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In this episode Dain Sundstrom, CTO of Starburst, explains how the combination of the Trino query engine and the Iceberg table format offer the ease of use and execution speed of data warehouses with the infinite storage and scalability of data lakes. Data lakes are notoriously complex. Your first 30 days are free!
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 datamanagement Dagster offers a new approach to building and running data platforms and datapipelines. Data lakes 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 datamanagementData lakes are notoriously complex. Data lakes in various forms have been gaining significant popularity as a unified interface to an organization's analytics. Closing Announcements Thank you for listening!
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. Data lakes are notoriously complex. Go to dataengineeringpodcast.com/dagster today to get started. Your first 30 days are free!
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 datamanagementData lakes are notoriously complex.
Without high-quality, available data, companies risk misinformed decisions, compliance violations, and missed opportunities. Why AI and Analytics Require Real-Time, High-QualityData To extract meaningful value from AI and analytics, organizations need data that is continuously updated, accurate, and accessible.
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 datamanagementData lakes 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 datamanagementData lakes are notoriously complex. Are there any trends that concern you?
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. Dagster offers a new approach to building and running data platforms and datapipelines.
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. Data lakes are notoriously complex. My thanks to the team at Code Comments for their support. Closing Announcements Thank you for listening!
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. Dagster offers a new approach to building and running data platforms and datapipelines.
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. Data lakes 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 datapipelines. Data lakes 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. Data lakes are notoriously complex. Data lakes are notoriously complex. My thanks to the team at Code Comments for their support.
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagementData lakes are notoriously complex. What are the open questions today in technical scalability of data engines? What are the open questions today in technical scalability of data engines?
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.
AI data engineers are data engineers that are responsible for developing and managingdatapipelines that support AI and GenAI data products. Essential Skills for AI Data Engineers Expertise in DataPipelines and ETL Processes A foundational skill for data engineers?
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagementData lakes are notoriously complex. Contact Info LinkedIn Parting Question From your perspective, what is the biggest gap in the tooling or technology for datamanagement today?
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. Data lakes are notoriously complex. Data lakes are notoriously complex. Your first 30 days are free!
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).
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. Data lakes are notoriously complex. Can you start by outlining some of the situations where reconciling data between databases is needed?
In this episode Alex Merced explains how the branching and merging functionality in Nessie allows you to use the same versioning semantics for your data lakehouse that you are used to from Git. Data lakes are notoriously complex. Go to dataengineeringpodcast.com/dagster today to get started. 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 datapipelines. Data lakes are notoriously complex. Data lakes are notoriously complex. Your first 30 days are free!
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. Data lakes are notoriously complex.
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagementData lakes are notoriously complex. Dagster offers a new approach to building and running data platforms and datapipelines. What do you have planned for the future of Elementary?
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagementData lakes 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 datamanagementData projects are notoriously complex. With multiple stakeholders to manage across varying backgrounds and toolchains even simple reports can become unwieldy to maintain. Data lakes 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.
Summary The first step of datapipelines is to move the data to a place where you can process and prepare it for its eventual purpose. Data transfer systems are a critical component of data enablement, and building them to support large volumes of information is a complex endeavor. Sponsored By: Starburst : ![Starburst
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 datamanagementData lakes are notoriously complex.
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.
Current open-source frameworks like YAML-based Soda Core, Python-based Great Expectations, and dbt SQL are frameworks to help speed up the creation of dataquality tests. They are all in the realm of software, domain-specific language to help you write dataquality tests.
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. Data lakes are notoriously complex. That’s three free boards at dataengineeringpodcast.com/miro.
Going into the DataPipeline Automation Summit 2023, we were thrilled to connect with our customers and partners and share the innovations we’ve been working on at Ascend. The summit explored the future of datapipeline automation and the endless possibilities it presents.
The Ten Standard Tools To Develop DataPipelines In Microsoft Azure. While working in Azure with our customers, we have noticed several standard Azure tools people use to develop datapipelines and ETL or ELT processes. We counted ten ‘standard’ ways to transform and set up batch datapipelines in Microsoft Azure.
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.
Data observability tools employ automated monitoring, root cause analysis, data lineage, and data health insights to proactively detect, resolve, and prevent data anomalies. Freshness : Freshness seeks to understand how up-to-date your data tables are, as well as the cadence at which your tables are updated.
Key Takeaways Data Mesh is a modern datamanagement architectural strategy that decentralizes development of trusted data products to support real-time business decisions and analytics. However, complex architectures and data silos make that difficult. One strategy being leveraged is a data mesh.
By automating many of the processes involved in dataqualitymanagement, dataquality platforms can help organizations reduce errors, streamline workflows, and make better use of their data assets. This functionality is critical for not only fixing current issues but also preventing future ones.
This is what managingdata without metadata feels like. Often described as “data about data,” it is the unsung hero in datamanagement that ensures our vast amounts of information are not only stored but easily discoverable, organized, and actionable. Chaos, right?
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?
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