Data Architecture
Introduction
Data architecture refers to the models, policies, rules, and standards that govern which data is collected, and how it is stored, arranged, integrated, and put to use in data systems and in organizations. It provides a formal approach to creating and managing the flow of data and how it is processed across an organization's systems and applications.
History
The concept of data architecture is as old as data processing itself, with the first data architectures being designed and implemented in the 1960s and 1970s as part of large scale mainframe projects. As the complexity and volume of data increased, the need for a formal data architecture became more apparent.
Components of Data Architecture
Data architecture includes the primary data entities, data processes and data flows of an organization. It is comprised of three main components:
1. Data models: These are an abstraction which organizes elements of data, and standardizes how they relate to one another and to the properties of real-world entities. For example, a data model may specify that the data element representing a car be composed of a number of other elements which, in turn, represent the color and size of the car and define its owner.
2. Data Integration: This is the process of combining data residing in different sources and providing users with a unified view of these data. This process becomes significant in a variety of situations, which include both commercial (when two similar companies need to merge their databases) and scientific (combining research results from different bioinformatics repositories, for example) domains.
3. Data Governance: This refers to the overall management of the availability, usability, integrity, and security of the data employed in an enterprise. A sound data governance program includes a governing body or council, a defined set of procedures, and a plan to execute those procedures.
Importance of Data Architecture
Data architecture is important for the success of any enterprise as it provides a clear and comprehensive view of the data resources of the organization. It ensures that the data is accurate, reliable and accessible, and it helps to protect the data from security threats. It also helps to ensure that the data is used in a way that aligns with the organization's business goals and objectives.
Data Architecture and Business Intelligence
Data architecture plays a crucial role in business intelligence (BI). BI involves the delivery and integration of relevant and useful business information in an organization. Companies use BI to detect significant events and identify/monitor business trends in order to adapt quickly to their changing environment and a scenario. If the organization has a good data architecture, it will be easier to manage and analyze the data, which will lead to more accurate and timely decision making.
Data Architecture and Big Data
With the advent of big data, the importance of data architecture has increased manifold. Big data refers to the large, diverse sets of information that grow at ever-increasing rates. It encompasses the volume of information, the velocity or speed at which it is created and collected, and the variety or scope of the data points being covered. Data architecture helps in managing and controlling the big data and makes it easy for the organizations to access and interpret the data.
Data Architecture and Data Warehousing
A data warehouse is a large store of data collected from a wide range of sources within a company and used to guide management decisions. It separates analysis workload from transaction workload and enables an organization to consolidate data from several sources. Data architecture plays a vital role in the design and implementation of data warehouses.
Conclusion
In conclusion, data architecture is a critical component of any enterprise as it provides a roadmap for the management of data. It ensures that the data is accurate, reliable, and accessible, and it helps to protect the data from security threats. With the advent of big data, the importance of data architecture has increased manifold.