Enterprise Data Architecture in Healthcare Organizations
Enterprise-level data architecture is often discussed in relation to data analytics. The reason for that is because most analytics and analysis is done within the construct of data architecture. Just as the hospital or facility you work in has an underlying structure of columns, steel, and concrete, data warehouses and stores have to be designed around a structure, as well. Thatâ€™s where data architecture comes in. Because understanding this concept is so important, letâ€™s take a moment to break it down and learn more about each component.
What is Data Architecture?
Data architecture is many things. Itâ€™s a system, a structure, and a plan, in some ways. Letâ€™s look at how this architecture works as a system of protocols, a structure for management, and examine the three main components that all data architecture has.
A System of Protocols
Data architecture is a system of protocols that dictates many characteristics and outlines the rules of the data within it. It dictates how data is stored, how itâ€™s transformed and distributed, and what data should be included. It also governs the data management rules, the rules that govern structured formats, like file systems, and the rules for how data is to be integrated and utilized within an organization.
A Structure for Management
Additionally, data architecture acts as a structure for organizational management. It would be a nightmare to have to search through a disorganized and unstructured heap of data every time you needed information about a system, process, or person within your organization. Imagine if you went to a library and the books were thrown onto the shelf in no particular order, so you had to search the entire library every time you wanted a new book. And forget asking the librarian or consulting the directory — neither of those exists. Can you imagine how inefficient that would be? The same is true for data. There has to be a structure and a predictable manner of storage that those who govern the organization can rely on when information needs to be accessed.
3 Main Components of Data Architecture
There are a few major components that all data architectural designs have in common. One is whatâ€™s referred to as â€œdata architecture outcomesâ€. That term refers to models, data flows, definitions, and other similar characteristics as they pertain to the various levels of data. Usually, this component is referred to as data architecture â€œartifactsâ€. The second component is referred to as data architecture activities, which would deal with anything that forms, deploys, or fulfills the intention of the architecture. Finally, there are data architecture behaviors which are all the collaborations, skills, and mindsets among the various organizational roles that affect the enterpriseâ€™s data architecture.
What is Data Architecture Used For?
There are many uses for well-built data architecture. One use is that it facilitates strategic preparation. Another is that it helps to establish business requirements, and a third is that it aligns IT and business systems so everything works together.
Data architecture, when itâ€™s well-designed, allows organizations to quickly react to new opportunities and dodge potential bullets. It also facilitates the early and efficient adoption of technology and data-driven solutions. Furthermore, well-designed architecture can help organizations make decisions faster and more efficiently, and it can also improve enterprise-level management performance.
Business needs need to be translated into a system that includes data requirements suited to each need. Because business knowledge and IT skills donâ€™t often exist in the same group of people, itâ€™s important to have a system that both parties can use so that business professionals can communicate their needs and IT professionals can translate those needs into system requirements as they design the structure for organizational data. Having well-designed data architecture can facilitate this goal.
Aligns IT and Business Systems
Beyond providing a communication portal, data architecture can also facilitate the integration of actual systems. Business interests and functions can be married with IT needs and processes so that the entire organization functions at a higher level, is more integrated, and can better serve those who work in and with the enterprise itself.
Components of Data Architecture at an Organizational Level
Healthcare organizations have many needs when it comes to data. Information needs to be accessed, processed, stored in a place and format where everyone who needs it can access it, be interactive, be secure, and on the list goes. Well-designed data architecture has built-in components that help to achieve the goals of a healthcare organization or any other organization, for that matter.
- Access – Data architecture consists of features and structures that help provide access to those members of the organization who need it.
- Data Processing – Also inherent in most architectural designs is a system of data processing that provides reliable and consistent results, which is essential to the overall functioning of a large organization.
- Cloud Storage – One of the easiest ways to facilitate access is to utilize cloud storage capabilities, and data architecture typically has this component as part of its design.
- Network – Being able to access data from multiple locations both within the physical walls of an organization and anywhere else members might be is critical. Well-designed data architecture includes networking components that facilitate local and remote access.
- Interactive Elements – Not everyone in the organization is data literate or tech-savvy. Because of this, itâ€™s important that interactive elements exist that are easy to use and clear, even to those who donâ€™t have deep technical knowledge.
- Apps – Applications are often the vehicle through which interactive elements are delivered, and as long as theyâ€™re well-designed, this component of data architecture can go a long way to facilitating access.
- Encryption – Nothing else matters if data is not secure, so encryption is a critical component that every data architecture design must have.
Itâ€™s easy to see that many of these components facilitate or feed into each other, and thatâ€™s exactly the point. You canâ€™t have a competent data architecture design without ensuring that multiple components exist that intersect and support each other.
Data architecture is a complex topic that consumes volumes of literature. However, a basic understanding of what it is, what it does, and why itâ€™s useful can go a long way in helping you deepen your knowledge base and add value to your organization. If your organization suffers from a lack of structure where data is concerned, look at your current architecture, consult experts, and see if you might be able to improve it. You might be surprised to find what a small architectural shift can do for an entire enterprise.