Big data analytics is the process of collecting data, processing and cleaning it, then analyzing it with techniques like data mining, predictive analytics, and deep learning. This process requires a suite of tools to operate efficiently. Data analytics can save companies money, drive product development, and give insight into the market and customers. The company

Imply Infra: Big Data Analysis and Real-World Examples with Jad Naous

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Apache Iceberg is an open source high-performance format for huge data tables. Iceberg enables the use of SQL tables for big data, while making it possible for engines like Spark and Hive to safely work with the same tables, at the same time. Iceberg was started at Netflix by Ryan Blue and Dan Weeks, and

Iceberg at Netflix and Beyond with Ryan Blue

Starburst is a data lake analytics platform. It’s designed to help users work with structured data at scale, and is built on the open source platform, Trino. Adam Ferrari is the SVP of Engineering at Starburst. He joins the show to talk about Starburst, data engineering, and what it takes to build a data lake.

Building a Data Lake with Adam Ferrari

Building scalable software applications can be complex and typically requires dozens of different tools. The engineering often involves handling many arcane tasks that are distant from actual application logic. In addition, a lack of a cohesive model for building applications can lead to substantial engineering costs. Nathan Marz is the creator of Rama, which is

Rama with Nathan Marz

SurrealDB is the result of a long-time collaboration between brothers Tobie and Jaime Morgan Hitchcock. The project has modest origins and started merely to support other projects the brothers were working on. However, over time the project grew and in 2021  they started working on it full-time. Since then the project has gained serious adoption.

Bonus Episode: SurrealDB with Tobie Morgan Hitchcock

Maritime logistics is the process organizing the movement of goods across the ocean. Historically, this has been a challenging problem because of the multinational nature of shipping, as well as piracy, smuggling, and legacy technology. It’s also profoundly important for security reasons, and because 90% of what we buy travels over the oceans. Ocean vessels

Imply Infra: Big Data Analysis and Real-World Examples with Jad Naous

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