What is the difference between a fact table and a dimension table?

The fact table contains business facts (or measures), and foreign keys which refer to candidate keys (normally primary keys) in the dimension tables. Contrary to fact tables, dimension tables contain descriptive attributes (or fields) that are typically textual fields (or discrete numbers that behave like text).

What is a periodic snapshot fact table?

(Periodic) Snapshot fact tables capture the state of the measures based on the occurrence of a status event or at a specified point-in-time or over specified time intervals (week, month, quarter, year, etc.). In the design above the sales are rolled up to the month in the Periodic Snapshot fact table.

Does a transactional or snapshot fact table have more dimensions?

Transaction fact table stores data of the most detailed level, therefore, it has a high number of dimensions associated with it. Periodic snapshots – Periodic snapshots fact table stores the data that is a snapshot in a period of time.

What is fact grain dimension and fact table?

Fact tables are data structures which capture the measurements of a particular business process. This collection of dimensional keys is called the grain of the fact. Types of Fact Tables. The three basic fact table grains are the transactional, the periodic snapshot and the accumulating snapshot.

Is a fact table normalized or denormalized?

According to Kimball: Dimensional models combine normalized and denormalized table structures. The dimension tables of descriptive information are highly denormalized with detailed and hierarchical roll-up attributes in the same table. Meanwhile, the fact tables with performance metrics are typically normalized.

Which schema is faster star or snowflake?

The Star schema is in a more de-normalized form and hence tends to be better for performance. Along the same lines the Star schema uses less foreign keys so the query execution time is limited. In almost all cases the data retrieval speed of a Star schema has the Snowflake beat.

Can a snowflake schema have more than one fact table?

The snowflake schema is represented by centralized fact tables which are connected to multiple dimensions.. 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.

What is a row in a periodic snapshot fact table?

A row in a periodic snapshot fact table captures some sort of periodic data — for instance, a daily snapshot of financial metrics, or perhaps a weekly summary of accounts receivable, or a monthly tally of inventory numbers. In other words, the ‘grain’ or ‘level of resolution’ is the period, not the individual transaction.

How are snapshot fact tables used in data warehouse?

This week we will focus on periodic snapshot fact tables. (Periodic) Snapshot fact tables capture the state of the measures based on the occurrence of a status event or at a specified point-in-time or over specified time intervals (week, month, quarter, year, etc.).

What is the grain of a fact table?

The grain for the first fact table is one record per combination of Product, Order Date, and Customer. The grain for the second fact table is one record per combination of Product, Order Date, Customer, Promotion, and Sales Territory.

What’s the difference between a snapshot table and an accumulating table?

Unlike periodic snapshot tables, accumulating snapshot tables are a little harder to explain. To understand why Kimball and his peers came up with this approach, it helps to understand a little about the kinds of questions that were being asked of business in the 90s, which was when the Data Warehouse Toolkit was first written.