Latest Episodes

Putting Apache Spark Into Action with Jean Georges Perrin - Episode 60

December 10, 2018

Apache Spark is a popular and widely used tool for a variety of data oriented projects. With the large array of capabilities, and the complexity of the underlying system, it can be difficult to understand how to get started using it. Jean George Perrin has been so impressed by the versatility of Spark that he is writing a book for data engineers to hit the ground running. In this episode he helps to make sense of what Spark is, how it works, and the various ways that you can...

Play Episode

Apache Zookeeper As A Building Block For Distributed Systems with Patrick Hunt - Episode 59

December 3, 2018

Distributed systems are complex to build and operate, and there are certain primitives that are common to a majority of them. Rather then re-implement the same capabilities every time, many projects build on top of Apache Zookeeper. In this episode Patrick Hunt explains how the Apache Zookeeper project was started, how it functions, and how it is used as a building block for other distributed systems. He also explains the operational considerations for running your own cluster, how it compares to more recent entrants such as Consul and EtcD,...

Play Episode

Set Up Your Own Data-as-a-Service Platform On Dremio with Tomer Shiran - Episode 58

November 26, 2018

When your data lives in multiple locations, belonging to at least as many applications, it is exceedingly difficult to ask complex questions of it. The default way to manage this situation is by crafting pipelines that will extract the data from source systems and load it into a data lake or data warehouse. In order to make this situation more manageable and allow everyone in the business to gain value from the data the folks at Dremio built a self service data platform. In this episode Tomer Shiran, CEO...

Play Episode

Stateful, Distributed Stream Processing on Flink with Fabian Hueske - Episode 57

November 19, 2018

Modern applications and data platforms aspire to process events and data in real time at scale and with low latency. Apache Flink is a true stream processing engine with an impressive set of capabilities for stateful computation at scale. In this episode Fabian Hueske, one of the original authors, explains how Flink is architected, how it is being used to power some of the world's largest businesses, where it sits in the lanscape of stream processing tools, and how you can start using it today.

Play Episode

How Upsolver Is Building A Data Lake Platform In The Cloud with Yoni Iny - Episode 56

November 11, 2018

A data lake can be a highly valuable resource, as long as it is well built and well managed. Unfortunately, that can be a complex and time-consuming effort, requiring specialized knowledge and diverting resources from your primary business. In this episode Yoni Iny, CTO of Upsolver, discusses the various components that are necessary for a successful data lake project, how the Upsolver platform is architected, and how modern data lakes can benefit your organization.

Play Episode

Self Service Business Intelligence And Data Sharing Using Looker with Daniel Mintz - Episode 55

November 5, 2018

Business intelligence is a necessity for any organization that wants to be able to make informed decisions based on the data that they collect. Unfortunately, it is common for different portions of the business to build their reports with different assumptions, leading to conflicting views and poor choices. Looker is a modern tool for building and sharing reports that makes it easy to get everyone on the same page. In this episode Daniel Mintz explains how the product is architected, the features that make it easy for any business...

Play Episode

Using Notebooks As The Unifying Layer For Data Roles At Netflix with Matthew Seal - Episode 54

October 29, 2018

Jupyter notebooks have gained popularity among data scientists as an easy way to do exploratory analysis and build interactive reports. However, this can cause difficulties when trying to move the work of the data scientist into a more standard production environment, due to the translation efforts that are necessary. At Netflix they had the crazy idea that perhaps that last step isn't necessary, and the production workflows can just run the notebooks directly. Matthew Seal is one of the primary engineers who has been tasked with building the tools...

Play Episode

Of Checklists, Ethics, and Data with Emily Miller and Peter Bull (Cross Post from Podcast.__init__) - Episode 53

October 22, 2018

As data science becomes more widespread and has a bigger impact on the lives of people, it is important that those projects and products are built with a conscious consideration of ethics. Keeping ethical principles in mind throughout the lifecycle of a data project helps to reduce the overall effort of preventing negative outcomes from the use of the final product. Emily Miller and Peter Bull of Driven Data have created Deon to improve the communication and conversation around ethics among and between data teams. It is a Python...

Play Episode

Improving The Performance Of Cloud-Native Big Data At Netflix Using The Iceberg Table Format with Ryan Blue - Episode 52

October 15, 2018

With the growth of the Hadoop ecosystem came a proliferation of implementations for the Hive table format. Unfortunately, with no formal specification, each project works slightly different which increases the difficulty of integration across systems. The Hive format is also built with the assumptions of a local filesystem which results in painful edge cases when leveraging cloud object storage for a data lake. In this episode Ryan Blue explains how his work on the Iceberg table format specification and reference implementation has allowed Netflix to improve the performance and...

Play Episode

Combining Transactional And Analytical Workloads On MemSQL with Nikita Shamgunov - Episode 51

October 9, 2018

One of the most complex aspects of managing data for analytical workloads is moving it from a transactional database into the data warehouse. What if you didn't have to do that at all? MemSQL is a distributed database built to support concurrent use by transactional, application oriented, and analytical, high volume, workloads on the same hardware. In this episode the CEO of MemSQL describes how the company and database got started, how it is architected for scale and speed, and how it is being used in production. This was...

Play Episode

Subscribe Wherever You Listen To Podcasts

Episodes 1Apple PodcastsEpisodes 2OvercastEpisodes 3Google PodcastsEpisodes 4Google PlayEpisodes 5SpotifyEpisodes 6PocketCastsEpisodes 7Radio PublicEpisodes 8CastBoxEpisodes 9StitcherEpisodes 10TuneInEpisodes 11RSS

Join The Mailing List