Scaling Through Simplicity—How a 300 million User Chat App Reduced Data Engineering Efforts by 70% - Databricks

Scaling Through Simplicity—How a 300 million User Chat App Reduced Data Engineering Efforts by 70%

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Moving at the speed of a startup often means rapid iterative development, which can lead to a patchwork of systems and processes. In the early days at Kik (one of the most popular chat apps among U.S. teens), the data team was able to move extremely quickly but often at the expense of scalable data engineering. In this session, Kik’s head of data will share the eight things they did to save time and money. The team took their data stack from a complex combination of systems and processes to a scalable, simple, and robust platform leveraging Apache Spark and Databricks to make data super easy for everyone in the company to use.

About Joel Cumming

Joel is the Head of Data at Kik, where he leads a team of data engineers and data scientists. Prior to joining Kik, Joel led analytics and big data teams at BlackBerry during its growth from 3 million to 80 million subscribers. Joel has multiple data related patent filings on topics ranging from mobile advertising to determining interests from location. Outside of work, Joel’s passion lies in leveraging data for social good, and has worked with several not-for-profits focused on improving access to clean water and education in Africa.