Agile Database Techniques

Effective Strategies for the Agile Software Developer

John Wiley & Sons    ISBN#: 0-471-20283-5

Scott W. Ambler + Associates
 
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Overview

Part 1 describes the fundamental skills and knowledge that everyone on an agile project team should have.  This includes the basics of object orientation, relational databases, the object-relational impedance mismatch, data modeling, and how to deal with legacy data issues. Without this common base of knowledge it is very difficult for application developers and data professionals to work together effectively.  A significant problem in the IT industry is that most data books do not cover object-oriented development issues and most object books seem to ignore data issues. This needs to stop.

Part 2 focuses on how to take an evolutionary approach to data.  This section sets the foundation for a model-driven development (MDD) approach, or more accurately an agile model-driven development (AMDD) approach where your application code and database schemas are based on agile models.  This isn't the only way to work, you may decide to take a test-driven development (TDD) approach instead or better yet combine it with AMDD.  Both methods support evolutionary development but because MDD is very common within the data community and I suspect that they will gravitate more towards an AMDD approach rather than a TDD approach.  However, some agile developers, particularly extreme programmers, prefer TDD over AMDD.  Luckily the two approaches work very well together so it really doesn’t matter.  The implication is that TDD will become more important to data professionals in the coming years.  This section also describes database refactoring, an evolutionary technique that enables you to improve your database design in small steps.  In many ways database refactoring is normalization after the fact.  Chapters describing mapping objects to relational databases, performance tuning, database encapsulation, and supporting tools are included in this part because they enable evolutionary development

Part 3 focuses on implementation techniques and strategies such as concurrency control, security access control, finding objects in relational databases, referential integrity, and the effective use of XML.  An important observation is that many of these topics are traditionally thought of as data issues, but as you'll see there is far more to them than this – it isn't a black and white world. 

Part 4 describes strategies for adopting agile database techniques.  These chapter provides advice for individuals who want to become agile software developers and for organizations that want to adopt agile techniques.

 

Chapter List

 

Part 1: Foundational Skills and Knowledge

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Part 2: Evolutionary Database Development

 

Part 3: Data-Oriented Development Techniques

 

Part 4: Adopting Agile Database Techniques

 

 

Why I Wrote This Book

Since the early 1990s I've been working with both object and relational database (RDB) technologies to build business applications, and since the mid-1990s I've done a fair bit of writing on the subject.  These writings have appeared in Software Development, in several of my books (in particular Building Object Applications That Work and The Object Primer), and on my personal web site. The two white papers at my site, one on mapping objects to RDBs and the other describing the design of a persistence layer, have proven to be incredibly popular with several hundred thousand downloads over the years.  The persistence layer paper has even been used as the basis for several open source products.  Although it's been very rewarding for me to share my ideas through these writings I never took the time to collect this work in one place nor have I written everything that I have to say about the topic.  This book rectifies this situation. 

As a consultant I've worked with object and data professionals, their related technologies, and of course their techniques.  In doing so I've worked in traditional environments that take a near-serial approach to development as well as more modern environments that take an agile and evolutionary approach to development. Over time I've worked on many different project teams in various roles. Data oriented issues where important, and sometimes even critical to success, on each project.  Although traditional project teams seemed to have a handle on how to deal with data issues the more agile ones often struggled – in part because the data professionals in those organizations preferred to take a serial approach and in part because the object developers didn't appreciate the importance of data-oriented issues.  Being an ex-data specialist (oh no, my horrible secret is out!) and being experienced in object technology I often found ways for the two groups to work together.  My experience was that data professionals were often overly focused on data to the exclusion of the wide variety of challenges faced by object developers and similarly object developers had little or no data-related experience.  So I would help the two groups find ways to work together, to mentor them in each other's techniques, and to help them overcome what is known as the object-relational impedance mismatch.  For these two groups to work together effectively they need to understand and appreciate what the other group is focused on, and I would even call into question the wisdom of having separate groups to begin with. This book describes the skills that both data professionals and object professionals require in order to build modern-day software. 

As a methodologist I have actively tried to find ways to develop software effectively, and over the years have run the gambit from prescriptive approaches such as my work with process patterns and the Enterprise Unified ProcessTM (EUP) to agile approaches such as Agile Modeling (AM) and now agile database techniques.  In part this book is an extension of AM to help describe how data professionals can take an evolutionary (iterative and incremental) approach to development.  Although many people within the data community are adamantly opposed to evolutionary approaches, interestingly enough I've often found that those opposed to it have never actually tried it, the reality is that agile software development is real and it's here to stay.  For data professionals to remain relevant they must be prepared to work in an agile manner, otherwise project teams will very likely find ways to work around them (I suspect you see this sort of thing happen within your organization all of the time).  My experience, on actual projects, is that you can in fact be very successful taking an agile approach to data-oriented activities if you choose to do so.  Many people will tell you that it won't work, but all they're really saying is that they either can't make it work or they don't want to.  This book describes numerous, proven techniques that support evolutionary data-oriented development.

When I first started writing this book I intended its focus to be on the Agile Data (AD) method.  This method describes how data professionals and application developers can work together effectively on agile projects.  It also describes how enterprise professionals, such as enterprise architects and data administrators, can support agile development teams effectively.  Because I was taking an iterative and incremental approach to the development of the book I quickly realized that the real value lay in detailed development techniques instead of yet another methodology.  So I refocused.



Who Should Read This Book?

You!  Anyone who is interested in improving their productivity as a developer, or who wishes to bring effective database development practices into their team or organization.



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Agile Database Techniques

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We actively work with clients around the world to improve their information technology (IT) practices, typically in the role of mentor/coach, team lead, or trainer.  A full description of what we do, and how to contact us, can be found at Scott W. Ambler + Associates

 


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