My first day at the data school we began with focusing on core concepts in data. A specific take away for me was learning the terminologies:
Structured data is typically arranged in tables with rows and columns. Rows are often identified as individual transactions and columns consist of the data fields not forgetting their headers! Common forms are: .xslx .csv .txt
Unstructured data is thought of as data that isn’t sorted or managed and often consists of collections of data. These can include documents, emails, social media posts and videos e.c.t.
Databases is and collection of organized and structured data stored electronically. i.e MongoDB
Data Warehouse is a collective storage unit for your data. It stores structured data that is defined by schemas to organize your data into labeled boxes. A warehouse may contain historical data as well as current data. i.e Oracle
Data Lakes is a ‘lake’ or ‘reservoir’ that stores both structured and unstructured data. i.e AmazonS3
Data Lakehouse, as given in the name is a combination of ‘warehouses’ and ‘lakes’ offering flexible analysis with a variety of data types. i.e Databricks Data Intelligence Platform