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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As data engineers the health of our pipelines is our highest priority. Unfortunately, there are countless ways that our dataflows can break or degrade that have nothing to do with the business logic or data transformations that we write and maintain. Sean Knapp founded Ascend to address the…
As data engineers the health of our…
04 November 2019 | 00:48:51
Despite the fact that businesses have relied on useful and accurate data to succeed for decades now, the state of the art for obtaining and maintaining that information still leaves much to be desired. In an effort to create a better abstraction for building data applications Nick Schrock…
Despite the fact that businesses have…
28 October 2019 | 01:07:49
The scale and complexity of the systems that we build to satisfy business requirements is increasing as the available tools become more sophisticated. In order to bridge the gap between legacy infrastructure and evolving use cases it is necessary to create a unifying set of components. In…
The scale and complexity of the systems…
22 October 2019 | 00:42:51
Managing a data warehouse can be challenging, especially when trying to maintain a common set of patterns. Dataform is a platform that helps you apply engineering principles to your data transformations and table definitions, including unit testing SQL scripts, defining repeatable…
Managing a data warehouse can be…
15 October 2019 | 00:47:04
The process of exposing your data through a SQL interface has many possible pathways, each with their own complications and tradeoffs. One of the recent options is Rockset, a serverless platform for fast SQL analytics on semi-structured and structured data. In this episode CEO Venkat…
The process of exposing your data through…
08 October 2019 | 00:54:39
Building an end-to-end data pipeline for your machine learning projects is a complex task, made more difficult by the variety of ways that you can structure it. Kedro is a framework that provides an opinionated workflow that lets you focus on the parts that matter, so that you don’t…
Building an end-to-end data pipeline for…
01 October 2019 | 00:35:09
Object storage is quickly becoming the unifying layer for data intensive applications and analytics. Modern, cloud oriented data warehouses and data lakes both rely on the durability and ease of use that it provides. S3 from Amazon has quickly become the de-facto API for interacting with…
Object storage is quickly becoming the…
23 September 2019 | 01:08:20
The conventional approach to analytics involves collecting large amounts of data that can be cleaned, followed by a separate step for analysis and interpretation. Unfortunately this strategy is not viable for handling real-time, real-world use cases such as traffic management or supply…
The conventional approach to analytics…
18 September 2019 | 00:57:56
The first stage in every data project is collecting information and routing it to a storage system for later analysis. For operational data this typically means collecting log messages and system metrics. Often a different tool is used for each class of data, increasing the overall…
The first stage in every data project is…
10 September 2019 | 00:55:20
Data professionals are working in a domain that is rapidly evolving. In order to stay current we need access to deeply technical presentations that aren’t burdened by extraneous marketing. To fulfill that need Pete Soderling and his team have been running the Data Council series of…
Data professionals are working in a…
02 September 2019 | 00:52:46