What is a fact-less fact in data warehouse?
The fact-less fact is often used to resolve a many-to-many cardinality issue. Types of Fact-less fact tables in Data Warehouse? This type of fact table establishes the relationship among the various dimension members from various dimension tables without any measured value.
How big is a fact table in a data warehouse?
Their size can equal many terabytes, and they take the most space in a data warehouse. An error early in the fact table design process generates many problems, which don’t get easier to solve as the warehouse evolves! It is possible to reorganize data from one type of fact table to another.
What are some examples of factless fact tables?
Common examples of factless fact table: Ex-Visitors to the office. List of people for the web click. Tracking student attendance or registration events.
What is factless table in DBMS?
It is essentially an intersection of dimensions (it contains nothing but dimensional keys). There are two types of factless tables: One is for capturing an event, and one is for describing conditions. An event establishes the relationship among the dimension members from various dimensions, but there is no measured value.
What is factless fact in data warehouse?
Factless tables simply mean the key available in the fact that no remedies are available. Factless fact tables are only used to establish relationships between elements of different dimensions. And are also useful for describing events and coverage, meaning tables contain information that nothing has happened.
What is fact table in data warehouse with example?
A fact table is used in the dimensional model in data warehouse design. A fact table is found at the center of a star schema or snowflake schema surrounded by dimension tables. A fact table consists of facts of a particular business process e.g., sales revenue by month by product.
What is junk dimension with example?
A Junk Dimension is a dimension table consisting of attributes that do not belong in the fact table or in any of the existing dimension tables. The nature of these attributes is usually text or various flags, e.g. non-generic comments or just simple yes/no or true/false indicators.
How many attributes does factless fact table have?
There are two kinds of factless fact tables: Factless fact table describes events or activities. Factless fact table describes a condition, eligibility, or coverage.
What are the 3 types of fact tables?
These are:Transaction fact tables.Periodic snapshot tables, and.Accumulating snapshot tables.
What are the three types of fact tables?
There are three types of fact tables and entities: Transaction. A transaction fact table or transaction fact entity records one row per transaction. Periodic.
Why do we use junk dimension?
A junk dimension combines several low-cardinality flags and attributes into a single dimension table rather than modeling them as separate dimensions. There are good reasons to create this combined dimension, including reducing the size of the fact table and making the dimensional model easier to work with.
What is semi additive fact with example?
Semi-additive facts are facts that can be summed up for some of the dimensions in the fact table, but not the others. For example if you have the number of items in the warehouse for each day, you can sum up the items for each day (total warehouse of the day), but it make no senso to sum up in the year.
What is degenerate dimension table with example?
For example, the Oracle FAQ defines a degenerate dimension as a "data dimension that is stored in the fact table rather than a separate dimension table. This eliminates the need to join to a dimension table. You can use the data in the degenerate dimension to limit or 'slice and dice' your fact table measures."
What is the meaning of Factless?
Lacking facts; inaccurate or fictionalfactless (comparative more factless, superlative most factless) Lacking facts; inaccurate or fictional.
What is true about factless fact table?
A factless fact table is a fact table that does not have any measures. It is essentially an intersection of dimensions (it contains nothing but dimensional keys). There are two types of factless tables: One is for capturing an event, and one is for describing conditions.
What are additive semi-additive and non-additive facts?
Semi-additive measures can be aggregated across some dimensions, but not all dimensions. For example, measures such as head counts and inventory are considered semi-additive. Non-additive measures are measures that cannot be aggregated across any of the dimensions.
What is fact table and dimension table with example?
Fact Table vs Dimension Table Comparison TableCharacteristicsFact TableDimension TableCreation TimeA fact table is created after dimension tables are created.The dimension table needs to be created first.Schema StructureThere is less number of fact tables in a schema.There is a number of dimension tables in a schema.10 more rows
What constitutes a fact table what are the various types of facts explain using examples?
The fact table is a central table in the data schemas. It is found in the centre of a star schema or snowflake schema and surrounded by a dimension table. It contains the facts of a particular business process, such as sales revenue by month. Facts are known as measurements or matrices.
What are the 2 kinds of data that a fact tables contain?
A fact table typically has two types of columns: those that contain facts and those that are a foreign key to dimension tables. The primary key of a fact table is usually a composite key that is made up of all of its foreign keys.
How many fact tables are there in data warehouse?
There are four types of fact tables: transaction, periodic snapshot, accumulating snapshot and factless fact tables. Every flavor serves a purpose in representing the underlying business which the data warehousing system supports.
What is a factless table?
By definition, the factless fact table is a fact table that does not contain any facts. There are two kinds of factless fact tables: 1 Factless fact table describes events or activities. 2 Factless fact table describes a condition, eligibility, or coverage.
Can you find measures to track in a dimensional model?
When designing dimensional model, you often find that you want to track events or activities that occur in your business process but you can’t find measures to track. In these situations, you can create a transaction-grained fact table that has no facts to describe that events or activities. Even though there are no facts storing in the fact table, the event can be counted to produce very meaningful process measurements.
What is a factless table?
Factless Fact Table. Factless tables simply mean the key available in the fact that no remedies are available. Factless fact tables are only used to establish relationships between elements of different dimensions. And are also useful for describing events and coverage, meaning tables contain information that nothing has happened.
Why do you need a fact table?
It is used to support negative analysis reports. For example, to create a report that a store did not sell a product for a certain period of time, you should have a fact table to capture all possible combinations. Then you can find out what is missing. Ex-Visitors to the office.
What is a large dimension table?
Large Dimension Tables : Large dimension tables are very deep and wide. Deep means it has a very large number of rows and wide means it may have many attributes or columns. To handle large dimensions, one can take out some mini dimensions from a large dimension as per the interest.
Is it difficult to change a customer's dimensions?
But in the case of customer dimensions, where a number of rows are millions and changes infrequently, then type 2 changes are feasible and not very difficult. If customer dimensions change rapidly, then Type 2 changes are problematic and difficult.
What is a factless fact table?
A Data Warehouse fact-less fact table is a fact that does not have any measures stored in it. This table will only contain keys from different dimension tables. The fact-less fact is often used to resolve a many-to-many cardinality issue.
Can a factless fact table answer a positive query?
A fact-less-fact table can only answer ‘optimistic’ queries (positive query) but cannot answer a negative query. Coverage fact is used to support negative analysis reports. For example, an electronic store did not sell any product for give period of time.
What is a factless table?
Factless Fact Table. A factless fact table is a fact table that does not have any measures. It is essentially an intersection of dimensions. On the surface, a factless fact table does not make sense, since a fact table is, after all, about facts.
Why is adding a fact that always shows 1 redundant?
However, adding a fact that always shows 1 is redundant because we can simply use the COUNT function in SQL to answer the same questions.
How to create a fact table?
Here is an overview of four steps to designing a fact table described by Kimball: 1 Choosing business process to a model – The first step is to decide what business process to model by gathering and understanding business needs and available data 2 Declare the grain – by declaring a grain means describing exactly what a fact table record represents 3 Choose the dimensions – once the grain of the fact table is stated clearly, it is time to determine dimensions for the fact table. 4 Identify facts – identify carefully which facts will appear in the fact table.
What are the different types of measures in a fact table?
Measure types. Fact table can store different types of measures such as additive, non-additive, semi-additive. Additive – As its name implied, additive measures are measures which can be added to all dimensions.
What is a factless table?
Factless fact table. A factless fact table is a fact table that does not have any measures. It is essentially an intersection of dimensions (it contains nothing but dimensional keys). There are two types of factless tables: One is for capturing an event, and one is for describing conditions.
What are the two types of factless tables?
There are two types of factless tables: One is for capturing an event, and one is for describing conditions. An event establishes the relationship among the dimension members from various dimensions, but there is no measured value. The existence of the relationship itself is the fact.
What is a fact table?
In the most general sense, fact tables are the measurements of a business process. They hold mostly numeric data and correspond to an event rather than a particular report. The most important feature of a fact table, besides measures, is grain. Grain defines what level of detail is observed for a particular event.
How many rows are there in a fact_retail_sale table?
Suppose we fill the fact_retail_sale table from two sources: a database table with 100,000 rows and a spreadsheet with 20,000 rows. These rows are filled on a yearly basis. The dimension tables are: dates (365 rows), products (100 rows) and stores (1,000 rows).
What are some examples of measures in a fact table?
They occur when all the important information about the dimension is already in the fact table. Examples include various control header numbers, ticket numbers, order numbers, etc. Measures (i.e. metrics or business facts) in a fact table can be: Additive: summable across any dimension.
What is the common factor in fact tables?
However, before we delve into what these different fact tables do, let’s talk about an important common factor: sparsity, or the proportional amount of data stored in a fact table. Sparsity is related to grain, and it has an effect on query performance.
What is a foreign key in a dimensional table?
Foreign keys to dimensional tables. Foreign keys are self-explanatory; degenerate dimensions also belong to this group. A degenerate dimension is a dimension key with no parent dimension table. They occur when all the important information about the dimension is already in the fact table.
What is the grain of a transaction fact table?
The grain of this type is one row per transaction, or one row per line on a transaction. The grain of a transaction fact table is a point in space and time. They hold the smallest of business details.
What are technical columns? What are some examples?
Technical columns are useful for auditing and low-level maintenance of the model. Timestamps, which are used to mark when insertions or updates occur in the fact table, are a common example of a technical column.