A good example of a pattern in science comes from the father of genetics, Gregor Mendel. ... By Towards Data Science… The big data design pattern … The book is ideal for data management professionals, data modeling and design professionals, and data warehouse and database repository designers. Architectural patterns are similar to software design pattern but have a broader scope. We purposely use “pattern language” to reflect that the field of Deep Learning is a nascent, but rapidly evolving, field that is not as mature as other topics in computer science. Workload patterns help to address data workload challenges associated with different domains and business cases efficiently. A pattern is a when data repeats in a predictable way. Bad design choices are explicitly affecting the solution’s scalability and performance. In this article, I will be briefly explaining the following 10 common architectural patterns with their usage, pros and cons. The majority of literature in the computer science field, the phrase “design patterns” is used rather than “pattern language”. Big data workload patterns. Show less Data Model Patterns: A Metadata Map not only presents a conceptual model of a metadata repository but also demonstrates a true enterprise data … As such today I will introduce you to a few practical MongoDB design patterns that any full stack developer should aim to understand, when using the MERN/MEAN collection of technologies: Polymorphic Schema; Aggregate Data …