Use of data workflows is a fundamental functionality of any data engineering team. Nonetheless, designing an easy-to-use, scalable, and flexible data workflow platform is a complex undertaking. Tomer Levi walks you through how the data engineering team at Fundbox uses AWS serverless technologies to address this problem and how it enables data scientists, BI devs, and engineers move faster.

Francesco Mucio shares the basic tools he and his team had to learn (or relearn) moving from the coziness of their database to the big world of Spark, cloud, distributed systems, and continuous applications. It was an unexpected journey that ended exactly where it started: with an SQL query.

Apache Impala is an MPP SQL query engine for planet-scale queries. When set up and used properly, Impala is able to handle hundreds of nodes and tens of thousands of queries hourly. Manish Maheshwari explains how to avoid pitfalls in Impala configuration (memory limits, admission pools, metadata management, statistics), along with best practices and anti-patterns for end users or BI applications.

In the analysis of the mobile world, everyone starts with the question, "Where?" SK Telecom is trying to meet these needs. Kyungtaak Noh explains how the company provides geospatial analysis by processing geospatial data through Druid with Lucene.

One day, my kid asked me: Dad, what are you doing at work? That struck me because being an AI and BI practitioner for about 20 years, I have helped clients on a daily basis, but my how do I explain …