A data architecture is the foundation of any data strategy. It is the “how” when implementing a data strategy.
In this article, we’ll look at:
- Business agility
- Data architecture
- Architecture components
- Data standards
- The shift to new architecture
Data schemas
The architecture is responsible for setting the data standards that define what kinds of data will pass through it.
These standards can be achieved by creating a data schema. The data schema defines:
- Each entity that should be collected. Schema for contact info, for example, might include name, phone number, email, and place of work.
- The type of data each piece should be. For example, name is text data, phone number is integer data, email is text data, place of work is text data.
- The relationship of that entity to others in the database, such as where it comes from and where it’s going.
Data security
Data standards also help set the security rules for the architecture. These can be visualized in the architecture and schema by showing what data gets passed where, and, when it travels from point A to point B, how the data is secured.
Security protocols can include:
- Encrypting data during travel
- Restricting access to individuals
- Anonymizing data to decrease the value of the information upon receipt by receiving party
- Additional actions