What the Data Management Professional Needs to Know About the Latest Trends and Technologies

As much as we read books on embracing change such as “Who Moved My Cheese?”, “Who Ate My Cheese?”, and “Who Sat On My Cheese?”, how many of us really like change? (And how many of us really like cheese?) If we are lucky enough to be in the data management world, relatively little has changed in the last decade compared to related disciplines such as software development. In fact, I have been teaching data modeling for two decades and several topics in my classes (such as normalization) are just as relevant today as they were 20 years ago. But an adventure is brewing.

Similar to ascending the first drop of a large roller coaster, I can feel us (us being the data analyst, architect, and modeler) about to embark on an exciting and new adventure. The change has already started happening in many organizations, and I believe will continue to spread steadily through all industries. What’s causing this change? I’m glad you asked – there are trends and technologies that have been around for a while but have started becoming mainstream. Cloud computing, mashups, unstructured data, columnar databases, XML, agile, and others will impact the data management professional, and therefore will be the subject of these blogs. Let’s use this monthly blog to explore how these technologies and trends will impact us.

I’ll be doing a one day tutorial at the Enterprise Data World conference in San Francisco in March on these trends, I am expanding my four day Data Modeling Master Class to encompass these trends, and I have been also raising quite a few of these trends in my monthly Design Challenges (sign up here: www.stevehoberman.com/challenges.htm). Each subsequent blog posting will dive into the details of the impact of specific technologies. I welcome your comments on these.

What’s interesting about these trends and technologies is that they don’t just impact technically how we do our jobs, but they often also impact the softer side of our jobs. By the softer side, I include skills such as communication and influencing skills.

For example, consider the mashups. My definition for a mashup is the following:

The term “mashup” started in the music world but has rapidly been adopted in IT to mean a web-based application which uses two or more standalone applications to provide a new service. Frequently one of the standalone applications is mapping software such as GoogleMap. Application programming interfaces (APIs) from the standalone applications make it easy and cost-effective to create the mashup. Applying mashups in a business setting is often referred to as “enterprise mashups”.

We’ve probably all used mashups (probably without even knowing it). Go to redbox.com for example and not only can you reserve a video, but you can look at a map to find the Redbox closest to your house. When you discover that “Gone with the Wind” exists in a Redbox just 3 blocks from your house, you are the user of a mashup. You are using Redbox’s own software mashed up with GoogleMap.

Mashups are becoming more popular within organizations. Now imagine you are working on a new datamart in your company to view sales by region, which also provides links to GoogleMap so users can see maps, visualize distances, and leverage other features within GoogleMap. How does such an application impact the data architect, data analyst, and data modeler? I welcome your thoughts here and read my thoughts in my next blog posting!