Data architecture has been described as fostering the integration of business and IT or technical considerations. Due to the influence of the systems, processes and technology that a company uses, data architecture informs a variety of other business decisions. Your business’ data architecture plan cannot be stagnant; it must grow and change alongside your business. New regulations may require you to alter your current strategy, while business goals may encourage you to adopt an entirely new approach.
As such, it is important to understand what the term encompasses and the impact it has on your business. Overall, the process of understanding your company’s data architecture will help your company run more smoothly and efficiently while contributing to a more organized enterprise architecture.
Data Architecture Definition
The term data architecture refers to a few different considerations and there is variability in how different sources define the term. While it can be useful to have a variety of resources, it can be challenging if team members are left struggling to truly understand a concept, especially when each source seems to have their own interpretation of what the concept is. Here are three of the most popular definitions:
But what does it all mean? What is data architecture, really? Let’s break down the definition of data architecture and the implications for your business.
Guidelines or Infrastructure?
Overall, data architecture is concerned with how data is collected, stored and used. It is related to data management and data governance and is a subset of enterprise architecture.
There are a few important concepts that help us understand the term. The first concept uses the term to refer to both guidelines and infrastructure. For instance, data architecture could involve ideas such as rules, policies, and processes regarding company data. Businesses can outline requirements and limitations for what data can be collected, how the data is managed and how to execute actions related to the data. Additionally, data policies and standards may outline specifications for the handling of sensitive data and regulations to manage the collection, storage and use of the data that is collected.
However, the term can also refer to more specific technical infrastructure such as the systems, platforms and databases that a company utilizes. For example, data lake architecture and data warehouse architecture will be different due to the different ways they ingest, process, and store data. Data lakes can ingest data regardless of format or structure while data warehouses store structured data.
Data Models: An Integral Part of Data Architecture
Data models can be extremely useful when managing data architecture. The models may include the specific modes of data collection, processing and storage (i.e. the infrastructure itself). It could also include the existing data types, sources, structures and processes in addition to the layout of systems and paths of data flow.
In order to integrate new technology, services, or software, your business will need to evaluate the existing architecture and outline a working model of the available systems and resources. It will also be necessary to determine business requirements, specific needs, integration with current systems, existing data sources and future goals. Outlining these models can help to reveal inefficiencies in your current data plan and show areas that need to be optimized or re-evaluated.
Often, businesses can get excited about adopting new technology and software and rush into implementation before determining their specific needs or capabilities. For instance, businesses may not have the manpower in-house to effectively develop and implement the technology or software they require. The result could end up being an expensive, unintegrated, and unusable mess.
What are Data Architects?
A discussion of the definition would not be complete without those who work most closely with data architecture: the data architects. Data architects are focused on whether the data architecture of the company meets the needs of the business. Below are some of the potential job requirements and roles of a data architect:
- Design data architecture and build computer database systems;
- Determine appropriate technology, software and tools that are required by the business as they pertain to the existing architecture;
- Optimize and manage current data architecture;
- Help determine data policies, procedures and guidelines, including data standardization;
- Help fulfill both business and IT requirements of the company; and
- Data management, ingestion, curation, analytics, visualization, and modeling.
Some data architects focus on the more theoretical or conceptual side to data architecture, while others are equipped with development and technical knowledge. It is important that data architects work closely with those in both business-oriented and technical roles so that they understand the needs of the company and those that work there.
Definition of Data Architecture: A Summary
To review, data architecture:
- encompasses the business framework of how data is managed, both conceptually and physically;
- is a subset of enterprise architecture;
- is essential to data governance and data management;
- is often managed by a data architect;
- can be outlined in a business model; and
- informs and directs future plans for services, platforms and technology adoption.
Don’t employ a full-time data architect? No problem! 7T offers software and technology consulting, data governance and system integration services to help you make the most of your data.
Additionally, our developers are experts in mobile app development and custom software development. We can help you craft a solution that meets the specific needs of your business.