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Using BigQuery ML and BigQuery GIS together to predict NYC taxi trip cost

In this article, I’ll walk you through the process of building a machine learning model using BigQuery ML. As a bonus, we’ll have the chance to use BigQuery’s support for spatial functions. We’ll use the New York City taxicab dataset, with the goal of predicting taxi fare, given both pick-up and drop-off locations for each ride — imagine that we are designing a trip planner.

What's happening in BigQuery: integrated machine learning, maps, and more

In this month’s installment of What’s Happening in BigQuery, we’re sharing new features intended to make your life easier: some make BigQuery more performant and more cost effective, while others, like BigQuery ML, enable groundbreaking analysis tools in a cloud data warehouse that’s a first of its kind. First off, we just finished Next ‘18, our annual event focused on all things cloud.

Demystifying Microservices

Are they basically just an evolved version of service-oriented architectures (SOA)? Since a microservice must be exposed via an application programming interface (API) for an organization to scale it to new developers, does that mean managing microservices is basically the same as managing APIs? As this article will discuss, the answer to both of these questions is a clear “no” — and companies looking to get the most from their microservices need to understand why.

Going Serverless with Talend through CI/CD and Containers

Continuous integration, delivery and deployment, known as CI/CD, has become such a critical piece in every successful software project that we cannot deny the benefits it can bring to your project. At the same time, containers are everywhere right now and are very popular among developers. In practice, CI/CD delivery allows users to gain confidence in the applications they are building by continuously test and validate them.