Mapping data sources:
Understand and generate data map to include descriptions of the business meaning of the data, its uses, its quality, the applications that maintain it and the database technology in which it is stored.
Documenting interfaces and data movement:
Understanding enterprise data and record how it is moved around the "virtual" enterprise. This includes the frequency of movement, the source and destination of each step, how the data is transformed as it moves, and any aggregation or calculations.
Designing the movement of data through the BI/Analytics System.
Defining integrative views of data:
Work with business people and application designers to identify and model integrative views and determine the quality of service requirements data currency, availability, response times and data volumes.
Designing canonical data views: Ensure that the canonical views assist broad range of data transformations as possible.
Defining technical standards and guidelines:
Define Data architecture standards and guidelines to cover when and how to use the architected databases (such as the data warehouse, operational data store, Datalakes), the technologies to be used for various purposes, and models of selected entities, objects and processes. The guidelines should encourage reuse of existing data stores, as well as address issues of security, timeliness and quality.
Proof of Concept:
Participation in proof-of-concept projects and other projects that are early users of new technologies is required from time to time.
Leveraging existing data assets:
Often, developers create new sources of data, rather than reuse those already in existence. This increases fragmentation. Must provide guidelines for reuse and ensure that the architecture management processes include the assessment of all proposals to create new data stores.
Managing related metadata:
Define and maintain metadata to include business descriptions of the data, details of any calculations or summaries, descriptions of the sources of the data, and indications of data quality and currency.
Communicating the data architecture:
Responsible for communicating the benefits of the data architecture directed to a range of stakeholders the development community, IT operations, IT management at all levels, and business people. The EDA must acquire information from these groups to focus the architecture to meet business and IT needs. The EDA also must also help developers use the architecture.
Ensuring a focus on data quality:
Educate the business on data quality importance, and involve and facilitate the work of business constituents on improvement programs. Work effectively with data stewards and to make them understand data semantics and identify opportunities for improving data quality.
College degree in a Technical or related field and 8 years professional level experience with 3-4 years supervisory experience for roles with supervision; or 12 years professional level related Technical experience with 3-4 years supervisory experience for roles with supervision; or an equivalent combination of education and professional level related Technical experience desired.