Slowly Changing Dimensions & their types

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Slowly Changing Dimensions

                   Slowly changing dimensions, referred as SCD, can be modeled basically in 3 different ways based on whether we want to store full histories, partial histories or no history. These different types are called Type 2, Type 3 and Type 1 respectively.

                        The "Slowly Changing Dimension" problem is a common one particular to data warehousing. In a nutshell, this applies to cases where the attribute for a record varies over time. For example: Consider table Customer. Prasad is a name of customer. He first lived in Mumbai. So, the original entry in the customer lookup table has the following record:

Customer key	Name	State
1	Prasad	Mumbai

                       Later on, he moved to Pune, on January, 2014. Now how will you modify its customer table to reflect this change? This is the "Slowly Changing Dimension" problem.

Generally there are three ways to solve this type of problem, and they are categorized as follows:

SCD Type 1: The new record replaces the original record. No HISTORY is maintained.

SCD Type 2: A new record is added into the table, therefore both old and new record exist.

SCD Type 3: It stores partial history;  In Type 2, whenever the values of the attributes change, we insert new rows                    to the table. In case of type 3, we add new column to the table to store the history.

We will see all SCD types one by one as below:

SCD Type - 1

In SCD type - 1, the new information simply overwrites the original information. In other words, no history is kept. For example  the following table

Customer key	Name	State
1	Prasad	Mumbai

After Prasad moved from Mumbai to Pune, the new information replaces the new record, and we have the following table:

Customer key	Name	State
1	Prasad	Pune

Advantages:

This is the easiest way to handle the Slowly Changing Dimension problem, since there is no need to keep track of the old information.

Disadvantages:

All history is lost. By using this method, it is not possible to trace back in history.

Usage:

About 40% to 50% of the time.

Where to use Type 1:

If  it is not necessary for the data warehouse to keep track of historical changes.

SCD Type - 2

In SCD type - 2, a new record is added to the table to represent the new information. Therefore, both the original and the new record will be present. The new record gets its own primary key. Latest record can be tracked by various ways.

In above example given in above type will become

Customer key	Name	State
1	Prasad	Mumbai

After Prasad moved from Mumbai to Pune, we add the new information as a new row into the table

Customer key	Name	State
1	Prasad	Mumbai
3	Prasad	Pune

 Latest record can be tracked by various ways.

1) Effective and End date concept:

Customer key	Name	State	Eff_dt	End_Dt
1	Prasad	Mumbai	02-Dec	NULL
2	Nitin	Nagpur	02-Dec	NULL

Customer key	Name	State	Eff_dt	End_Dt
1	Prasad	Mumbai	02-Dec	07-Jan
3	Prasad	Pune	07-Jan	NULL
2	Nitin	Nagpur	02-Dec	NULL

2) Versioning:

We can save the history by using the version method also as below

Customer key	Name	State	Version
1	Prasad	Mumbai	1
2	Nitin	Nagpur	1

Customer key	Name	State	Version
1	Prasad	Mumbai	1
3	Prasad	Pune	2
2	Nitin	Nagpur	1

Advantages:

This allows us to accurately keep all historical information.

Disadvantages:

This will cause the size of the table to grow fast. In cases where the number of rows for the table is very high to start with, storage and performance can become a concern.

This necessarily complicates the ETL process.

Usage:

About 50%-60% of the time.

When to use Type 2:

If it is necessary for the data warehouse to track historical changes.

SCD Type - 3 

In SCD type - 3, there will be two columns to indicate the particular attribute of interest, one indicating the original value, and one indicating the current value. There will also be a column that indicates when the current value becomes active. Type 3 design is used to store partial history.

In Type 2 design. whenever the values of the attributes change, we insert new rows to the table. In case of type 3, however, we add new column to the table to store the history.

For example suppose Prasad lived in Mumbai then shifted to Pune then table will be maintained a below:

Customer key	Name	State
1	Prasad	Mumbai
2	Nitin	Nagpur

Customer key	Name	State	State_Old
1	Prasad	Pune	Mumbai
2	Nitin	Nagpur

Prasad again shifted to Kolhapur from Pune the table will be as:

Customer key	Name	State	State_Old	State_Old_1
1	Prasad	Kolhapur	Pune	Mumbai
2	Nitin	Nagpur

Advantages:

This does not increase the size of the table, since new information is updated.

This allows us to keep some part of history.

Disadvantages:

Type 3 will not be able to keep all history where an attribute is changed more than once. For example, if Prasad later moves to Nagpur then the Mumbai information will be lost.

Usage:

Type 3 is rarely used in actual practice.

Where to use Type 3:

If it is necessary for the data warehouse to track historical changes, and when such changes will only occur for a finite number of time.