“Key Components of a Data Architecture”
Do you ever wonder how companies manage all their data and technology systems? It is true that the bigger the company, the more complex it is the work in managing technology. Large companies use more
then a handful of systems, applications, standards and resources for its operations, and when a lot of moving parts and processes exist, it often results in complexity.
Data architecture is a collection of technologies and protocols that define how data is collected and how it is meant to flow throughout the organization. Similar to building architecture, data architecture starts with a blueprint developed by both technology and business professionals within an organization.
Technology professionals are the architects who act as stewards of the organization’s data architecture, and business professionals are the end-users. While a data architecture involves a lot of building blocks, which varies from one business to another, the major components include data sources, infrastructure, integration points, and production.
• Data sources and flows–Defining sources from which data can be extracted is a major component of data architecture. Knowing where data is coming from will allow companies to understand the data formats and outputs they will be working with. This is the starting point of the whole architecture framework.
• Infrastructure and data warehousing processes– This is the most tangible component of data architecture because it involves location, and historically, a piece of hardware as well—the storage units and processing environment. Both of these allow companies to store, extract, transform and load the data. As more data is collected, more storage capacity and processing power are required to hold all of it and process accordingly. Expandable storage and agile processes are important in order to serve the business as it scales up or down.
• Integration points and connectors – It is common for an organization to own or license several tools, applications, and systems. However, not all of them are produced by the same technology manufacturer, and they may not naturally work together. Fortunately, there are services available that focus on connecting and integrating various systems in order for them to work seamlessly and allow data to flow with minimal interruptions.
• Production – This is the end component of data architecture. All of the other components exist in order to push data toward production. Production is the state where data is readily available to the end-user by way of user interfaces and dashboards. All of the activity that happens in production then flows back to the entire architecture, all the way to storage.
Companies that are dependent on data to fuel its operations need a defined data architecture as part of their data strategy. It is the foundation that allows organizations to execute on its data strategy. A well-defined and flexible data architecture enables the organization to perform in a faster and easier way, which is a source of competitive advantage today.[horizontal-scrolling group=”GROUP23″]