The data architecture has three levels (processes):
Conceptual level (business model): includes the entire list of data objects and describes their conceptual or semantic model.
Logical level (system model): defines the interrelationship of data objects and their logical model.
Physical level (technological model): defines the mechanisms for working with data in specific processes and operations (describes the method for implementing the actual data architecture in the underlying technological infrastructure).
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Elements of data architecture
Data architecture includes models, strategies, rules and standards.
The conceptual model reveals how data is interconnected with each other and with other areas (for example, business processes and technical resources, including personnel and server systems).
This database architecture model is sometimes called lambda architecture. It is especially effective for storing and online processing of large amounts of information coming in real time, for example from streaming services.
Strategy is the main task solved by creating a data architecture. For example, improving customer service or optimizing recommendation systems.
The data storage architecture is formed taking into account the specifics of the area in which the company operates. Different models are used for different areas. For example, the architecture for a game developer will differ from that required by an online store or marketplace.
An important stage of development is interaction with the customer, since each business has its own unique requirements and goals.
Rules and standards are a set of principles for interaction with lambda architecture, which can also be called data policy. They can vary depending on the type of information base chosen for storage (simple, relational, NoSQL, or mixed type).
Elements of data architecture
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Architecture design cannot be done using a ready-made template or by copying from competitors. Understanding the unique requirements of the customer is critical to its creation.
An engineer may receive an order to develop a database architecture for storing medical examination data or for archiving reports. The solution to each task has its own characteristics. During the Data Engineering course, students are trained in designing data architectures of various types based on specific business tasks. Students, in a team with experienced engineers, implement projects for different areas of application.