Data Transformation using BigQuery: Store massive data, run complex analytical queries | HCL Technologies

Data Transformation using BigQuery

BigQuery can be used to solve data quality issues and perform data transformation. Cleansing can be done by filtering and isolating data from dataset. Cleansing and transforming data on BigQuery leverage the ELT methodology of processing data as opposed to ETL supported by various tools and technologies like Apache Spark. Raw data stored in Cloud Storage (GCS) can be extracted into BigQuery and then can be transformed using BigQuery views, materialized view, store procedure, scripts, functions/ analytical functions, and user defined functions (UDF). BigQuery is widely used for storing massive datasets. It’s used for running complex analytical queries for getting business insights. Download this whitepaper to know more.

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