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Using Trino And Iceberg As The Foundation Of Your Data Lakehouse

Data Engineering Podcast

Summary A data lakehouse is intended to combine the benefits of data lakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). Data lakes are notoriously complex. Visit [dataengineeringpodcast.com/data-council]([link] and use code *depod20* to register today!

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Addressing The Challenges Of Component Integration In Data Platform Architectures

Data Engineering Podcast

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

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Enhancing The Abilities Of Software Engineers With Generative AI At Tabnine

Data Engineering Podcast

If you are migrating to a modern data stack, Datafold can also help you automate data and code validation to speed up the migration. Learn more about Datafold by visiting dataengineeringpodcast.com/datafold Data lakes are notoriously complex. webapps vs. data pipelines vs. exploratory analysis, etc.)

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Data Lake vs. Data Warehouse vs. Data Lakehouse

Sync Computing

While data warehouses are still in use, they are limited in use-cases as they only support structured data. Data lakes add support for semi-structured and unstructured data, and data lakehouses add further flexibility with better governance in a true hybrid solution built from the ground-up.

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Using SQL to democratize streaming data

Cloudera

However, in the typical enterprise, only a small team has the core skills needed to gain access and create value from streams of data. This data engineering skillset typically consists of Java or Scala programming skills mated with deep DevOps acumen. This is a task best left to expert Java programming minds.

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Tame The Entropy In Your Data Stack And Prevent Failures With Sifflet

Data Engineering Podcast

Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. RudderStack helps you build a customer data platform on your warehouse or data lake. runs natively on data lakes and warehouses and in AWS, Google Cloud and Microsoft Azure.

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How Software Bill of Materials change the dependency game

Zalando Engineering

We publish a curated data set containing dependency data from the SBOM for every application we deploy, based on its Container image. The data set is available in our data lake and thus can be easily queried and visualized by any engineer. Another insight from analyzing the SBOM data was our usage of the AWS SDK.

Java 98