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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.

Talend Unveils Bulk Data Uploader to Enable Large-Scale, Real-Time Analytics on Microsoft Azure SQL Data Warehouse

Redwood City, CA - August 16, 2018 - Talend(NASDAQ: TLND), a global leader in cloud integration solutions, unveiled a new bulk data uploader for Microsoft Azure SQL Data Warehouse, which helps empower thousands of users across an organization with a fast, flexible and secure cloud data warehouse.

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.