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Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagementDatalakes are notoriously complex. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data.
Summary A data lakehouse is intended to combine the benefits of datalakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). Datalakes are notoriously complex. To start, can you share your definition of what constitutes a "Data Lakehouse"?
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement Introducing RudderStack Profiles. RudderStack Profiles takes the SaaS guesswork and SQL grunt work out of building complete customer profiles so you can quickly ship actionable, enriched data to every downstream team.
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagementDatalakes are notoriously complex. Datalakes in various forms have been gaining significant popularity as a unified interface to an organization's analytics. When is Fabric the wrong choice?
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement Dagster offers a new approach to building and running data platforms and data pipelines. Datalakes are notoriously complex. Go to dataengineeringpodcast.com/dagster today to get started.
In this episode Yingjun Wu explains how it is architected to power analytical workflows on continuous data flows, and the challenges of making it responsive and scalable. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagementDatalakes are notoriously complex.
In this episode Pete Hunt, CEO of Dagster labs, outlines these new capabilities, how they reduce the burden on data teams, and the increased collaboration that they enable across teams and business units. Datalakes are notoriously complex. Go to dataengineeringpodcast.com/dagster today to get started.
In this episode Kevin Liu shares some of the interesting features that they have built by combining those technologies, as well as the challenges that they face in supporting the myriad workloads that are thrown at this layer of their data platform. Can you describe what role Trino and Iceberg play in Stripe's data architecture?
He highlights the role of data teams in modern organizations and how Synq is empowering them to achieve this. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagementDatalakes are notoriously complex. Can you describe what Synq is and the story behind it?
In this episode she shares the practical steps to implementing a data governance practice in your organization, and the pitfalls to avoid. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagementDatalakes are notoriously complex.
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement This episode is supported by Code Comments, an original podcast from Red Hat. Datalakes are notoriously complex. My thanks to the team at Code Comments for their support.
In this episode Artyom Keydunov, creator of Cube, discusses the evolution and applications of the semantic layer as a component of your data platform, and how Cube provides speed and cost optimization for your data consumers. Datalakes are notoriously complex. Your first 30 days are free!
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagementDatalakes are notoriously complex. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data.
Colleen Tartow has worked across all stages of the data lifecycle, and in this episode she shares her hard-earned wisdom about how to conduct an AI program for your organization. Datalakes are notoriously complex. What do you have planned for the future of your work at VAST Data? Your first 30 days are free!
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement Dagster offers a new approach to building and running data platforms and data pipelines. Datalakes are notoriously complex. Go to dataengineeringpodcast.com/dagster today to get started.
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement This episode is supported by Code Comments, an original podcast from Red Hat. Datalakes are notoriously complex. Datalakes are notoriously complex.
In this episode Andrew Jefferson explains the complexities of building a robust system for data sharing, the techno-social considerations, and how the Bobsled platform that he is building aims to simplify the process. What is the current state of the ecosystem for data sharing protocols/practices/platforms?
In this episode Tasso Argyros, CEO of ActionIQ, gives a summary of the major epochs in database technologies and how he is applying the capabilities of cloud data warehouses to the challenge of building more comprehensive experiences for end-users through a modern customer data platform (CDP).
Summary Data lakehouse architectures are gaining popularity due to the flexibility and cost effectiveness that they offer. The link that bridges the gap between datalake and warehouse capabilities is the catalog. Datalakes are notoriously complex. What is involved in integrating Nessie into a given data stack?
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement This episode is brought to you by Datafold – a testing automation platform for data engineers that prevents dataquality issues from entering every part of your data workflow, from migration to dbt deployment.
In this episode Tobias Macey shares his thoughts on the challenges that he is facing as he prepares to build the next set of architectural layers for his data platform to enable a larger audience to start accessing the data being managed by his team. Datalakes are notoriously complex.
In this episode he explains the data collection and preparation process, the collection of model types and sizes that work together to power the experience, and how to incorporate it into your workflow to act as a second brain. Datalakes are notoriously complex. Datalakes are notoriously complex.
In this episode Gleb Mezhanskiy, founder and CEO of Datafold, discusses the different error conditions and solutions that you need to know about to ensure the accuracy of your data. Datalakes are notoriously complex. Can you start by outlining some of the situations where reconciling data between databases is needed?
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement Dagster offers a new approach to building and running data platforms and data pipelines. Datalakes are notoriously complex. Datalakes are notoriously complex.
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagementData projects are notoriously complex. With multiple stakeholders to manage across varying backgrounds and toolchains even simple reports can become unwieldy to maintain. Datalakes are notoriously complex.
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement Introducing RudderStack Profiles. RudderStack Profiles takes the SaaS guesswork and SQL grunt work out of building complete customer profiles so you can quickly ship actionable, enriched data to every downstream team.
In this episode Andrey Korchack, CTO of fintech startup Monite, discusses the complexities of designing and implementing a data platform in that sector. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagementDatalakes are notoriously complex.
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagementDatalakes are notoriously complex. Can you start by sharing some of your experiences with data migration projects? Can you start by sharing some of your experiences with data migration projects?
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagementDatalakes are notoriously complex. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data.
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement Introducing RudderStack Profiles. RudderStack Profiles takes the SaaS guesswork and SQL grunt work out of building complete customer profiles so you can quickly ship actionable, enriched data to every downstream team.
In this episode founder Tarush Aggarwal explains how the realities of the modern data stack are impacting data teams and the work that they are doing to accelerate time to value. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement Introducing RudderStack Profiles.
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement You shouldn't have to throw away the database to build with fast-changing data. Datalakes are notoriously complex. That’s three free boards at dataengineeringpodcast.com/miro.
Andrei Tserakhau has dedicated his careeer to this problem, and in this episode he shares the lessons that he has learned and the work he is doing on his most recent data transfer system at DoubleCloud. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement Introducing RudderStack Profiles.
Both traditional and AI data engineers should be fluent in SQL for managing structured data, but AI data engineers should be proficient in NoSQL databases as well for unstructured datamanagement. Data Storage Solutions As we all know, data can be stored in a variety of ways.
Key Takeaways Data Fabric is a modern data architecture that facilitates seamless data access, sharing, and management across an organization. Datamanagement recommendations and data products emerge dynamically from the fabric through automation, activation, and AI/ML analysis of metadata.
How confident are you in the quality of your data? Across industries and business objectives, high-qualitydata is a must for innovation and data-driven decision-making that keeps you ahead of the competition. Can you trust it for fast, confident decision-making when you need it most?
Here is the agenda, 1) Data Application Lifecycle Management - Harish Kumar( Paypal) Hear from the team in PayPal on how they build the data product lifecycle management (DPLM) systems.
Data lakehouse architecture combines the benefits of data warehouses and datalakes, bringing together the structure and performance of a data warehouse with the flexibility of a datalake. A visualization of the flow of data in data lakehouse architecture vs. data warehouse and datalake.
Data lakehouse architecture combines the benefits of data warehouses and datalakes, bringing together the structure and performance of a data warehouse with the flexibility of a datalake. A visualization of the flow of data in data lakehouse architecture vs. data warehouse and datalake.
Some would say that it’s not a big deal, however, these mixed environments have resulted in the complexities of managing disjointed data and business processes. With these challenges in enterprise datamanagement, there has to be an approach to overcoming them, right? The solution is called a data fabric.
Data observability tools employ automated monitoring, root cause analysis, data lineage, and data health insights to proactively detect, resolve, and prevent data anomalies. Both terms are focused on the practice of ensuring healthy, highqualitydata across an organization.
Enter data fabric: a datamanagement architecture designed to serve the needs of the business, not just those of data engineers. A data fabric is an architecture and associated data products that provide consistent capabilities across a variety of endpoints spanning multiple cloud environments.
Enter data fabric: a datamanagement architecture designed to serve the needs of the business, not just those of data engineers. A data fabric is an architecture and associated data products that provide consistent capabilities across a variety of endpoints spanning multiple cloud environments.
An Azure Data Engineer is responsible for designing, implementing, and maintaining datamanagement and data processing systems on the Microsoft Azure cloud platform. They work with large and complex data sets and are responsible for ensuring that data is stored, processed, and secured efficiently and effectively.
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