3Vs of Big Data

Volume: Terabytes to Petabytes to Exabytes

Variety: Structured, Semi structured, Unstructured

Velocity: Batch, Streaming ..

Terminology: Data warehouse vs Data lake

Data warehouse: PBs of Storage + Compute (Typically)

Data stored in a format ready for specific analysis! (processed data)

Examples: Teradata, BigQuery(GCP), Redshift(AWS), Azure Synapse Analytics

Typically uses specialized hardware

Data lake: Typically retains all raw data (compressed)

Typically object storage is used as data lake

Amazon S3, Google Cloud Storage, Azure Data Lake Storage Gen2 etc..

Flexibility while saving cost

Perform ad-hoc analysis on demand

Analytics & intelligence services (even data warehouses) can directly read from data lake

Azure Synapse Analytics, BigQuery(GCP), Redshift Spectrum(AWS), Amazon Athena etc..