In the New Year, instead of diving right back into the development/coding of data solutions I thought I’d take a step back from technology.  Why?  To again focus on a set of principles designed to aid the process of developing and managing data: Data Management.  With the current advances of Data/Big Data & Business Intelligence technologies and the sharp focus on delivering “breakthrough insights” to information-hungry organisations, it has become even more important to harness the power of effective Data Management.

Without a Data Management policy the following issues can affect an organisations ability to remain competitive:

  • Systems designed and deployed in isolation have great difficulty in being integrated
  • Information cannot be shared easily between systems if the semantics of these systems are different
  • Without data sharing and accessibility, people within the organisation may not have the information they need to carry out their role effectively
  • The same data is created and saved repeatedly causing data duplication and confusion

At the beginning of 2012 I had the opportunity to study under the tutelage of DAMA UK’s Keith Gordon in Data Management.  The BCS book Principles of Data Management that accompanied the course is freely available for purchase and I fully recommend it.  The principles outlined within the book are very much geared to tackling practical real-world issues, having been developed and tested after many years on the front-line.


I’ve cherry picked a few core areas that the book covers, please be aware that certain areas are enormous subjects in their own right and can’t be completely covered in a single chapter.

Data & The Enterprise

Shows us that Data is a key asset and a resource to be shared and collaborated with across the organisation.  For information to be accurately and timely delivered, data must be properly managed.

Database Development, Data Modelling & Corporate Data Modelling

Before diving right in and creating data structures and filling with vast amounts of data, we must first model the data and ask questions about the validity of that model.  Do attributes share common themes?  Can these common themes be re-used in data models across the organisation?

Data Definition & Naming Conventions

When creating data structures, it’s important to define common and shared definitions, this eases data integration.  This is especially difficult when buying off-the-shelf software but may help to identify integration problems before they occur.

Data Quality

If an organisation wants to derive insights and useful, actionable information from data then the quality of that data is paramount.  Missing or incorrect values will all skew the value of that piece of data.

Resources needed for Data Management

What skills and technology are needed to install a data management function within an organisation?  Do you need database developers, database administrators, data stewards?

What is clear from this book is that the principles outlined do highlight a fundamental fact that to “win at data” it’s very much a community effort from all members of an organisation.  From Directors, IT Managers, Developers to Systems Users all play a role in delivering an effective Data Management initiative.