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 data platforms are required 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 all of the original problems — a result of confusing technology with architecture.
Architecture is more than just software. It starts from use and includes data, methods of building and maintenance, 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 have 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
- BI and analytics leaders and managers; data architects, modelers, and designers; big data architects, designers, and implementers; anyone with data management responsibilities challenged by recent and upcoming changes in the data landscape