The main idea behind one big table (OBT) is to join all of the data necessary for analytics into wide [[Denormalization|denormalized]] tables. One big table is a popular approach to serving analytics at larger scales and takes advantage of the benefits of [[Column-oriented Database|columnar databases]]. It's usually combined with/built on top of other techniques such as a [[Dimensional Modeling|Dimensional Model]] or [[Data Vault Modeling|Data Vault]]. > [!tip] > You can use OBT when starting new data warehouse to provide value immediately while another longer-term approach is worked on like a [[Dimensional Modeling|Dimensional Model]] or a [[Data Vault Modeling|Data Vault]]. ## One Big Table Advantages - Increases query performance by removing the need for joins. - Simple to query. ## One Big Table Disadvantages - Very wide tables can get messy to read and maintain. - Does not adapt to changes well. Adding new data sources will require rebuilding the table. %% wiki footer: Please don't edit anything below this line %% ## This note in GitHub <span class="git-footer">[Edit In GitHub]( "git-hub-edit-note") | [Copy this note]( "git-hub-copy-note")</span> <span class="git-footer">Was this page helpful? [👍]( or [👎](</span>