Google’s cloud data warehouse, BigQuery, has enabled organizations around the world to accelerate their digital transformation and empower their data analysts to unlock actionable insights from their data. Using BigQuery ML, data analysts are able to create sophisticated machine learning models with just SQL and uncover predictive insights from their data much faster.
Starting this week, we’re adding new content to the BigQuery Spotlight Youtube series. Throughout the summer we’ll be adding new videos and blog posts focused on helping new BigQuery architects and administrators master the fundamentals. You can find complimentary material for the topics discussed in the official BigQuery documentation.
Data security is an ongoing concern for anyone managing a data warehouse. Organizations need to control access to data, down to the granular level, for secure access to data both internally and externally. With the complexity of data platforms increasing day by day, it's become even more critical to identify and monitor access to sensitive data.
BigQuery Reservations help manage your BigQuery workloads. With flat-rate pricing, you can purchase BigQuery slot commitments in 100-slot increments in either flex, monthly, or yearly plans instead of paying for queries on demand. You can then create/manage buckets of slots called reservations and assign projects, folders, or organizations to use the slots in these reservations. By default, queries running in a reservation automatically use idle slots from other reservations.
Businesses hoping to make timely, data-driven decisions know that the value of their data may degrade over time and can be perishable. This has created a growing demand to analyze and build insights from data the moment it becomes available, in real-time.
Many of you rely on Dataflow to build and operate mission critical streaming analytics pipelines. A key goal for us, the Dataflow team, is to make the technology work for users rather than the other way around. Autotuning, as a fundamental value proposition Dataflow offers, is a key part of making that goal a reality - it helps you focus on your use cases by eliminating the cost and burden of having to constantly tune and re-tune your applications as circumstances change.
With summer just around the corner, things are really heating up. But you’re in luck because this month BigQuery is supplying a cooler full of ice cold refreshments with this release of user-friendly SQL capabilities. We are pleased to announce three categories of BigQuery user-friendly SQL launches: Powerful Analytics Features, Flexible Schema Handling, and New Geospatial Tools.
Many people wonder if they should use BigQuery or Bigtable. While these two services have a number of similarities, including "Big" in their names, they support very different use cases in your big data ecosystem. At a high level, Bigtable is a NoSQL wide-column database. It's optimized for low latency, large numbers of reads and writes, and maintaining performance at scale.
