Peter Lawrey discusses data-driven reactive systems, profiling latency distribution in such an environment, finding rare bugs, implementing resilience and monitoring.
Simon Metson approaches the problem of evolving a data system; some patterns and anti-patterns both technical (polyglot systems, lambda architectures) and organisational (data silos, lava layers).
Dave McCrory talks about what is Data Gravity, how it affects performance and portability and why these effects are amplified when there are larger volumes of data.
Peter Bourgon provides a practical introduction to Conflict-free Replicated Data Types (CRDTs) and describes a production CRDT system built at SoundCloud to serve several product features.
Mark Madsen explains the history of databases and data processing over the past decades and looks where the industry will go.
The authors discuss some of the unique challenges they've faced delivering highly personalized search over semi-structured data at massive scale.
John Canfield discusses the changing payment ecosystem, innovations in mining and organizing unstructured data from many sources, and approaches to deciding for loss minimization and user experience.
Ian Robinson takes a look at how size, structure and connectedness have converged to change the way we work with data, showing some new opportunities with connected data illustrated with graph search.
Volker Pacher, Sam Phillips present key differences between relational databases and graph databases, and how they use the later to model a complex domain and to gain insights into their data.
Justin Moore shares how Facebook's own advances in Data Science have solved intricate location technology problems and how these lessons can be applied to other verticals to achieve similar gains.
Simon Redfern presents how the Open Bank Project innovates by leveraging open APIs, open source and open data, making banking data more accessible via an ecosystem of apps and services.
Alvaro Videla shows how to build a system that can ingest data produced at separate locations and replicate it across regions using RabbitMQ.