Google’s new BigQuery features speed up analytics in cloud data warehouse

Get a free Techzine subscription!

On Thursday, Google added new speed-boosting features to its BigQuery cloud data warehouse. With the new capabilities, the company says that enterprises will be able to run analytics workflows up to 4-5 times faster in some cases.

BigQuery is a service in Google Cloud that companies can use in data analysis from their operations to gathering business intelligence.

It is best suited to tasks like inferring customer buying trends and predicting the number of packages that will go through a fulfillment center in a future quarter. The first enhancement added can create what they call materialized views.

Materialized views

In database terms, a materialized view is a cached copy of records accessed or used frequently.

The records can be inventory for store management. Regular access is a part of inventory management, meaning that companies spend more on data. Making such information appear as materialized views means that queries are sped up, reducing wait times.

When BigQuery has to fetch a frequently used dataset, it can load it up quickly from ready-to-use materialized views in the cache, instead of going through a company’s entire database to find the information.

Saves time and cloud bills

The sped-up version of BiqQuery will be more noticeable to users who make computationally intensive queries. Some of the queries are not just for data retrieval but can sometimes include processes like calculations.

A ready-to-use copy of the results will mean the results come back much faster, cutting cloud bills and saving a lot of time.

Google first showed off the materialized view feature alongside upgraded to the BI Engine component in BigQuery. Last July, the company debited BigQuery Omni, a version of the data warehouse that can analyze information that is in competing cloud providers like Azure and AWS.