We’ve curated some of the big news surrounding structured data for the week to help you stay on top of changes and news:
Over the past few weeks, there have been rumblings across the community about the Google search results not working as expected. Barry Schwartz provides an overview of the issue.
In late 2015, JR Oakes and his colleagues undertook an experiment to attempt to predict Google ranking for a given webpage using machine learning. This article covers their findings.
Sites that display intrusive interstitial ads will be ranked lower by Google from January 10th 2017, the company said in a blogpost. In addition to this, Google will remove the mobile friendly label from the mobile web search, as the company mentions more than 85% of search results now meet this criteria.
At Under Armour, an analytics data warehouse, SQL-based big data processing engine, and machine-learning engine work together to provide business and user insights, personalized recommendations, search enhancements, and data access, but the data innovations won’t end there.
With so many digital images out there, businesses have a prime opportunity to mine those images for consumer insights and other learnings. But how far along are companies in analyzing images and how can they best leverage those insights? Judith Aquino discusses.
According to DB-Engines.com, graph databases have outgrown every other type of database in popularity since 2013, and not by a small margin either. It’s clear that developers, data scientists, and IT pros are just beginning to explore the potential of graph databases to solve new classes of big data analytic and transaction challenges. This article provides five reasons why graph databases are surging in popularity now