Hello friends, If you are talking about data, database , data-warehouse or big data nothing will complete without schema. Schema plays an important role in Data Platform. Today I am exploring about Schema on write and schema on read in respect of datawarehouse and data lake. Let see differences. Schema on write Structured Data, RDBMS, OLAP / Data-warehouse. Heavy ETL (extract-transform-load) role in data movement. Change in data-model is costly. work well in range of Data Mart. User have set of questions. Business Analysis. Collect Data - Apply Schema - Write Data - Analyze. Schema on read Structure & Un-structured Data. RDBMS, NoSQ & Hadoop. BigData / Data Lake. ELT (extract-load-transform) & Low cost extraction. Schema is just a structured file can be switched dynamically. Ideal for large volume of data. User is exploring data without pre-defined query. Data science & Research. Collect Data - Write Data - Apply Schema- An
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