With data becoming one of the key strategic assets, companies need to do more than just collect and store information correctly – it is important to learn how to manage data systematically. The Center of Excellence for Classification and Data Modeling (CoE) is a structural unit that ensures consistency, quality and efficiency of all data handling in the organization.
The Center of Excellence (CoE) is the core of expert support and a methodological foundation for digital transformation in a company. It builds a data-driven culture and enables organizations to build processes that make decisions based on structured, validated and representative data rather than on intuition or local information.
A data center of excellence is usually formed from cross-functional teams that work according to the “two pizzas” principle. This principle, proposed by Jeff Bezos, means that the size of the team should be such that it can be fed with two pizzas, i.e. not to exceed 6-10 people. This approach helps to avoid excessive bureaucracy and increases the flexibility of work. The CoE team should include employees with a variety of technical skills, from data analytics and machine learning to expertise in specific business areas. With their deep technical knowledge, data engineers should not only optimize processes and model data, but also support colleagues by reducing time on routine tasks (Fig. 4.3-9).
Just as in nature ecosystem resilience is ensured by biodiversity, in the digital world flexibility and adaptability are achieved through a diversity of approaches to handling data. However, this diversity must be based on common rules and concepts.
A Center of Excellence (CoE) can be compared to the “climate conditions” of a forest ecosystem, which determine which types of data will thrive and which will be automatically discarded. By creating a favorable “climate” for quality data, the CoE facilitates the natural selection of best practices and methodologies that later become organizational standards.
To accelerate integration cycles and achieve better results, CoE should provide its members with a sufficient degree of autonomy in decision-making. This is especially important in a dynamic environment where trial and error, constant feedback and frequent releases can bring significant benefits. However, this autonomy is only effective if there is clear communication and support from senior management. Without strategic vision and top-level coordination, even the most competent team can face barriers in implementing their initiatives.
It is the COE or senior management’s responsibility to ensure that the data modeling approach is not limited to one or two projects, but is embedded in the overall information management and business process management system.
The Center of Expertise (CoE), in addition to tasks related to data modeling and Data Governance, is responsible for the development of common standards and approaches to the deployment and operation of the data infrastructure. It also creates a culture of continuous improvement, process optimization and efficient use of data in the organization (Fig. 4.3-10).
The systematic approach to data and model management within CoE can be roughly divided into several key blocks:
Process standardization and model lifecycle management: CoE develops and implements methodologies to unify the creation and management of data models. This includes: establishing structural templates, quality control methods and version control systems to ensure data continuity across all phases of work.
Role management and responsibility assignment: The COE defines key roles in the data modeling process. Each project participant is assigned clearly defined roles and areas of responsibility, which promotes teamwork and reduces the risk of data inconsistencies.
Quality control and auditing: effective management of construction data requires continuous monitoring of its quality. Automated mechanisms are being introduced to check data, identify errors, missing attributes.
Metadata and Information Architecture Management: CoE is responsible for creating a unified system of classification and identifiers, naming and entity description standards, which is critical for integration between systems.
The Center of Excellence (CoE) for Data is not just a group of experts, but a systemic mechanism that creates a new data-driven culture and provides a unified approach to working with data throughout the company. Through competent integration of modeling processes into the overall information management system, standardization, classification and data quality control, CoE helps businesses to continuously improve their products and business processes, respond faster to market changes and make informed decisions based on reliable analytics.
Such centers are particularly effective when combined with modern DataOps principles – under a move that ensures continuous delivery, automation and quality control of data. We will talk more about DataOps in Part 8, in the chapter “Modern Data Technologies in the Construction Industry”.
In the following chapters, we will move from strategy to practice – let’s conditionally “transform” into a data center: we will look at several examples of how task parameterization, requirements gathering and the automatic validation process take place.
