Positioning Architecture T-Shirt-Sizes

In my previous post, I’ve introduced the idea of architecture t-shirt sizes to depict the idea that you BI architecture should growth with your requirements. In this blog post I position the four example t-shirt sizes on Damhof’s Data Management Quadrants.

T-Shirt Sizes in the Context of Data Management Quadrants

If you haven’t read my previous blog post, you should do so first.

In [Dam], Ronald Damhof describes a simple model for the positioning of data management projects in an organization. Here, he identifies two dimensions and four quadrants (see also Figure 1). On the x-axis, Damhof uses the terms push-pull strategy, known from business economics. This expresses how strongly the production process is controlled and individualized by demand. On the right or pull side, topic-specific data marts and from them information products such as reports and dashboards, for example, are developed in response to purely technical requirements. Agility and specialist knowledge are the key to this. The first two T-shirt sizes, S and M, can be categorized as belonging on this side. On the left or push side, the BI department connects various source systems and prepares the data in a data warehouse. The focus here is on economies of scale and deploying a stable basic infrastructure for BI in the company. Here we can see the other two T-shirt sizes, L and XL.

Figure2
Figure 2: Damhof’s Data Quadrant Model

On the y-axis, Damhof shows how an information system or product is produced. In the lower half, development is opportunistic. Developers and users are often identical here. For example, a current problem with data in Excel or with other tools is evaluated directly by the business user. This corresponds to the S-size T-shirt. As can be seen in my own case, the flexibility gained for research, innovation, and prototyping, for example, is at the expense of the uniformity and maintainability of results. If a specialist user leaves the company, knowledge about the analysis and the business rules applied is often lost.

In contrast, development in the upper half is systematic: developers and end users are typically different people. The data acquisition processes are largely automated and so do not depend on the presence of a specific person in daily operations. The data is highly reliable due to systematic quality assurance, and key figures are uniformly defined. The L- and XL-size T-shirts can be placed here in most cases.

The remaining T-shirt, the M-size, is somewhere “on the way” between quadrants IV and II. This means it is certainly also possible for a business user without IT support to implement a data mart. If the solution’s development and operation is also systematized, this approach can also be found in the second quadrant. This also shows that the architecture sizes are not only growing in terms of the number of levels used.

The positioning of the various T-shirt sizes in the quadrant model (see Figure 2) indicates two further movements.

  • The movement from bottom to top: We increase systematization by making the solution independent of the original professional user. In my own dashboard, for example, this was expressed by the fact that at some point data was no longer access using my personal SAP user name but using a technical account. Another aspect of systematization is the use of data modeling.
  • While my initial dashboard simply imported a wide table, in the tabular model the data was already dimensionally modelled.
  • The movement from right to left: While the first two T-shirt sizes are clearly dominated by technical requirements and the corresponding domain knowledge, further left increasing technical skills are required, for example to manage different data formats and types and to automate processes.
Figure3
Figure 2: T-Shirt Sizes in the Data Quadrant Model
Summary and Outlook

Let’s get this straight: BI solutions have to grow with their requirements. The architectural solutions shown in T-shirt sizes illustrate how this growth path can look in concrete terms. The DWH solution is built, so to speak, from top to bottom – we start with the pure information product and then build step by step up to the complete data warehouse architecture. The various architectural approaches can also be positioned in Ronald Damhof’s quadrant model: A new BI solution is often created in the fourth quadrant, where business users work exploratively with data and create the first versions of information products. If these prove successful, it is of particular importance to systematize and standardize their approach. At first, a data mart serves as a guarantor for a language used by various information products. Data decoupling from the source systems also allows further scaling of the development work. Finally, a data warehouse can be added to the previous levels to permanently merge data from different sources and, if required, make them permanently and historically available.

Organizations should aim to institutionalize the growth process of a BI solution. Business users can’t wait for every new data source to be integrated across multiple layers before it’s made available for reporting. On the other hand, individual solutions must be continuously systematized, gradually placed on a stable data foundation, and operated properly. The architecture approaches shown in T-shirt sizes provide some hints as to what this institutionalization could look like.

This article was first published in TDWI’s BI-SPEKTRUM 3/2019

Summer News 2019

It’s been quiet here. No new blog post since end of 2017. Let me share with you what happend so far and what’s coming next.

One of the reasons I had no time for blogging were my various customer projects. Whereas SAP BusinessObjects was my world till 2017, in 2018 I definitely moved into the Microsoft BI world more and more. I had the pleasure to work with much of the cool stuff around Power BI, SSAS Tabular, SSRS and various Azure services. Besides that I further pushed WhereScape data warehouse automation in our customer projects.

2018 was an intensive year in my company IT-Logix too. I had to jump in as an ad interim COO last summer and run operations for eight months – besides my role as the Chief Knowledge Officer and my regular project work. In April 2019 I finally could handover all my management activites and stepped back from the executive committee after more than ten years. On the other hand I was elected into the board of directors. This new role goes along much better with my continued interest in exciting projects, developing new fields of businesses and sharing knowledge with the community.

Community is key – my concern in 2019 is to invest in the next generation of BI and analytics folks. Therefore I’m investing myself into building up the Swiss branch of TDWI Young Guns. The Young Guns community serves as a networking platform between students, young professionals and more experienced people – all sharing a common interest in data and what you can do with it. After a successful first barcamp back in May there are some promising upcoming events you shoudn’t miss if you’re around Switzerland in September and October. Subscribe to the Young Guns mailing list or join us on LinkedIn to learn more about the details.

I also continued my conceptual work with an updated version of my requirments framework IBIREF including practical guidance of how to write and slice BI specific user stories. In addition, I worked on a new model around different (or better: growing) tshirt sizes for your BI architecture. The basic concept will be published in TDWI’s BI-SPEKTRUM by end of August – you’ll find a copy here too. So stay tuned.

19.07.01. Event MAKE BI ITX (390)
A glimpse at my presentation about T-Shirt Sizes for your BI architecture

Covering the same topic, I had the pleasure to give a keynote together with Ronald Damhof during the MAKE BI confernence beginning of July. I’ll give a similar presentation during BOAK and TDWI Schweiz confernce this autumn, unfortunately without Ronald. In addition, I’ll share some of my (disciplined) agile project experience during DADay 2019, a virtual conference organised by the Disciplined Agile Consortium.

Finally I have many ideas for further blog posts. Bear with me that I’ll find some time to write them down.