Data Architecture: What is it and Why should we care?

Data Architecture, as understood by most in the industry, has many different definitions. Here is what Wikipedia says – “In information technology, data architecture is composed of models, policies, rules or standards that govern what data is collected, and how it is stored, arranged, integrated, and put to use in data systems and within the organization. Data is usually one of several architecture domains that form the pillars of an enterprise architecture or solution architecture”. I would define Data Architecture as a discipline that deals with designing, constructing and integrating an organization’s data asset so it can be well optimized for the organization to run its business.

Enterprise Architecture is often compared with the architecture of a house, which defines individual design elements of nook and corners of the house to build it to specifications. Similarly, the data architecture is a design that defines the way data enters the organization, lives in its systems and applications, moves within the organization and is consumed to run the business. It is a blueprint of the data design. Most enterprises deal with unmanageable data sprawl that continues to grow at tremendous speed. This “just a bunch of data”, or JBOD, is a major driving force behind the need for a data strategy and an enterprise data architecture. It is much like a road network to reach to IT goal and thus business goal while data strategy defines “how” to reach that goal. In principle, the data architecture defines a framework that helps in organizing data ingestion, data storage & management, and data processing. Different components of this architecture would include data integration, DBMS selection, Data modeling, performance and measurement, security and privacy, Business intelligence, metadata, Data quality, and data governance.

The analogy of house design (see attached table) works well in this context to understand what components need to be taken care of when we talk about data architecture.

So why do we need a road network to reach our goals? Well…because we all value order than chaos. We like to follow etiquettes versus no rules of conduct. Okay… but what help will this “order” provide us and how? This question is simple to answer but rather difficult to execute. The enterprise data architecture helps us onboard the data quickly and delivers clean and trustworthy data at the speed required by patrons and business. It also ensures that data is handled in a more secure and compliant way, which may be required by local laws and regulations. It makes it easier to incorporate new data types and technology and enables end-user self-service. The list goes on, but the cardinal point is that data architecture ties it all together.

However, it is unwieldy to build an enterprise data architecture from scratch that can meet our need. A more pragmatic approach would be to build the future state of architecture in each new strategic business initiative. More in next issue…