This Saturday, January 28th sees Data Privacy Day come round again, an international effort to empower individuals and encourage businesses to respect privacy, safeguard personal data and enable trust. As always this should act as a reminder that every individual within an organization requires a basic understanding of their internal privacy rules and regulations.

Accessing data from the manufacturing shop floor is one of the key topics of interest with the majority of cloud platform vendors due to the pace of Industry 4.0 adoption. Industry 4.0, also known as the Fourth Industrial Revolution, refers to the emerging trend of technological transformation in manufacturing and related industries.

It’s 2023 and with the new year comes an opportunity to drive innovation, growth, and digital transformation with data in the face of ongoing economic turbulence. If Snowflake’s report, How to Win in Today’s Data Economy is any indication, data-driven organizations are poised to emerge as the winners of the year with 77% Data Economy Leaders, which is only 6% of those surveyed, experiencing annual revenue growth versus 36% of Data Economy Laggards, the lowest-performing survey group.

Data, data, data. It does seem we are not only surrounded by talk about data, but by the actual data itself. We are collecting data from every nook and cranny of the universe (literally!). IoT devices in every industry; geolocation information on our phones, watches, cars, and every other mobile device; every website or app we access—all are collecting data. In order to derive value from this avalanche of data, we have to get more agile when it comes to preparing the data for consumption.

Scania is at the forefront of a more autonomous, connected, electric future for the transportation industry. Find out why its Head of Data and Information Management uses data mesh—and Snowflake—to make it a reality. Scania is a global truck, bus, and industrial engine manufacturer and offers an extensive range of related services so its customers can focus on their core business.

This Eckerson Group report gives you a good understanding of how the Unravel platform addresses multiple categories of data observability—application/pipeline performance, cluster/platform performance, data quality, and, most significant, FinOps cost governance—with automation and AI-driven recommendations.

Marketing data integration is the process of combining marketing data from different sources to create a unified and consistent view. If you’re running marketing campaigns on multiple platforms—Facebook, Instagram, TikTok, email—you need marketing data integration. Why? Because being able to assimilate data from different channels and across multiple marketing touchpoints gives you visibility into the overall impact of a campaign, event, or another marketing effort.

Built with BigQuery: How Tamr delivers Master Data Management at scale and what this means for a data product strategy

Multivariate time series forecasting allows BigQuery users to use external covariate along with target metric for forecasting.

Google Cloud customers who want app-level encryption in hybrid cloud data warehouses can encrypt and decrypt that data outside BigQuery. Here’s how to do that securely.