Understanding Google BigQuery

Google BigQuery is a data warehouse developed by google which allows users to process heavy datasets from multiple sources in a reasonable amount of time as compared to other databases.

Google BigQuery is accessible via its Classic Web UI, Google Cloud Console and Command line tool. Also BigQuery has its REST API using which various third party tools can use it.

In Google Cloud Console users have access to various cool big data tools such BigQuery ML,Dataflow, Cloud Data Prep. In the Classic Web UI one can only use the BigQuery to access and query datasets

Google Cloud Console

Classic Web UI

Why BigQuery

• Cost Effective: In BigQuery you only pay for what you consume. For storage of tables the pricing is $0.020 per GB and if table in not edited for 90 days, the cost is reduced by half.
  For queries the pricing is  $5.00 per TB where 1 TB per month is free for every user.
• Relatively Fast: Google BigQuery is Petabyte Scale Data Warehouse which uses parallel processing in the back end while querying large datasets or joining multiple sources which makes it less time consuming.
• Scalability: While analyzing the data using BigQuery , the user doesn't need to worry about the memory size or CPU limitations as it automatically scales the size required for the query processing.
• Because of the parallel processing used in BigQuery multiple tasks for example loading,querying the data can be done at same time without causing any lag.
• There are other various Big Data tools in Google Cloud Platform such as BigQuery ML, Cloud Data Prep, AI Pipelines, AI Notebooks that one case with BigQuery for data analysis.