{"product":{"product_id":"0764599445","title":"Building the Data Warehouse","price":"48.99","image_url":"https://m.media-amazon.com/images/I/41I9yuDNsYL._SL500_.jpg","url":"https://www.amazon.com/dp/0764599445"},"comments":[{"body":"Also [Building the Data Warehouse - Inmon](https://www.amazon.com/dp/0764599445/ref=cm_sw_r_apan_glt_i_G903E2RH21W0MG5456H9)","subreddit_name":"BusinessIntelligence","author":"TidePodSommelier"},{"body":"If you plan to read Kimball, I recommend that you read Inmon as well like [Building the Data Warehouse](https://www.amazon.com/Building-Data-Warehouse-W-Inmon/dp/0764599445). It will give you another point of view. While Kimball focuses on the usability for queries (front-end), Inmon focuses more on making the clean integration of data sources (back-end).\r\n\r\nIf you have a lot of time you can look for the [Data Vault structure](https://danlinstedt.com/solutions-2/data-vault-basics/). The approach uses a very granular modelization. My point of view is that it is too much modeling work and slow to query. It seems overkill to me but you can make your own judgment.\r\n\r\nThe [Data Lake notion](https://www.blue-granite.com/blog/bid/402596/top-five-differences-between-data-lakes-and-data-warehouses) is probably overkilled as well for you but good to know. The idea is that you dump every data you have in a low-cost data store (Hadoop usually) before processing it.\r\n\r\nYou can also read [my point of view here](https://dataintoresults.com/docs/manifesto.html?utm_source=reddit\u0026amp;utm_medium=reply\u0026amp;utm_campaign=reddit-1). It's basically taking ideas from all of those within a simple and agile framework.","subreddit_name":"BusinessIntelligence","author":"DataIntoResults"}]}