Data integration pipelines supply valuable data from producers to consumers, but even the best pipelines can break. Now what?

Where your ELT provider normalizes your data can dramatically increase or decrease your compute costs.

Most organizations spend at least 37% (sometimes over 50%) more than they need to on their cloud data workloads. A lot of costs are incurred down at the individual job level, and this is usually where there’s the biggest chunk of overspending. Two of the biggest culprits are oversized resources and inefficient code. But for an organization running 10,000s or 100,000s of jobs, finding and fixing bad code or right-sizing resources is shoveling sand against the tide.

Retail companies can easily visualize and analyze their geospatial data in BigQuery using the CARTO platform.

This is a guest post by Bill Inmon, known as the father of the data warehouse. In this article, he will discuss how IT organizations often resist text analytics even though it can bring great business value. The article will then go into Bill Inman's experience with IT organizations and text analytics, highlighting the importance of text analytics and how it can be used to gain valuable insights for businesses.

Today, data is the lifeblood of every organization. Without it, you’re left without key insights into business processes, consumers, employees, and the overall health of your entire organization. And here’s the scariest part: most organizations are on life support due to their inability to properly manage their data and turn it into actionable insights. Data fabric technology can help in a significant way, which is why it’s been getting so much buzz recently.

Unify data from diverse sources and formats using Aiven Kafka's open source streaming. Analyze with BigQuery for swift, accurate insights.

Elements of the Google Data Cloud including BigQuery, DataFlow, and Vertex AI are behind Glean’s personalized enterprise search platform.