DataMarts.ArrayVersion

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The introduction of the array version of data marts is designed to enhance flexibility and consistency, particularly in managing regional data that may vary in field type and structure. This approach involves grouping related data fields into JSON-like arrays or structures within SQL. Here’s an explanation of its benefits and mechanics:

Key Points of the Array Implementation:

  1. Unified Data Structure: By converting various field values into array-like structures, we ensure that data from multiple regions can be stored and interpreted in a consistent format. This allows different regions, which might not send identical sets of field values, to be processed without needing separate data models or structures.
  2. Data Grouping: Related fields are grouped into cohesive arrays, making it easier to handle and parse data programmatically. For instance, arrays like ORDER_LINE_SEQ, CODES, STATUS, NOTES, and MARKET encapsulate relevant data points together. This enables streamlined processing and querying as these arrays encapsulate their related data fields within a single output column.
  3. Support for Inconsistent Regional Data: Regions may vary in the types of data fields they report. The use of arrays allows for flexible handling of missing or additional data fields without altering the core data structure. This enhances scalability as new data points can be added to the array format with minimal disruption to existing structures.
  4. Improved Data Parsing: Data consumers, such as downstream applications and analysts, benefit from the organized structure. Parsing JSON-formatted arrays simplifies data extraction and interpretation, particularly for visualisation tools or data processing scripts that are designed to handle hierarchical data.

Example:

The Customer.Orderline dataMart showcases how fields are grouped into JSON-like arrays:

  • ORDER_LINE_SEQ: Encapsulates order keys (ORDER_NO_KEY, LINE_NO_KEY, etc.), making it a clear reference point for all line sequence identifiers.
  • CODES: Groups order-related codes (e.g., ORDER_NO, CUST_ORDER_TYPE, etc.) to simplify access to these values for error-checking or analysis.
  • STATUS: Combines state codes and cancellation reasons, including their descriptions, into a nested structure, providing a comprehensive view of status-related information.
  • NOTES: Puts line descriptions and notes into one array for easy retrieval and review.
  • MARKET: Groups strategic market data (STRATEGIC_PILLAR, SALES_REGION, etc.) to support high-level reporting on sales dynamics.

Benefits:

  • Consistency Across Regions: This structure handles variations in data submission effectively.
  • Scalable Data Modelling: Easily accommodates the addition of new fields or changes in regional data requirements.
  • Enhanced Data Management: Grouping fields reduces the complexity of individual field handling and improves the maintainability of the SQL code.
  • Optimised Parsing and Analysis: The JSON structure aligns with modern data processing needs, facilitating easy transformation for analytical tools and processes.

In summary, the array approach in data marts not only promotes uniformity in handling diverse regional data but also simplifies data management and retrieval, supporting the broader data strategy’s adaptability and scalability.

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