Data Architecture
The strategic planning for your Enterprise Data
Overview
Data Architecture is the planning of your data. Think of a business as a master planned community. The houses are each system you might be running. The data architecture is how it is planning out so everything works together, especially the common elements that is shared by everyone such as streets, sewers and lighting.
Key Concepts
The most important attributes to data architecture.
Standards
Your organization has standards for data. How do format dates, what can have null values and so forth. Without standards that are both written and specific your team will guess and your data will be a mess.
Data Integration
Data integration gets various data sources to actually talk to each other and removes data silos. In many companies data is spread across the organization in files, documents, and a variety of apps.
Data Modeling
Data modeling matches data needs agains business requirements. The two common data modeling techniques are Conceptual, Logical, Physical and Bronze Silver Gold layers.
Master Data
Master data deals with the most commonly used data in your organization. Customers, Team Members, Products and Locations are all examples of master data.
Data Quality
Data quality matters and it doesn't happen by accident. With high quality data you make good decision, your system work well and you understand your customers.
Privacy
Honoring customer privacy by following established standards and regulations for your industry and operating locations is highly important and adds value to the business.
Related Topics
The topics with the most overlap to data architecture are Data Engineering and Database Design.