The problem designers need to solve isn’t big data or small data — it’s all data. The data warehouse is sufficient for a portion of the data we manage but not all of it.
Today’s requirements are to accept any data (not just rigidly structured) at any speed (not just what the database can handle). Data must be delivered via any means (not just SQL-based BI tools) and support any process (including algorithms and transformations).
Big data marketers position their solutions as alternatives to the data warehouse, but new technologies solve different challenges and aren't appropriate for some of the original problems — a confusion of technology with architecture.
Architecture is more than just software. It starts from use and includes the data, methods of building and maintaining, and organization of people. We are also in an emerging technology space when it comes to data. This requires reintroducing exploratory design practices that have been largely discarded over the last 10 years as data warehousing and BI matured.
You Will Learn
- Data architecture alternatives adaptable to today’s data realities
- New technologies that address problems inherent in the scope and scale of data today
- Methods and techniques to migrate from old data architectures to new ones that resolve today’s problems and prepare for the future