In human history, the belief that the Earth was at the center of everything persisted until Nicolaus Copernicus introduced the heliocentric solar system model in 1543. It took centuries for the Catholic Church to accept this new perspective. Similarly, in today’s enterprise architecture, developers and architects view applications as the center of everything, but they are mistaken. Data should be at the core of enterprise architecture, and a data-centric approach can provide significant advantages for businesses.
Data-centric architecture involves structuring a system around data, making it the most important asset. Other elements of the system are designed and built around data to ensure efficient management, processing, and retrieval of data.
The app-centric approach in enterprise architecture emerged with the advent of relational databases in the 1970s, which tied data to specific applications. While this approach initially worked well, it has led to problems such as custom access controls, lengthy integration projects, and data replication. Every new solution or capability requires copying data and integrating systems, which has made enterprise architectures rigid and resistant to change.
However, the truth is that applications are merely tools to access and interact with data. Data holds the true value for businesses regardless of the application used. The dependency on specific applications arises from the solutions and integrations built on top of them, making it difficult to switch platforms. By adopting a data-centric approach, businesses can place data at the heart of their architecture, enabling better utilization and flexibility.
Data-centricity brings about several benefits and solves persistent problems in enterprise architecture. One major issue is data replication, which requires significant effort and resources. In an app-centric approach, new databases are created for each project, leading to data duplication and security risks. Data-centricity eliminates the need for data replication by providing a single source of truth and using links to share data across applications.
Another problem is data silos, where data is trapped within specific applications. App-centric designs perpetuate data silos as new databases are created for new software. Data-centric architecture separates data from applications and allows it to exist as a network, eliminating the need for bigger silos. Data collaboration platforms or data fabrics facilitate data sharing and reuse across applications, creating a permanent solution to data silos.
App-centric architectures also limit business agility as new projects require integration efforts and groundwork. Legacy architectures are often difficult to change, and any modification risks breaking the entire system. Low-code and “no-code” technologies may provide faster front-end delivery but do not address the underlying complexity. Data-centricity introduces plasticity, enabling real-time changes and adaptability. By eliminating data copies and integration efforts, new solutions can be built quickly, enhancing business agility.
In conclusion, embracing data-centricity in enterprise architecture unlocks operational efficiencies and solves persistent problems. By prioritizing data and placing it at the core of design, functionality, and decision-making processes, businesses can overcome issues such as data replication, data silos, and limited agility. Data-centric architecture allows for faster solution development, data sharing, and adaptability, leading to significant advantages for businesses in today’s dynamic and competitive landscape.
In human history, the belief that the Earth was at the center of everything persisted until Nicolaus Copernicus introduced the heliocentric solar system model in 1543. It took centuries for the Catholic Church to accept this new perspective. Similarly, in today’s enterprise architecture, developers and architects view applications as the center of everything, but they are mistaken. Data should be at the core of enterprise architecture, and a data-centric approach can provide significant advantages for businesses.
Data-centric architecture involves structuring a system around data, making it the most important asset. Other elements of the system are designed and built around data to ensure efficient management, processing, and retrieval of data.
The app-centric approach in enterprise architecture emerged with the advent of relational databases in the 1970s, which tied data to specific applications. While this approach initially worked well, it has led to problems such as custom access controls, lengthy integration projects, and data replication. Every new solution or capability requires copying data and integrating systems, which has made enterprise architectures rigid and resistant to change.
However, the truth is that applications are merely tools to access and interact with data. Data holds the true value for businesses regardless of the application used. The dependency on specific applications arises from the solutions and integrations built on top of them, making it difficult to switch platforms. By adopting a data-centric approach, businesses can place data at the heart of their architecture, enabling better utilization and flexibility.
Data-centricity brings about several benefits and solves persistent problems in enterprise architecture. One major issue is data replication, which requires significant effort and resources. In an app-centric approach, new databases are created for each project, leading to data duplication and security risks. Data-centricity eliminates the need for data replication by providing a single source of truth and using links to share data across applications.
Another problem is data silos, where data is trapped within specific applications. App-centric designs perpetuate data silos as new databases are created for new software. Data-centric architecture separates data from applications and allows it to exist as a network, eliminating the need for bigger silos. Data collaboration platforms or data fabrics facilitate data sharing and reuse across applications, creating a permanent solution to data silos.
App-centric architectures also limit business agility as new projects require integration efforts and groundwork. Legacy architectures are often difficult to change, and any modification risks breaking the entire system. Low-code and “no-code” technologies may provide faster front-end delivery but do not address the underlying complexity. Data-centricity introduces plasticity, enabling real-time changes and adaptability. By eliminating data copies and integration efforts, new solutions can be built quickly, enhancing business agility.
In conclusion, embracing data-centricity in enterprise architecture unlocks operational efficiencies and solves persistent problems. By prioritizing data and placing it at the core of design, functionality, and decision-making processes, businesses can overcome issues such as data replication, data silos, and limited agility. Data-centric architecture allows for faster solution development, data sharing, and adaptability, leading to significant advantages for businesses in today’s dynamic and competitive landscape.
