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Data Engineering Podcast
This show goes behind the scenes for the tools, techniques, and difficulties associated with the discipline of data engineering. Databases, workflows, automation, and data manipulation are just some of the topics that you will find here.
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Tobias Macey
Tobias Macey
Database Refactoring Patterns with Pramod Sadalage - Episode 22 - E22
Summary
As software lifecycles move faster, the database needs to be able to keep up. Practices such as version controlled migration scripts and iterative schema evolution provide the necessary mechanisms to ensure that your data layer is as agile as your application. Pramod Sadalage saw the need for these capabilities during the early…
Summary
As software lifecycles move faster, the database needs to be able to keep up.…
12 March 2018 | 00:49:06
The Future Data Economy with Roger Chen - Episode 21 - E21
Summary
Data is an increasingly sought after raw material for business in the modern economy. One of the factors driving this trend is the increase in applications for machine learning and AI which require large quantities of information to work from. As the demand for data becomes more widespread the market for providing it will begin…
Summary
Data is an increasingly sought after raw material for business in the modern…
05 March 2018 | 00:42:48
Honeycomb Data Infrastructure with Sam Stokes - Episode 20 - E20
Summary
One of the sources of data that often gets overlooked is the systems that we use to run our businesses. This data is not used to directly provide value to customers or understand the functioning of the business, but it is still a critical component of a successful system. Sam Stokes is an engineer at Honeycomb where he helps to…
Summary
One of the sources of data that often gets overlooked is the systems that we use…
26 February 2018 | 00:41:33
Data Teams with Will McGinnis - Episode 19 - E19
Summary
The responsibilities of a data scientist and a data engineer often overlap and occasionally come to cross purposes. Despite these challenges it is possible for the two roles to work together effectively and produce valuable business outcomes. In this episode Will McGinnis discusses the opinions that he has gained from experience…
Summary
The responsibilities of a data scientist and a data engineer often overlap and…
19 February 2018 | 00:28:39
TimescaleDB: Fast And Scalable Timeseries with Ajay Kulkarni and Mike Freedman - Episode 18 - E18
Summary
As communications between machines become more commonplace the need to store the generated data in a time-oriented manner increases. The market for timeseries data stores has many contenders, but they are not all built to solve the same problems or to scale in the same manner. In this episode the founders of TimescaleDB, Ajay…
Summary
As communications between machines become more commonplace the need to store the…
11 February 2018 | 01:02:40
Pulsar: Fast And Scalable Messaging with Rajan Dhabalia and Matteo Merli - Episode 17 - E17
Summary
One of the critical components for modern data infrastructure is a scalable and reliable messaging system. Publish-subscribe systems have been popular for many years, and recently stream oriented systems such as Kafka have been rising in prominence. This week Rajan Dhabalia and Matteo Merli discuss the work they have done on…
Summary
One of the critical components for modern data infrastructure is a scalable and…
04 February 2018 | 00:53:47
Dat: Distributed Versioned Data Sharing with Danielle Robinson and Joe Hand - Episode 16 - E16
Summary
Sharing data across multiple computers, particularly when it is large and changing, is a difficult problem to solve. In order to provide a simpler way to distribute and version data sets among collaborators the Dat Project was created. In this episode Danielle Robinson and Joe Hand explain how the project got started, how…
Summary
Sharing data across multiple computers, particularly when it is large and…
29 January 2018 | 01:02:58
Snorkel: Extracting Value From Dark Data with Alex Ratner - Episode 15 - E15
Summary
The majority of the conversation around machine learning and big data pertains to well-structured and cleaned data sets. Unfortunately, that is just a small percentage of the information that is available, so the rest of the sources of knowledge in a company are housed in so-called “Dark Data” sets. In this episode…
Summary
The majority of the conversation around machine learning and big data pertains…
22 January 2018 | 00:37:13
CRDTs and Distributed Consensus with Christopher Meiklejohn - Episode 14 - E14
Summary
As we scale our systems to handle larger volumes of data, geographically distributed users, and varied data sources the requirement to distribute the computational resources for managing that information becomes more pronounced. In order to ensure that all of the distributed nodes in our systems agree with each other we need to…
Summary
As we scale our systems to handle larger volumes of data, geographically…
15 January 2018 | 00:45:43
Citus Data: Distributed PostGreSQL for Big Data with Ozgun Erdogan and Craig Kerstiens - Episode 13 - E13
Summary
PostGreSQL has become one of the most popular and widely used databases, and for good reason. The level of extensibility that it supports has allowed it to be used in virtually every environment. At Citus Data they have built an extension to support running it in a distributed fashion across large volumes of data with…
Summary
PostGreSQL has become one of the most popular and widely used databases, and for…
08 January 2018 | 00:46:44