Data-driven organizations are modernizing and transforming their operating model to exploit new and existing digital capabilities. The transformation imperative is responding to the demand for more: more product-centric teams, more DevOps delivery, more releases, more cloud services, more self-service, and of course, more data sources.
With so much changing, how do we pull it all together into a seamless digital operating model? In this episode of Data Mesh TV — Rob Akershoek, a thought leader in the IT4IT Digital Operations space joins us to explore what a digital operating model looks like and where Data Mesh capabilities fit.
An evolving Digital Operating Model
Let’s start by framing a vision for digital operations. You should recognize the following digital trends as they are prevalent across all industries:
- Domain-Driven Architectures
- Multi-Vendor Sourcing
- Cloud Services & Platforms
- Product-Centric Teams
- DevOps or DataOps Delivery
- Continuous Release Models
- Self-Service Support Models
- Business Enablement
We should be striving to integrate these organizational, architecture, and service delivery processes. If you execute in silos and in isolation, it won’t mesh, and you will fail to fully realize your digital strategy.
Abstracting architecture complexity to focus on value delivery
Abstracting architectural complexity to enable business teams to focus on accelerating value delivery is a common feature in many digital strategies. For data leaders, the business ask is clear, “Give me immediate access to the data I need to drive the digital business models.” The idea is for the business consumers to focus on the analytics, insight, and actions from data.
To achieve this vision, we need all of the elements of that digital operating model to work together. We need product-centric teams dedicated to their unique digital use cases. We need DevOps teams prioritizing and iterating through rapid technology enhancements. We need to enable self-service capabilities to empower business teams with greater control.
A Data Mesh strategy aligns well with a digital operating model
Placed side-by-side, Data Mesh fits very well with a digital organization. If your organization is on a digital transformation journey, your Data Mesh will further strengthen and accelerate your goals. Here are three examples:
Product-Centric Teams. The product organization aligns very well with the Domain and Data Product capabilities offered by the Data Mesh. Autonomous product teams will have faster access to the data that they need to accelerate their business product outcomes.
Cloud Services & Platforms. Data Mesh gives the architecture teams greater agility and optionality. You don’t need to migrate data, you don’t need to focus on a single provider, and you don’t need to centralize. Pick the best cloud services and platforms that meet your functional business needs, without making trade-offs for data accessibility.
Self-Service Models. One of the four Data Mesh principles is focused on Self-Service. In a mesh, the domain and product teams are encouraged and allowed to do more on their own. Teams work autonomously within a Domain to build their own Data Products, to refine them, and to share them.
When building your Data Mesh, consider standard operating frameworks such as: IT4IT Digital Operating framework, NIST for security, TOGAF for architecture, DevOps, or the Scrum Methodology.