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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Collecting, integrating, and activating data are all challenging activities. When that data pertains to your customers it can become even more complex. To simplify the work of managing the full flow of your customer data and keep you in full control the team at Rudderstack created their…
Collecting, integrating, and activating…
14 February 2022 | 00:47:35
Along with globalization of our societies comes the need to analyze the geospatial and geotemporal data that is needed to manage the growth in commerce, communications, and other activities. In order to make geospatial analytics more maintainable and scalable there has been an increase in…
Along with globalization of our societies…
07 February 2022 | 00:59:54
There are many dimensions to the work of protecting the privacy of users in our data. When you need to share a data set with other teams, departments, or businesses then it is of utmost importance that you eliminate or obfuscate personal information. In this episode Will Thompson explores…
There are many dimensions to the work of…
06 February 2022 | 01:00:06
The Data Engineering Podcast has been going for five years now and has included conversations and interviews with a huge number of guests, covering a broad range of topics. In addition to that, the host curated the essays contained in the book "97 Things Every Data Engineer Should…
The Data Engineering Podcast has been…
31 January 2022 | 00:41:36
Pandas is a powerful tool for cleaning, transforming, manipulating, or enriching data, among many other potential uses. As a result it has become a standard tool for data engineers for a wide range of applications. Matt Harrison is a Python expert with a long history of working with data…
Pandas is a powerful tool for cleaning,…
31 January 2022 | 01:00:22
Data platforms are exemplified by a complex set of connections that are subject to a set of constantly evolving requirements. In order to make this a tractable problem it is necessary to define boundaries for communication between concerns, which brings with it the need to establish…
Data platforms are exemplified by a…
23 January 2022 | 00:56:00
Data engineering is a relatively young and rapidly expanding field, with practitioners having a wide array of experiences as they navigate their careers. Ashish Mrig currently leads the data analytics platform for Wayfair, as well as running a local data engineering meetup. In this episode…
Data engineering is a relatively young…
23 January 2022 | 00:52:45
Data quality control is a requirement for being able to trust the various reports and machine learning models that are relying on the information that you curate. Rules based systems are useful for validating known requirements, but with the scale and complexity of data in modern…
Data quality control is a requirement for…
15 January 2022 | 01:02:30
Applications of data have grown well beyond the venerable business intelligence dashboards that organizations have relied on for decades. Now it is being used to power consumer facing services, influence organizational behaviors, and build sophisticated machine learning systems. Given this…
Applications of data have grown well…
15 January 2022 | 00:50:14
Reverse ETL is a product category that evolved from the landscape of customer data platforms with a number of companies offering their own implementation of it. While struggling with the work of automating data integration workflows with marketing, sales, and support tools Brian Leonard…
Reverse ETL is a product category that…
08 January 2022 | 00:44:57