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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
Mobile Data Collection And Analysis Using Ona And Canopy With Peter Lubell-Doughtie - Episode 41 - E41
Summary
With the attention being paid to the systems that power large volumes of high velocity data it is easy to forget about the value of data collection at human scales. Ona is a company that is building technologies to support mobile data collection, analysis of the aggregated information, and user-friendly presentations. In this…
Summary
With the attention being paid to the systems that power large volumes of high…
30 July 2018 | 00:29:14
Ceph: A Reliable And Scalable Distributed Filesystem with Sage Weil - Episode 40 - E40
Summary
When working with large volumes of data that you need to access in parallel across multiple instances you need a distributed filesystem that will scale with your workload. Even better is when that same system provides multiple paradigms for interacting with the underlying storage. Ceph is a highly available, highly scalable, and…
Summary
When working with large volumes of data that you need to access in parallel…
16 July 2018 | 00:48:31
Building Data Flows In Apache NiFi With Kevin Doran and Andy LoPresto - Episode 39 - E39
Summary
Data integration and routing is a constantly evolving problem and one that is fraught with edge cases and complicated requirements. The Apache NiFi project models this problem as a collection of data flows that are created through a self-service graphical interface. This framework provides a flexible platform for building a wide…
Summary
Data integration and routing is a constantly evolving problem and one that is…
08 July 2018 | 01:04:16
Leveraging Human Intelligence For Better AI At Alegion With Cheryl Martin - Episode 38 - E38
Summary
Data is often messy or incomplete, requiring human intervention to make sense of it before being usable as input to machine learning projects. This is problematic when the volume scales beyond a handful of records. In this episode Dr. Cheryl Martin, Chief Data Scientist for Alegion, discusses the importance of properly labeled…
Summary
Data is often messy or incomplete, requiring human intervention to make sense of…
02 July 2018 | 00:46:14
Package Management And Distribution For Your Data Using Quilt with Kevin Moore - Episode 37 - E37
Summary
Collaboration, distribution, and installation of software projects is largely a solved problem, but the same cannot be said of data. Every data team has a bespoke means of sharing data sets, versioning them, tracking related metadata and changes, and publishing them for use in the software systems that rely on them. The CEO and…
Summary
Collaboration, distribution, and installation of software projects is largely a…
25 June 2018 | 00:41:43
User Analytics In Depth At Heap with Dan Robinson - Episode 36 - E36
Summary
Web and mobile analytics are an important part of any business, and difficult to get right. The most frustrating part is when you realize that you haven’t been tracking a key interaction, having to write custom logic to add that event, and then waiting to collect data. Heap is a platform that automatically tracks every…
Summary
Web and mobile analytics are an important part of any business, and difficult to…
17 June 2018 | 00:45:27
CockroachDB In Depth with Peter Mattis - Episode 35 - E35
Summary
With the increased ease of gaining access to servers in data centers across the world has come the need for supporting globally distributed data storage. With the first wave of cloud era databases the ability to replicate information geographically came at the expense of transactions and familiar query languages. To address…
Summary
With the increased ease of gaining access to servers in data centers across the…
11 June 2018 | 00:43:41
ArangoDB: Fast, Scalable, and Multi-Model Data Storage with Jan Steeman and Jan Stücke - Episode 34 - E34
Summary
Using a multi-model database in your applications can greatly reduce the amount of infrastructure and complexity required. ArangoDB is a storage engine that supports documents, dey/value, and graph data formats, as well as being fast and scalable. In this episode Jan Steeman and Jan Stücke explain where Arango fits in the…
Summary
Using a multi-model database in your applications can greatly reduce the amount…
04 June 2018 | 00:40:05
The Alooma Data Pipeline With CTO Yair Weinberger - Episode 33 - E33
Summary
Building an ETL pipeline is a common need across businesses and industries. It’s easy to get one started but difficult to manage as new requirements are added and greater scalability becomes necessary. Rather than duplicating the efforts of other engineers it might be best to use a hosted service to handle the plumbing so…
Summary
Building an ETL pipeline is a common need across businesses and industries.…
28 May 2018 | 00:47:50
PrestoDB and Starburst Data with Kamil Bajda-Pawlikowski - Episode 32 - E32
Summary
Most businesses end up with data in a myriad of places with varying levels of structure. This makes it difficult to gain insights from across departments, projects, or people. Presto is a distributed SQL engine that allows you to tie all of your information together without having to first aggregate it all into a data warehouse.…
Summary
Most businesses end up with data in a myriad of places with varying levels of…
21 May 2018 | 00:42:08