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  1. Exchange Discount Summary
  2. School of the Supernatural
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When there was a promotion going on, the unit price had a different calculation:. There was also a Line discount amount and an Onder discount amount. I added all the columns into the Sales fact. Conformed fact. A conformed measure in multiple facts must use the same common business rule and definition so multiple facts can be united in a report or a cube.

When several data marts are using fact data with same name of fact tables or name of columns for measures and they have compatible calculation methods and units of measure and support additivity across business processes. If a measure e. Factless fact. A fact table that contains no measures is called factless or measureless fact. Sometimes a factless fact has a value column called Count with only one value as 1 used in a data access tool to sum over and get the number of rows. In case the fact grain is weekly and a week is missing, it can be inserted to have all weeks complete and here will Count gets the value 0.

Factless fact is for registration of event or assignment e. If we add a measure column for Attendence with 1 or 0 per date per student it is not a factless fact anymore. Factless fact can be used to represent a many-to-many relationship among dimensions. Capture a relationship in the fact. To be a column in a dimension or to be its own dimension and used in a fact is a good question. Therefore the fact capture a relationship among accounts, products and branches.

Another example is that an account can belong to two customers and a customer can have several accounts. This many-to-many relationship can be expressed in a factless fact or in a bridge table, see later.

Exchange Discount Summary

A bank transaction is done by one customer from an account and it is natural to have a Customer dimension in the fact. An example is a retailer SuperChemi belongs to a chain Ethane at date of sale e. In the retailer SuperChemi changes to another chain Propane but we still keep the registered relationship back in and in the fact.

When a chain is not a part of the fact table and we in year like to find sales of retailers for a specific chain e. Transactional fact or Transaction fact. A fact table that describes an event or operation that occurred at a point in time in a source legacy system e. The row has a date e. If data needs to be changed, corrected or cancelled in source legacy system, then a data warehouse needs to make a counterpart row in the fact with a new time stamping or a time span.

See more in section 6. I prefer multiple facts where the date dimension is role-playing for e. Periodic snapshot fact. When a month or a year is over and data is ready, data will be loaded. Sometimes data for the current month is also loaded every day for a current-month-to-date, therefore the current month will be updated until it is over, finish and can be closed. Measures can be a balance in account or inventory level of products in stock and so on.

School of the Supernatural

Key values for dimensions is found at the end of the period. Accumulating snapshot fact.

A fact table that describes a process with milestones of multiple dates and values columns with different names which will be filled out gradually. Each stage of the lifecycle has its own columns e. In a retail store a product has three movements as ordered, received and sold that would be three date dimension columns in an accumulating snapshot fact.

A fact table where a row is a summarize of measurement events occurring at predictable steps between the beginning and the end of a process.

The next ETL process will do a summarize of payment per customer from the Begindate to current date or end-of-month date, and then update the fact row with same BeginDate with the new summarized payment and new EndDate, so a fact row will be revisited and updated multiple times. Derived fact or Additional fact. A derived fact can be based on multiple fact tables for making faster ad hoc query performance and simplify queries for analysts and for providing a dataset to the Presentation interface area. Aggregate fact or Summarized fact.

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An aggregate fact is derived from a base-level fact and measures in an aggregate fact is a computed summary of measures in the base-level fact. Year-to-Date ytd fact where month February is a summing up or roll up of January and February and so forth. Aggregate fact table is simple numeric roll up of atomic fact table data built solely to accelerate query performance.

It is called incremental aggregation when a ETL process do a dynamically update of a table by applying only new or changed data without the need to empty the table and rebuild aggregates. Consolidated fact. A consolidated fact is a derived fact table that combine data from other facts.

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Smashed fact. A fact table contents several measures but only one or few of them has a value in each fact row. For the fact rows with same dimension member repeated in multiple contiguous rows with identical values, they will be smashed or collapsed into one fact row using operation as sum, min or max to limit the number of rows in the fact. Time span fact. A fact table used for a source legacy system that is regularly updatable meaning that the source change and overwrite its values.

It is called Slowly Changing Facts. Counterpart fact negating fact and Transactional fact. A fact table used for Slowly Changing Facts because the source legacy system is changing fact value without keeping the old value as a historical transactions. Column wise fact and Row wise fact. A column wise pivoted fact table is useful to be columns in a report e.

For a cube a row wise is much better because it gives good dimensions e. Period, Entry, Amount. Therefore a data warehouse needs to convert from columns to rows or vice versa. Exploded fact. A fact table contents huge number of rows where a period e. Other fact classifications. Transaction has one row per transaction when they occur together with a datetime. For example, an application for a bank loan until it is accepted or rejected or a customer or working relationship.

These fact tables are typically used for short-lived processes and not constant event-based processes, such as bank transactions. An example of a status column in a fact table that receive data from a school system where a student follow a course and later finish it, but sometimes a student skip the course and are delete in the system.

Before reload the fact it can be a good idea to have a CourseStatus column with values like: Active, Completed or Dropped.

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Purpose of a dimension. Some purposes as I seen it:. A dimension can of course be non-hierarchical and non-grouping. Different dimensionality covers the issue that not all combination of multiple dimension values are allowed in a fact and the data warehouse needs to make sure of the data quality. Dimension keys. Primary key is a surrogate key identity column a unique sequence number to remove dependence from the source legacy system and for using in fact table foreign key.

Business key is from a source legacy system and can be a primary key or another column that has unique values. In section 1. The key value is not immutable but is meaningful for a human being that a business user prefer to use to identify a thing and as a search lookup value giving in a phone call to a company, a bank, a hospital or to the government. An alias is an Enterprise wide business key because the same value is used in multiple source legacy systems.

Surrogate key is from a source legacy system and is most often a primary key as an auto-generated unique sequence number or identity column id, uid , that is immutable and meaningless for a human being. The value of a business key can change over time e. Changing dimensions.

Source data is volatile data because they will change over time e. Columns of a dimension that would undergo changes over time. A dimension column that changes frequently. If you do need to track the changes, using a standard Slowly Changing Dimensions technique can result in a huge inflation of the size of the dimension. A single fixed value does not change over time but can be corrected in case of an error in a source legacy system , e. The history of data values is lost forever. A fact table refers to a dimension value most recent, as-is.

A fact table refers to a dimension value in effect when fact data occurred, as-was, often by a date column in fact table based on source data or by a current load insert date when the fact data was entered into the fact table or was created, born or occurred. A view upon the fact will provide the current keys to join to dimension view. A column called IsCurrent has two values: 0 for historical and 1 for current to mark each data row of a type 2 dimension.