“You can also create custom labels that can consist of any keys and values you choose”
Google’s enterprise data warehouse BigQuery has released new collaboration and public dataset features.
BigQuery enables researchers to conduct Structured Query Language queries within Google Cloud Platform.
Users can investigate their hypotheses using tools such as machine learning on private or public datasets
A simple yet practical feature that has been added is the ability to share queries with colleagues. While looking at your saved queries the user can turn on ‘Link Sharing’ which then makes your query visible to others.
Whenever you make a change or update to the query, others are then able to see the updated query, removing the need to manual copy and message the new version.
A second practical feature added is the ability to sort and filter queries. Users can now sort by an array of settings such as the query’s date, duration, input bytes or slot time.
Users of BigQuery can now also add metadata to their projects and can edit individual column descriptors via the new UI.
BigQuery: Now With More Metadata
Writing in a Google Cloud blog, Michael Saunders Product Manage at BigQuery wrote that: “You can add and edit descriptions for your datasets or tables, making it easier for you and your team members to understand them.”
“You can also create custom labels that can consist of any keys and values you choose, which can serve your team as keywords to search your datasets and tables,” Saunders writes.
Google have also opened up The Google Cloud Public Datasets (GCPD) program, allowing users to connected the public datasets with their own queries.
Launched in 2016 GCPD works with public data providers to store copies of high-value, high-demand public datasets in GCP to make them more accessible and discoverable.
It currently hosts some 3PB of data including Landsat data from the United States Geological Survey (USGS), along with Bitcoin blockchain transactions, GitHub Activity Data and Human Genome Variants.