Data by Design refers to an approach in data engineering that extends the traditional design phase to not only ensure the technical architecture of data systems but also focus on various aspects related to data quality, management maturity, intended use, and risk prevention. It encompasses a comprehensive strategy to deliberately shape and structure data systems while considering potential risks such as privacy concerns, geo-residency, access control, biases, and ethical implications. In essence, it is an inclusive framework that emphasizes the proactive consideration and integration of risk management strategies throughout the entire life cycle of data, from its initial conception to its utilization in different applications.
Data by Design involves the following:
- Data architecture and platforms: These are key to naming, taxonomy, data linkability, reusable design frameworks, scalability, performance, velocity, and self-service capabilities. ...
