Redwood City, CA - September 11, 2018 - Talend (NASDAQ: TLND), a global leader in cloud integration solutions, today announced it will debut at the Strata Data Conference in New York City a new sandbox that brings sophisticated machine learning technologies to the hands of developers and data engineers so they can easily create smarter data pipelines.

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.

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.

Have you heard about the new buzz term in analytics, “Deep Learning”? Although it might seem like some obscure, abstract addition to the already cluttered analytics space, Deep Learning is actually more of a combination of other analytics methodologies that tries to accomplish something better.

Today, almost everyone has big data, machine learning and cloud at the top of their IT “to-do” list. The importance of these technologies can’t be overemphasized as all three are opening up innovation, uncovering opportunities and optimizing businesses. Machine learning isn’t a brand new concept, simple machine learning algorithms actually date back to the 1950s, though today it’s subject to large-scale data sets and applications.