Data Architecture is the way that your organization’s data is structured and persisted within the various systems you use to manage your data. The Data Architecture is very important as it determines the ability and efficiency of your systems to access and use the data. Data is used in different ways across your data eco-system, in some cases it is rapidly being created, read, updated and deleted and is structured in a manner that facilitates those rapid individual interactions. In other cases, your data is used for analytics and must be summarized and grouped in a specific manner, and the data must be structured differently for those processes. The correct Data Architecture at each stage of your BI Solution Architecture will ensure you have seamless and effective access and interaction with your data when you need it.
It is both fundamental and critical that your data be stored, persisted, and structured in a best practices manner in order to ensure data quality, logical congruency, user accessibility, security, and ultimately high quality, accurate and timely results which will take the form of dashboards, reports, and presentation in various user apps. The quality of the data presented is only as good as the quality of its management and integration, and for that your organization will need to have the proper architecture for each use case.
Data Architecture is the physical structure of your data and the manner in which it is persisted and stored in the various systems and methods within your organization. There are many different methods, systems, and architectures for storing data. You may have data in flat files like Excel, you may be using Access as a desktop data base
Using best practices procedures and tools your organization can hold requirements gathering sessions to understand your stake holders use cases, needs, requirements, assumptions and constraints. Your team can gather information on the types of systems and reports you will need, and from there you can determine the best tools, systems and architectures to manage your data and make it available in the format, locations, and protocols that are required by your end-users and stake holders. There are a lot of vendors for applications, and a lot of design options, so expect this to be a very interesting and involved conversation that is fundamental to getting your data management and enablement right for the long term. The results of this work will be technical models, diagrams, and requirements documentation that will allow your developers to build your data management solution to proper specifications. This involves the management of all business event recording and organization in a logical structure.