Modern business problems require ever ­increasing amounts of data, and ever ­increasing variety in the data that they ingest. Aphorisms such as the “three V's” have evolved to describe some of the high-level challenges that “Big Data” solutions are intended to solve. An introductory article on the subject may conclude with a recommendation to consider a high-level technology stack such as Hadoop and its associated ecosystem.

While this sort of recommendation may be a good starting point, the business will inevitably find that there are complex data architecture challenges both with designing the new “Big Data” stack as well as with integrating it with existing transactional and warehousing technologies.

This paper will examine a number of architectural patterns that can help solve common challenges within this space. These patterns do not rely on specific technology choices, though examples are given where they may help clarify the pattern, and are intended to act as templates that can be applied to actual scenarios that a data architect may encounter.

Click to read our White Paper on Big Data Architecture Patterns.