Data Storage for Analytics and Machine Learning

How do you store data to make it useful? Simple! You put it in a database, or a data warehouse, or a lake, or a lakehouse. It may actually be complex, just a matter of questions you’re trying to answer with data. 00:00 Intro 01:48 Database 03:50 The drawback of databases 06:00 Data warehouse 07:09 Data warehouses: snowflake schema and star schema 10:32 Limitations of data warehouses 12:14 Data lake 14:20 Limitations of data lakes 14:52 Data lakehouses and their three layers Read more in our articles: 1) Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases https://www.altexsoft.com/blog/data-lake-architecture/ 2) Data Warehouse Architecture: Layers, Components, and Schemas https://www.altexsoft.com/blog/data-warehouse-architecture/ 3) Types of DBMS and Databases: Advantages, Limitations, and Best Applications https://www.altexsoft.com/blog/databases-database-management-systems/ Follow us on LinkedIn: https://www.linkedin.com/company/altexsoft/ Follow us on Facebook: https://www.facebook.com/altexsoft/ Follow us on X: https://x.com/AltexSoft Follow us on Instagram: https://www.instagram.com/altexsoftcom/