Systems | Development | Analytics | API | Testing

BigQuery Admin reference guide: Query processing

BigQuery is capable of some truly impressive feats, be it scanning billions of rows based on a regular expression, joining large tables, or completing complex ETL tasks with just a SQL query. One advantage of BigQuery (and SQL in general), is it’s declarative nature. Your SQL indicates your requirements, but the system is responsible for figuring out how to satisfy that request. However, this approach also has its flaws - namely the problem of understanding intent.

Why you need metadata management and how to approach it

As your data operations evolve, they become messier. Diverse data sources and data models at their sources, multiple movements of data throughout your platform, and cobbled-up infrastructure, which has grown in complexity through every deployment have made it hard to identify, trace, classify, and understand your data assets. This can be as simple as an analyst spending hours trying to figure out where a data attribute in a table came from and whether it is trustworthy.

Massive Data Transformation With Pepsi | Rise of The Data Cloud Podcast

Interested in how to transfer e-commerce to the cloud, what data transformation looks like on a massive scale, and how to increase your ROI? In this episode, Vaibhav Kulkarni, Head of Data Products & Infrastructure Engineering at PepsiCo, talks about these topics and more. We hope you enjoy! Connect with Vaibhav Kulkarni

Data Onboarding: What You Need to Know

Getting your customer's data on the platform quickly and effectively is crucial for any business. How well you onboard new data will affect your success and your customer's experience. Effective onboarding affects so many aspects of a company's success that it's necessary to take a detailed look into all aspects of the process. The following is everything you need to know about data onboarding.

Four Questions To Accelerate Edge-to-Cloud AI Strategy Development

“More than 15 billion IoT devices will connect to the enterprise infrastructure by 2029.” Finding data is not going to be a challenge, clearly, but taking advantage of it all to drive business outcomes will be. Combining AI and machine learning (ML) with data collection and processing capabilities of the edge and the cloud may hold the answer.