![]() ![]() These SCD fields are added so that when a field is changed, for example, a customer’s address, the existing record in the dimension table is updated to indicate that the record isn’t active and a new record is inserted with an active flag. These fields are collectively referenced as the SCD fields (as shown in the following code) going forward in this post. For example, record effective date, record end date, and active record indicator are typically added to track if a record is active or not. The first step to implement SCD for a given dimension table is to create the dimension table with SCD tracking attributes. In this post, we only show the important SQL statements the complete SQL code is available in scd2_sample_customer_dim.sql. lab2_cluster.yaml – Creates a new cluster and loads TPC data.lab2.yaml – Loads TPC data into an existing cluster.To get started, we use one of two AWS CloudFormation templates from Amazon Redshift Labs: The following diagram shows how a regular dimensional table is converted to a type 2 dimension table. The following figure is the process flow diagram. We show how to create a type 2 dimension table by adding slowly changing tracking columns, and we go over the extract, transform, and load (ETL) merge technique, demonstrating the SCD process. To demonstrate this, we use the customer table from the TPC-DS benchmark dataset. We go through the best practices and anti-patterns. This post walks you through the process of implementing SCDs on an Amazon Redshift cluster. Type 3 (Previous value) – The value for specific columns in maintained as a separate attributeįor this walkthrough, you should have the following prerequisites:.Type 2 (Maintain history) – All changes are recorded and versions are tracked with dates and flags.Type 1 (No history) – The dimension table reflects the latest version no history is maintained.Type 0 is when no changes are allowed to the dimension, for example a date dimension that doesn’t change. The range of options for dealing with this involves SCD management methodologies referred to as type 1 to type 7. For historical reporting purposes, it may be necessary to keep a record of the fact that the customer has a change in address. This phenomenon is called a slowly changing dimension (SCD). For example, the shipping address for a customer may change. Over time, the attributes of a given row in a dimension table may change. Dimension and fact tables are joined using the dimension table’s primary key and the fact table’s foreign key. Rows in a dimension table are identified using a unique identifier like a customer identification key, and the fact table’s rows have a referential key pointing to the dimension table’s primary key. The attributes (or columns) of the dimension table provide the business meaning to the measures of the fact table. In a star schema, a dimension is a structure that categorizes the facts and measures in order to enable you to answer business questions. A star schema is a database organization structure optimized for use in a data warehouse. Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. ![]()
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