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A time dimension with a grain of seconds in a day will only have 86400 rows. A more or less detailed grain for date/time dimensions can be chosen depending on needs. As examples, date dimensions can be accurate to year, quarter, month or day and time dimensions can be accurate to hours, minutes or seconds.
The MultiDimensional eXpressions (MDX) language provides a specialized syntax for querying and manipulating the multidimensional data stored in OLAP cubes. [1] While it is possible to translate some of these into traditional SQL, it would frequently require the synthesis of clumsy SQL expressions even for very simple MDX expressions.
Dimensions can define a wide variety of characteristics, but some of the most common attributes defined by dimension tables include: Time dimension tables describe time at the lowest level of time granularity for which events are recorded in the star schema; Geography dimension tables describe location data, such as country, state, or city ...
Dimensions are the foundation of the fact table, and is where the data for the fact table is collected. Typically dimensions are nouns like date, store, inventory etc. These dimensions are where all the data is stored. For example, the date dimension could contain data such as year, month and weekday. Identify the facts
The snowflake schema is similar to the star schema. However, in the snowflake schema, dimensions are normalized into multiple related tables, whereas the star schema's dimensions are denormalized with each dimension represented by a single table. A complex snowflake shape emerges when the dimensions of a snowflake schema are elaborate, having ...
Data in a DW are organized according to the multidimensional model, that hinges on the concepts of fact (a focus of interest for the decision-making process, such as sales and orders) and dimension (a coordinate for analyzing a fact, such as time, customer, and product).
Example of a star schema; the central table is the fact table. In data warehousing, a fact table consists of the measurements, metrics or facts of a business process. It is located at the center of a star schema or a snowflake schema surrounded by dimension tables. Where multiple fact tables are used, these are arranged as a fact constellation ...
Valid time is the time period during or event time at which a fact is true in the real world. Transaction time is the time at which a fact was recorded in the database. Decision time is the time at which the decision was made about the fact. Used to keep a history of decisions about valid times.