Real-Time Data Architectures – the Growing Importance of Data Wrangling at the Network Edge

- PDT
Dev Innovation Summit Main Stage
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Peter Hughes
Push Technology, Head of Cloud

Peter Hughes is an experienced senior engineer in high-performance Java applications and has led the design & development of both back-end and front-end projects for real-time data platforms. He is currently Head of Cloud for Push Technology’s industry leading Diffusion®, an Intelligent Event-Data Platform. The platform powers real-time, highly-scalable and mission-critical web, mobile, and IoT applications for companies worldwide.

Peter spends his days entrenched in interactions with development and business teams around the globe. Peter is well-versed in both the business and deep technical challenges companies face and he has broad experience helping them address these challenges to achieve their corporate goals. He has strong engineering credentials in leading the design and development of both back-end and front-end projects for real-time data platforms. As a sought-after speaker, his recent presentations on real-time data over the Internet include: API World, the Nordic APIs Data Summit (https://youtu.be/Tizx93hhm7s), Devvox, Develop Denver and API Con The Hague.


As real-time distribution mechanisms like Pub/Sub become commodified parts of application architectures, developers are discovering a need for more sophisticated functionality than just simple message delivery. Traditionally, developers and software architects have struggled with the complexities of creating event-driven, real-time web, mobile, and IoT applications. This is because they are not data “wrangling” experts. Data wrangling comprises mapping raw data into another format suitable for another purpose and is critical to event-driven application development. However, without the right tools, data wrangling can be a laborious task, as it typically involves restructuring of large amounts of data.

This talk explores the growing value of data-wrangling at the network edge, and how pragmatic, app-focused platforms like GraphQL mark the future of real-time data architectures.”