Manage your business in a rapidly changing world with data analytics solutions. Keep an eye on your data, collect it from various sources and analyze it to reshape the strategy and strengthen the brand on the market.
What Is A
Data Architecture?
A data architecture describes how data is managed–from collection through to transformation, distribution, and consumption. It sets the blueprint for data and the way it flows through data storage systems. It is foundational to data processing operations and artificial intelligence (AI) applications.
The design of a data architecture should be driven by business requirements, which data architects and data engineers use to define the respective data model and underlying data structures, which support it. These designs typically facilitate a business need, such as a reporting or data science initiative.
Why Are
Data Architectures Important?
A well-designed data architecture is a crucial part of the data management process. It supports data integration and data quality improvement efforts, as well as data engineering and data preparation. It also enables effective Data Governance and the development of internal data standards. Those two things, in turn, help organizations ensure that their data is accurate and consistent.
A data architecture is also the foundation of a data strategy that supports business goals and priorities. In an article on key data strategy components, Donald Farmer, principal of consultancy Tree Hive Strategy, wrote that “a modern business strategy depends on data.” That makes data management and analytics too important to leave to individuals, Farmer said. To manage and use data well, an organization needs to create a comprehensive data strategy, underpinned by a strong data architecture.