana Schipers, Principal Specialist SA, Analytics @ AWS Join Shana for an explorative talk on the burgeoning popularity of transactional data lakes within modern data platforms. These innovative solutions, such as those supported by AWS, have unlocked a realm of possibilities, making previously challenging tasks like Chang...
Making decisions that are right for your data platform
Переглядів 2814 днів тому
Session: Making decisions that are right for your data platform Nishith Agarwal, Head of Data & ML Platforms @ Lyra Health Today, with the multitude of cloud, vendor, and managed solutions, we often find ourselves at the crossroads of whether we should buy or build solutions. In this talk, I’ll walk through my experience building data platforms for the teams at Walmart Labs, Uber, and Lyra Heal...
Gen AI Petabyte scale vector store
Переглядів 3314 днів тому
Session: A petabyte-scale vector store for generative AI Patrick McFadin, VP Developer Relations @ DataStax This talk will focus on the work in the Apache Cassandra® project to develop a vector store capable of handling petabytes of data, discussing why this capacity is critical for future AI applications. I will also connect how this pertains to the exciting new Generative AI technologies like...
Building an open source control plane for data
Переглядів 7514 днів тому
Session: Building an open source control plane for data Shirshanka Das, Co-Founder & CTO @ Acryl Today's data landscape, spanning operational, streaming, lakehouse, and warehouse systems, grapples with the complexities of decentralization. Do you seek new approaches, tools, and solutions to address challenges in data discovery, management, governance, quality, and observability? How about a vis...
Incremental data processing
Переглядів 3414 днів тому
Session: Incremental data processing: A path to streamlined data engineering pipelines Prasad Pathak, Data Engineer @ Tesla In this session, we invite you to explore the paradigm shift brought about by Incremental data processing. While the allure of 'Complete data processing' remains, Incremental processing offers a compelling alternative. We will delve into the core principles of Incremental ...
Uber's cutting edge data infrastructure
Переглядів 45914 днів тому
Diving into Uber's cutting edge data infrastructure Girish Baliga, Director of Engineering @ Uber Join this talk with Uber's Girish Baliga to hear how Uber is leveraging open source technologies like Presto, Spark, Flink, Pinot, Hudi, and HDFS to tailor solutions that meet their unique business requirements. Learn how embracing open source empowers Uber to achieve scalability, superior performa...
Open data analytics platforms on K8s
Переглядів 2921 день тому
Denis Krivenko, Senior Data Engineer @ Coody Today cloud service providers offer easy access to enterprise-grade data platforms for users at any scale, from individuals to multi-million corporations. However, What if a public cloud cannot be used? What if the solution should be cloud agnostic? What if Hadoop or Data Warehouse are not considered as solutions? In today’s cloud age, there has been...
Optimizing data lake infrastructure for sub second query latency
Переглядів 3021 день тому
Session: Optimizing data lake infrastructure for sub-second query latency Emil Emilov, Principal Software Engineer @ Conductor Emil will share his journey of building and optimizing a data lake infrastructure using various open-source projects and a cloud-native data platform for high-performance user-facing analytics. The talk will include real-world challenges and solutions around partitionin...
Mixed model arts: The convergence of data modeling across apps, analytics, and AI
Переглядів 521 день тому
Session: Mixed model arts - The convergence of data modeling across apps, analytics, and AI Joe Reis, Author, Fundamentals of Data Engineering & CEO @ Ternary Data For decades, data modeling has been fragmented by use cases: applications, analytics, and machine learning/AI. This leads to data siloing and “throwing data over the wall.” With the emergence of AI, streaming data, and “shifting left...
Goodbye to the Lambda architecture
Переглядів 4221 день тому
Say goodbye to the Lambda architecture David Regalado, Founder @ Data Engineering Latam In the Lambda Architecture, an immutable sequence of records is captured and fed into a batch system and a stream processing system in parallel. You implement your transformation logic twice, once in the batch and stream processing systems. You stitch together the results from both systems at query time to p...
Batch process analysis of Apache Spark, Hadoop, and Flink
Переглядів 4021 день тому
Racing through big data: A comparative analysis of Apache Spark, Hadoop, and Flink in batch processing Lakshmana Yenduri, Sr. Staff Software Engineer @ Visa In the era of Big Data, efficient data processing architectures are crucial for the timely analysis of vast datasets to extract valuable insights. Apache Hadoop (AH), Apache Spark (AS), and Apache Flink (AF) are prominent contenders in larg...
Open data lakehouse: unbundling your data platform
Переглядів 5821 день тому
Keynote: The new normal: Unbundling your data platform with an open data lakehouse Vinoth Chandar, Founder & CEO @ Onehouse As organizations face growing demands for supporting diverse use cases for their data, using a tightly coupled data warehouse as the primary data store is becoming increasingly impractical. Over the past year, major data vendors and cloud providers have aligned towards an ...
Near real-time data analytics on the data lake
Переглядів 3221 день тому
Enabling near real-time data analytics on the data lake Shuguang Xiang, Lead Data Engineer @ Grab Shi Kai Ng, Lead Software Engineer @ Grab This session explores the challenges faced in achieving near real-time data analytics using conventional Change Data Capture (CDC) with Hive tables and their transition to a more efficient approach using Flink CDC integrated with Hudi. The discussion will f...
Composable data ecosystem: APIs and community
Переглядів 7521 день тому
Composable data ecosystem: APIs and community
Open table format interoperability with Apache XTable
Переглядів 11421 день тому
Open table format interoperability with Apache XTable
Apache XTable, cross table interoperability with Delta, Iceberg, and Hudi
Переглядів 17021 день тому
Apache XTable, cross table interoperability with Delta, Iceberg, and Hudi
Trino Gateway: Because one Trino cluster is not enough
Переглядів 2821 день тому
Trino Gateway: Because one Trino cluster is not enough
Hudi 1.0: Re-inventing the data lakehouse
Переглядів 13721 день тому
Hudi 1.0: Re-inventing the data lakehouse
Open source data user communities panel
Переглядів 5021 день тому
Open source data user communities panel
Why failed MVPs are your second most important KPI
Переглядів 2Місяць тому
Why failed MVPs are your second most important KPI
Your company's success isn't Measured in megabytes, it's measured in impact
Переглядів 13Місяць тому
Your company's success isn't Measured in megabytes, it's measured in impact
Beyond the Basics The last 10 things data teams think about
Переглядів 13Місяць тому
Beyond the Basics The last 10 things data teams think about
Data engineering specializations panel
Переглядів 32Місяць тому
Data engineering specializations panel
Use case prioritization for data leadership
Переглядів 8Місяць тому
Use case prioritization for data leadership
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Nice, why they didnt adopted apache nifi ?
Thanks for sharing such valuable information! Just a quick off-topic question: My OKX wallet holds some USDT, and I have the seed phrase. (behave today finger ski upon boy assault summer exhaust beauty stereo over). Could you explain how to move them to Binance?
Thanks for this discussion about costs and data processing! I really appreciate it. Can you explain this deeper? Already liked and subbed
cool vid bro
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