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What are types of dimensions?

Joe Ford

What are types of dimensions?

Types of Dimensions are Conformed, Outrigger, Shrunken, Role-playing, Dimension to Dimension Table, Junk, Degenerate, Swappable and Step Dimensions. Five steps of Dimensional modeling are 1.

What are the different types of slowly changing dimensions?

Very simply, there are 6 types of Slowly Changing Dimension that are commonly used, they are as follows:

  • Type 0 – Fixed Dimension. No changes allowed, dimension never changes.
  • Type 1 – No History.
  • Type 2 – Row Versioning.
  • Type 3 – Previous Value column.
  • Type 4 – History Table.
  • Type 6 – Hybrid SCD.

What is slowly changing dimension with example?

Slowly Changing Dimensions (SCD) are the most commonly used advanced dimensional technique used in dimensional data warehouses. Slowly changing dimensions are used when you wish to capture the changing data within the dimension over time. There are three methodologies for slowly changing dimensions.

What is difference between star and snowflake schema?

Star schema contains a fact table surrounded by dimension tables. Snowflake schema is surrounded by dimension table which are in turn surrounded by dimension table. A snowflake schema requires many joins to fetch the data. A Galaxy Schema contains two fact table that shares dimension tables.

How do you test for slowly changing dimensions?

Testing Type 2 Slowly Changing Dimensions using ETL Validator

  1. Testing SCD Type 2 Dimensions.
  2. Test 1: Verifying the Current Data.
  3. Test 2: Verifying the uniqueness of the key columns in the SCD.
  4. Test 3: Verifying that historical data is preserved and new records are getting created.

What is slowly changing dimension in SQL?

The Slowly Changing Dimension transformation coordinates the updating and inserting of records in data warehouse dimension tables.

What is 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). For example, you can have a factless fact table to capture student attendance, creating a row each time a student attends a class.

How do you create a slowly changing dimension in Informatica?

  1. Extract all records from the source.
  2. Look up on the target table, and cache all the data.
  3. Compare the source data with the target data to flag the NEW and CHANGED records.
  4. Filter the data based on the NEW and CHANGED flags.
  5. Generate the primary key for every new row inserted into the table.

How do you implement SCD Type 3 in Informatica?

SCD – Creating a Type 3 Dimension Mapping

  1. Drag and Drop required source and target instance to the mapping work space.
  2. Add the lookup to the mapping to check whether the income row/data is exist in target or not.
  3. Lookup transformation will be created which is same as target instance.

How would you implement SCD Type 2 in SQL query?

Step: Transformations

  1. Each MERGE must have a column key: set “Business Key” for column [Id]
  2. Set “SCD1” for columns [Name] and [Telephone] as we want to update these fields every time.
  3. Set “SCD2” for column [Address] as we want to create a new row in dimension table once the value change.

How would you implement Type 2 SCD using SSIS and queries?

Now Source data is ready and PFB the steps you have to follow to use Slowly Changing Dimension Transformation to implement Type 2 SCD.

  1. Open SSIS Package and drag a dataFlow Task from toolbox to control Flow Pane as shown below.
  2. Either double click or Right click on Data Flow Task and select EDIT as shown below.

How do you implement SCD Type 2 in Pyspark?

Implement SCD Type 2 Full Merge via Spark Data Frames

  1. Objective. Source data:
  2. Imports the required packages and create Spark context.
  3. Create the target data frame.
  4. Create source data frame.
  5. Implement full join between source and target data frames.
  6. Implement the SCD type 2 actions.
  7. Union the data frames.

How do you implement SCD Type 1 in hive?

Type 1 SCD Here’s a sample of our managed table. The MERGE SQL code for Type 1 updates is extremely simple, if the record matches, update it; if not, add it. insert values (stage.id, stage.name, stage. email.

How does Hive handle SCD Type 2?

The most common SCD update strategies are:

  1. Type 1: Overwrite old data with new data.
  2. Type 2: Add new rows with version history.
  3. Type 3: Add new rows and manage limited version history.

Why hive does not support update?

Hive doesn’t support updates (or deletes), but it does support INSERT INTO, so it is possible to add new rows to an existing table. Delete has been recently added in Hive version 0.14 Deletes can only be performed on tables that support ACID Below is the link from Apache .

How do I join two big tables in hive?

If the tables don’t meet the conditions, Hive will simply perform the normal Inner Join. If both tables have the same amount of buckets and the data is sorted by the bucket keys, Hive can perform the faster Sort-Merge Join. To activate it, you have to execute the following commands: set hive.