Wie können Sie die richtige, sich langsam ändernde Dimension für Ihre Daten identifizieren?

Dim_customer_360 generally uses Type 2 but Why? There are many reasons behind it and below are some questions you can ask yourself before choosing the right SCD Type. 1. How much history you want to store? 2. Is the storage space matters for you? 3. How often you are going to query the history? Depending on above question you can choose the right SCD type for your table.

Business Requirements: Identify key attributes that impact historical analysis (e.g., customer status, product categories). Change Frequency: Evaluate how often attributes change to determine SCD type (e.g., Type 1 for rare, Type 2 for frequent changes). Data Volume/Complexity: Consider the volume and complexity of changes when choosing between SCD types (e.g., Type 3 for tracking multiple historical values).

Muy clara la explicación del SCD Tipo 0. Lo interesante es que, aunque su simplicidad lo hace atractivo para ciertas implementaciones, muchas veces se subestima el costo oculto de no contar con trazabilidad histórica. En entornos donde las decisiones estratégicas se apoyan en evolución de datos —como pricing, segmentación o comportamiento de clientes— no tener visibilidad sobre los cambios puede limitar el análisis longitudinal y la mejora continua. ¿Han tenido casos en los que migrar de Tipo 0 a Tipo 2 ha marcado la diferencia en la calidad de los insights?

A. Business Reporting Needs If only current values are needed → Use Type 1. If full historical tracking is required → Use Type 2. If partial history tracking is needed → Use Type 3 or Type 6. B. Frequency of Data Changes Rarely changing attributes → Type 0. Frequently updated attributes → Type 1 or Type 2 . C. Performance & Storage Considerations Type 2 increases storage and ETL complexity due to multiple historical rows. Type 3 keeps history compact but limits tracking depth. Type 4 can help balance performance by separating history into a dedicated table. D. Compliance & Auditing Needs Regulatory requirements may require full history (Type 2). Operational reporting may only need latest values (Type 1).

I've found that Type 1 SCD is best for attributes that don't require historical tracking, like phone numbers or product descriptions. The old data is overwritten with new values, simplifying maintenance but losing any record of past changes. In my experience, this approach works well for fields that change often but have little business value from a historical perspective. I confirm with stakeholders they don’t need older values, letting me confidently implement Type 1 and focus resources on more critical data. I’ve also used it for small attributes, reducing transformations and storage costs. I use it for minor updates that don't significant affect decisions or trends. Type 1 is ideal for simple changes that don't need historical tracking.

I’ve found that Type 2 SCD is the right choice when I need to keep complete historical records of dimension attributes. I add a new row each time something changes, storing old and new values and start and end dates. Although it increases complexity and storage needs, it’s been vital for auditing and historical reporting, especially for tracking things like shifts in customer addresses or product prices over time. I’ve had projects where failing to implement Type 2 meant losing key insights about how the data evolved. The overhead is typically worth it, since you can run meaningful trend analyses and compliance checks, letting teams see exactly what was valid at any given time. That’s held true across various industries I’ve worked with.

Slowly Changing Dimensions (SCD) are a critical concept in data warehousing. SCDs are those parts of the data warehousing structures that change on an irregular basis and not on fixed time intervals Features of SCDs: Historical tracking Data integrity Type-based classification Versioning Temporal Analysis Type 0( Fixed Dimension): there are no changes. Type 1( Overwrite): overwriting is used where the new value simply replaces the old value that was already stored. Type 2( Add New Row): Each time a new record is added, a new surrogate also gets created. Type 3(Add New Attribute): It is suitable where only the last change needs to be retained. Type 4( History Table): They employ the use of Current table and/ or Historical table.