Tod means Fox

Supporting decisions through sound data management

Archive for August, 2011

Mindmapping Dimensional Models

Aug 22

Posted by Tod McKenna in Data Architecture

When presented with a data modeling problem, I start with a conceptual design and then create the logical and physical designs as each concept becomes more mature and stable. This is an iterative process that can take many hours. Using mind mapping software has always given me a head start.

Mind mapping has been around for a long time. It’s a visual technique that you can employ which allows you to diagram ideas based on some central theme. For dimensional modeling, the theme is some event in the business process, while the ideas are the dimensions and dimension hierarchies. Mind maps are quick to make, easy to follow and share, and will allow you to see all interconnected concepts in one place. Software developers and data modelers have been using mind maps for a long time, but its use (as far as I’ve seen) isn’t quite mainstream in the dimensional modeling space.

Orders 300x97 Mindmapping Dimensional Models

Mind mapping an Orders business process dimensional model

When I start to construct a new data model (ER/DM), my first attempt at a design is often a mind map. As I read through requirements and examine business processes and business entities, I start to draw out how they may relate. Traditionally I used a paper and pencil. But recently, I’ve switched to using mind mapping software that I can access and share on all my devices. MinDgo, for example, works on my Mac, iPhone, and iPad. Once I’ve sufficiently covered all key concepts and requirements, I complete the conceptual model in PowerDesigner.

I use mind mapping software for the following reasons:

  1. Quick, easy, and structured way of designing high-level business process dimensional models
  2. Available on all my devices (unlike the heavy case/modeling tools we use), so when inspiration strikes, or when that coffee-machine meeting concludes, I can quickly get the ideas into the design
  3. Very easy to show, explain, and help interpret the models to business and technology colleagues
  4. Organizing different iterations of a design, and interconnecting related designs, is easy using software (try this in your Moleskin)

I also use this technique when I am trying to understand existing data models. For example, if I’m analyzing complex database documentation (from vendors like WorldScope or Charles River), I can get a good feel for how things relate by mind mapping as I go.

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New Role as Data Architect

Aug 5

Posted by Tod McKenna in Personal

stereographic polytope 8cell 150x150 New Role as Data ArchitectI have recently taken the position of Data Architect.

As I wrote on LinkedIn: “As data architect, I am responsible for creating a strategic and international data architecture and vision. This includes implementing data architecture standards and guidelines across the value chain; serving as the lead data architect for all data warehouse, reporting, and analytic (BI/DSS) projects; and playing a lead role in establishing data ownership/stewardship within the organization. ”

This is quite loaded.

As I settle in, I’ll be looking to prioritize our most pressing needs while consuming all that I can about our existing data landscape. This is bigger than the data warehouse, data marts, and BI applications I’ve been involved with over the past year. This is also bigger than the integration project I undertook (with the same company) over the course of two+ years while working on the quantitative investment team. I need to get my head around all aspects of our data, from our CRM system through to our ODS, from our master data management capabilities to our transaction processing. In addition, these systems all talk to each other through a network of messaging, transferring, and batch processing. Our integration and service architecture is maturing quite quickly, and we are constantly improving our alignment across borders, which means more data, higher quality, faster delivery. In many ways, our environment is robust and mature; in other areas, we can do better.

I intend to continue writing about data warehouse topics. But I also expect to write more about my experiences in this new role. I hope you don’t mind!

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