A data architect is a team member responsible for organizing data, ensuring that at the macro level the data assets of an organization originate from a defined single source or "golden source" and at the micro level are organized in data models. Having a clearly defined target state of golden sources aids the organization in predictably achieving its strategic goals by having high quality data at the ready to help meet strategic goals.
The data architecture should cover all data standards and controls including definitions, goldensources (with their data models) and data quality monitoring as the means to fully manage data.
From a project perspective the data architect will map required elements to the correct goldensource ensuring commonality of definition and use.
The definition of an IT architecture used in ANSI/IEEE Std 1471-2000 is: The fundamental organization of a system, embodied in its components, their relationships to each other and the environment, and the principles governing its design and evolution., where the data architect primarily focuses on the aspects related to data.
In TOGAF (the Open Group Architecture Framework) , architecture has two meanings depending upon its contextual usage:
- A formal description of a system, or a detailed plan of the system at component level to guide its implementation
- The structure of components, their inter-relationships, and the principles and guidelines governing their design and evolution over time.
According to DAMA (Data Management Association), Data Architect is often interchangeable with, but includes enterprise architecture considerations. A DAMA recognized Certified Data Management Professional would have a wide range of such skills.
Translating this to Data architecture helps defining the role of the data architect as the one responsible for developing and maintaining a formal description of the data and data structures - this can include data definitions, data models, data flow diagrams, etc. (in short metadata). Data architecture includes topics such as metadata management, business semantics, data modeling and metadata workflow management.
A data architect's job frequently includes the set up a metadata registry and allows domain-specific stakeholders to maintain their own data elements. This is often implemented in an Master Data Management solution which enables centralized management of business critical data.
Some fundamental skills of a Data Architect are:
- Logical Data modeling
- Physical Data modeling
- Development of a data strategy and associated polices
- Selection of capabilities and systems to meet business information needs
A Data Strategy enumerates the Data Policies each of which commit the organization to codifying a best practice. A policy may specify any one area of data standards; data security or Information Assurance; data retention or data stewardship.
Data architects usually have experience in one or more of the following technologies:
- Data dictionaries
- Data warehousing
- Enterprise application integration
- Metadata registry
- Master Data Management (MDM)
- Relational Databases
- Data retention
- Structured Query Language (SQL)
- Procedural SQL
- Unified Modeling Language (UML)
- XML, including schema definitions (XSD and RELAX NG) and transformations.