is an enterprise data warehouse for managing and analyzing big data. It’s fully managed, which means you don't have to set up or manage any server or local infrastructure. It takes care of all your organization's machine learning,
and business intelligence needs using SQL.
BigQuery is particularly useful for organizations that need to make data-driven decisions as quickly as possible. Say you’re a logistics company that runs a chain of drop-off and pick-up points for various items and charges customers based on the type of item they’re delivering, where it is being delivered, or the weight of the delivery item. It means they’ll have to keep a comprehensive record that captures all of these critical data points to prepare an invoice for customers properly.
From this dataset, you may decide to run a query to determine the number of long-distance deliveries you have made every month for the past 10 years. You may have decided to start imposing an extra charge for items beyond a certain delivery distance and would like to know how many of your customers would be affected by this. You’re dealing with an extensive data set, but you must be able to run a query like this as quickly as possible. Google’s Big Query is one of the best ways to get this done partly because it can complete your query in seconds but also because it is serverless, meaning you can run queries without the need to manage infrastructure.
BigQuerty is a scalable and distributed analysis engine. This means you only need seconds to query terabytes of data and some minutes for petabytes. BigQuery also helps to maximize flexibility as it separates the computer engine analyzing data from the storage choices. It allows storage and analysis of your data and can also be used to assess your data from anywhere.