Sometimes, it is a great idea to push away the keyboard when tackling the problems of an ill-performing, complex, query, and take up pencil and paper instead. By drawing a diagram to show off all the tables involved, the joins, the volume of data involved, and the indexes, you'll see more easily the relative efficiency of the possible paths that your query could take through the tables.

In this article, the authors analyze enterprise’s data architecture and obtain intelligent insights to find the best performing solution for a given set of requirements.

Fixed structured data keeps businesses running day in and day out. But supporting only fixed data is also extremely limiting to structured data processing. There is no reason that highly principled structured data processing has to be limited to static data structures. Dynamic data structures enable a new set of powerful, unlimited data processing opportunities. As an example, it would be very useful to have a highly flexible and principled hierarchical data processor to support dynamic structured data processing automatically. This article presents an example of such a dynamic structured data processing application and how it operates.

This article explains how to achieve easy database refactorings in the Java code, and how to have fun when programming towards a database (in a safe and very easy manner). While the techniques can be used in ORMs in general such as Toplink, Hibernate, the outset of the article is using raw SQL or low level ORMs such as SqlORM.

This article summarizes experience of applying Incrementally agile discipline to database development, reducing up-front design work to just-in-time work that matched to 2 week development iterations.

For application developers focusing on the needs of their code, rather than worrying about the complexities of data representation, the Entity Framework’s abstractions are essential. But eventually a database needs to be created, and this article shows how it’s done.

Over the last few years we've developed a number of techniques that allow a database design to evolve as an application develops. This is a very important capability for agile methodologies. The techniques rely on applying continuous integration and automated refactoring to database development, together with a close collaboration between DBAs and application developers. The techniques work in both pre-production and released systems.

This paper describes how data professionals can take an evolutionary approach to software development, showing how techniques such as Agile Modeling, Test-Driven Development (TDD), database refactoring, and performance tuning work together on an agile project.

This article discusses the challenges of both moving to Public Petroleum Data Model (PPDM) for the first time and transitioning between different versions of the PPDM model.

A fascinating discussion of five common database design errors which persist in spite of the fact that the unfortunate consequences of their use is so widely known. It is a needy reminder to anyone who has to design databases.