Tobias Macey

Technology

Weekly deep dives on data management with the engineers and entrepreneurs who are shaping the industry

Popular episodes

Bringing The Metrics Layer To The Masses With Transform

Jul 23 • 01:01:17

Summary

Collecting and cleaning data is only useful if someone can make sense of it afterward. The latest evolution in the data ecosystem is the introduction of a dedicated metrics layer to help address the challenge of adding context and semantics to raw information. In this episode Nick Handel shares the story behind Transform, a new platform that provides a managed metri...

Strategies For Proactive Data Quality Management

Jul 20 • 01:01:06

Summary

Data quality is a concern that has been gaining attention alongside the rising importance of analytics for business success. Many solutions rely on hand-coded rules for catching known bugs, or statistical analysis of records to detect anomalies retroactively. While those are useful tools, it is far better to prevent data errors before they become an outsized issue. ...

Low Code And High Quality Data Engineering For The Whole Organization With Prophecy

Jul 16 • 01:12:35

Summary

There is a wealth of tools and systems available for processing data, but the user experience of integrating them and building workflows is still lacking. This is particularly important in large and complex organizations where domain knowledge and context is paramount and there may not be access to engineers for codifying that expertise. Raj Bains founded Prophecy t...

Exploring The Design And Benefits Of The Modern Data Stack

Jul 13 • 49:01

Summary

We have been building platforms and workflows to store, process, and analyze data since the earliest days of computing. Over that time there have been countless architectures, patterns, and "best practices" to make that task manageable. With the growing popularity of cloud services a new pattern has emerged and been dubbed the "Modern Data Stack". In this episode me...

Democratize Data Cleaning Across Your Organization With Trifacta

Jul 9 • 01:07:13

Summary

Every data project, whether it’s analytics, machine learning, or AI, starts with the work of data cleaning. This is a critical step and benefits from being accessible to the domain experts. Trifacta is a platform for managing your data engineering workflow to make curating, cleaning, and preparing your information more approachable for everyone in the business. In t...

Stick All Of Your Systems And Data Together With SaaSGlue As Your Workflow Manager

Jul 5 • 55:31

Summary

At the core of every data pipeline is an workflow manager (or several). Deploying, managing, and scaling that orchestration can consume a large fraction of a data team’s energy so it is important to pick something that provides the power and flexibility that you need. SaaSGlue is a managed service that lets you connect all of your systems, across clouds and physical...

Leveling Up Open Source Data Integration With Meltano Hub And The Singer SDK

Jul 3 • 01:05:24

Summary

Data integration in the form of extract and load is the critical first step of every data project. There are a large number of commercial and open source projects that offer that capability but it is still far from being a solved problem. One of the most promising community efforts is that of the Singer ecosystem, but it has been plagued by inconsistent quality and ...

A Candid Exploration Of Timeseries Data Analysis With InfluxDB

Jun 29 • 01:06:02

Summary

While the overall concept of timeseries data is uniform, its usage and applications are far from it. One of the most demanding applications of timeseries data is for application and server monitoring due to the problem of high cardinality. In his quest to build a generalized platform for managing timeseries Paul Dix keeps getting pulled back into the monitoring aren...

Lessons Learned From The Pipeline Data Engineering Academy

Jun 26 • 01:11:03

Summary

Data Engineering is a broad and constantly evolving topic, which makes it difficult to teach in a concise and effective manner. Despite that, Daniel Molnar and Peter Fabian started the Pipeline Academy to do exactly that. In this episode they reflect on the lessons that they learned while teaching the first cohort of their bootcamp how to be effective data engineers...

Make Database Performance Optimization A Playful Experience With OtterTune

Jun 23 • 58:28

Summary

The database is the core of any system because it holds the data that drives your entire experience. We spend countless hours designing the data model, updating engine versions, and tuning performance. But how confident are you that you have configured it to be as performant as possible, given the dozens of parameters and how they interact with each other? Andy Pavl...

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