What is the best data type for a fact table column?

The choice of the best data type for a fact table column depends on the type of data it represents. Numeric data types like INT or DECIMAL are suitable for counts and quantities, while DATE or TIMESTAMP data types are ideal for time-based data. BOOLEAN data types work for binary values, and enumerated types (Enums) are suitable for columns with a finite set of values. Custom data types can be used when data doesn't fit into standard categories. Selecting the appropriate data type optimizes storage, query performance, and data accuracy, aligning with data warehousing systems, reporting, and analytics requirements.

Fact tables contain measurements of a business process and are in numbers, most often integers or floating-points. Fact tables also include Keys to join them with dimension tables which describe the business process.

Boolean is probably the most efficient for storage - however, in many cases users do not understand the boolean correctly (as they are used to yes/no or similar text selectors). Boolean also introduces ambiguity on how to handle missing data (true/false.. or null or maybe not known yet or maybe not verified..). Sometimes it is a good idea to create views that cast stored boolean values to text for ease of use; also it might be a good idea to add another boolean to indicate if value is missing or unverified depending on your use case.

Date and time is hard - there's no way around it. First of all each application tends to record datetimes in own ways. Then there are regional settings. And completely different calendars (gregorian, chinese, hebrew, etc., etc.). And time zones - or not - depending on your actual data source. Traditional way to handle date issues is to avoid usage of datetime in your fact tables completely and only point to calendar dimension that has all possible representations of dates in the world (or at least as many as your users need). Often instead of single datetime field 3 fields are in use: - date as a pointer to date dimension - time as a standard 24h59min59sec000ms time format - timezone as a pointer to timezones dimension.

Storing redundant Textual information is not desired. Having Text as data type is going to consume more storage space and should always be designed to identify a suitable dimension to be stored in to avoid repetitive storage.

Based on my professional experience in the field of finance, I have frequently selected the 'Int' data type for fact tables. The basis of this decision was the characteristics of our data. The majority of the external keys in fact tables pertained to dimension tables, which contained integer values. In addition, they contained quantities, counts, and volumes of transactions, as well as sales volume. The utilization of 'Int' guarantees streamlined storage and rapid query execution. Nevertheless, it is imperative to ensure that the data type selection corresponds precisely with the characteristics of the data in order to preserve precision and maximize efficiency.

The choice of data type for a fact table column in a data warehouse depends on the nature of the data being stored in that column. Fact tables typically store quantitative or numerical data related to business transactions or events. Here are some common data types used for fact table columns: 1. Integer (INT or BIGINT) 2. Decimal or Numeric 3. Float or Real 4. Date or Timestamp 5. Boolean (BIT) 6. Surrogate Key 7. Currency Codes 8. Flags or Enumerations It's important to choose the data type that best matches the nature of the data in your fact table column and consider the size and precision required. Additionally, ensure that data types are consistent with the data warehouse design and the analytical needs of the business.

The best practice is to ensure to cover the fields with below category of data type in a fact table and should make efforts not to add beyond these as much as possible to have a performant fact table. > Numeric /additive fields to report over various metrices > Temporal Field (Date/DateTime) to have timebound insights > Flag Fields (Boolean). To have direct slices. Anything other than these that are string/textual/repetitive values etc; should be place in relevant dimension tables to -Avoid more storage space; -Reduce resource intensive updates on Fact and -Increase the search efficiency.