In order to reach more standardized practices, improving the abilities on product development and maintenance, Application Labbooster is target standard data architecture principles.
The Data Architecture principles must provide an efficient data structuration to serve the business needs, not only for the product under development, but also for all R&I function, under the vision to be integrated in a next future into the Solvay Data Ocean. The Data Architecture brings common definitions on Staging, ODS and Data Mart Data structuration stages across the dev team, and through continuous improvement, it capitalizes on the good practices (for instance data compression, table partitions, star schema)
Target Data Architecture for ALB
Buckets
This area is used for consolidating and load Buckets into the GCP.
The consolidation will guarantee that we have one staging table per bucket set and avoid duplicate records/information.
Also use to making some normalization process.
Operational data store is a repository that provides a snapshot of the latest data from multiple transactional systems
for operational reporting.
The ODS will contain historical data for all the extraction coming from the different sources.
Group all the periods extracted to be stored in the google cloud storage.
Structure / access pattern specific to data warehouse environments, used to retrieve client-facing data.
The data mart is a subset of the data warehouse and is usually oriented to a specific business line or team.
Table Type | Table Name | Description |
Fact Table | FCT_xxxx | consists of the measurements, metrics or facts of a business process. |
Dimension Table | DIM_xxxx | Contains relatively static data which can change slowly but unpredictably, rather than according to a regular schedule. |