Latest Episodes

Cleaning And Curating Open Data For Archaeology - Episode 68

Archaeologists collect and create a variety of data as part of their research and exploration. Open Context is a platform for cleaning, curating, and sharing this data. In this episode Eric Kansa describes how they process, clean, and normalize the data that they host, the challenges that they face with scaling ETL processes which require domain specific knowledge, and how the information contained in connections that they expose is being used for interesting projects.

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Managing Database Access Control For Teams With strongDM - Episode 67

Controlling access to a database is a solved problem... right? It can be straightforward for small teams and a small number of storage engines, but once either or both of those start to scale then things quickly become complex and difficult to manage. After years of running across the same issues in numerous companies and even more projects Justin McCarthy built strongDM to solve database access management for everyone. In this episode he explains how the strongDM proxy works to grant and audit access to storage systems and the...

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Building Enterprise Big Data Systems At LEGO - Episode 66

Building internal expertise around big data in a large organization is a major competitive advantage. However, it can be a difficult process due to compliance needs and the need to scale globally on day one. In this episode Jesper S√łgaard and Keld Antonsen share the story of starting and growing the big data group at LEGO. They discuss the challenges of being at global scale from the start, hiring and training talented engineers, prototyping and deploying new systems in the cloud, and what they have learned in the process....

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TimescaleDB: The Timeseries Database Built For SQL And Scale - Episode 65

The past year has been an active one for the timeseries market. New products have been launched, more businesses have moved to streaming analytics, and the team at Timescale has been keeping busy. In this episode the TimescaleDB CEO Ajay Kulkarni and CTO Michael Freedman stop by to talk about their 1.0 release, how the use cases for timeseries data have proliferated, and how they are continuing to simplify the task of processing your time oriented events.

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Performing Fast Data Analytics Using Apache Kudu - Episode 64

The Hadoop platform is purpose built for processing large, slow moving data in long-running batch jobs. As the ecosystem around it has grown, so has the need for fast data analytics on fast moving data. To fill this need the Kudu project was created with a column oriented table format that was tuned for high volumes of writes and rapid query execution across those tables. For a perfect pairing, they made it easy to connect to the Impala SQL engine. In this episode Brock Noland and Jordan Birdsell from...

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Simplifying Continuous Data Processing Using Stream Native Storage In Pravega with Tom Kaitchuck - Episode 63

As more companies and organizations are working to gain a real-time view of their business, they are increasingly turning to stream processing technologies to fullfill that need. However, the storage requirements for continuous, unbounded streams of data are markedly different than that of batch oriented workloads. To address this shortcoming the team at Dell EMC has created the open source Pravega project. In this episode Tom Kaitchuk explains how Pravega simplifies storage and processing of data streams, how it integrates with processing engines such as Flink, and the...

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Continuously Query Your Time-Series Data Using PipelineDB with Derek Nelson and Usman Masood - Episode 62

Processing high velocity time-series data in real-time is a complex challenge. The team at PipelineDB has built a continuous query engine that simplifies the task of computing aggregates across incoming streams of events. In this episode Derek Nelson and Usman Masood explain how it is architected, strategies for designing your data flows, how to scale it up and out, and edge cases to be aware of.

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Advice On Scaling Your Data Pipeline Alongside Your Business with Christian Heinzmann - Episode 61

Every business needs a pipeline for their critical data, even if it is just pasting into a spreadsheet. As the organization grows and gains more customers, the requirements for that pipeline will change. In this episode Christian Heinzmann, Head of Data Warehousing at Grubhub, discusses the various requirements for data pipelines and how the overall system architecture evolves as more data is being processed. He also covers the changes in how the output of the pipelines are used, how that impacts the expectations for accuracy and availability, and some...

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Putting Apache Spark Into Action with Jean Georges Perrin - Episode 60

Apache Spark is a popular and widely used tool for a variety of data oriented projects. With the large array of capabilities, and the complexity of the underlying system, it can be difficult to understand how to get started using it. Jean George Perrin has been so impressed by the versatility of Spark that he is writing a book for data engineers to hit the ground running. In this episode he helps to make sense of what Spark is, how it works, and the various ways that you can...

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Apache Zookeeper As A Building Block For Distributed Systems with Patrick Hunt - Episode 59

Distributed systems are complex to build and operate, and there are certain primitives that are common to a majority of them. Rather then re-implement the same capabilities every time, many projects build on top of Apache Zookeeper. In this episode Patrick Hunt explains how the Apache Zookeeper project was started, how it functions, and how it is used as a building block for other distributed systems. He also explains the operational considerations for running your own cluster, how it compares to more recent entrants such as Consul and EtcD,...

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