Data structure underlies all parts of a data management strategy. Data quality, data governance, data security and other initiatives cannot be effective without understanding and optimizing the layout, models and organization of the underlying data. In order to create an effective enterprise data structure, data modelers and data architects work with business users to understand the business requirements and data usage. Organizations gain the most advantage from a data modeling practice when the data models are created using common standards and processes, consistent with the enterprise's view of the data. There should also be a broad education and communication process around the data. Users need to understand the definition of data, its suggested uses and how it fits their business requirements. Business requirements are reflected in structured data models. These models are developed at both the enterprise and business unit levels. Data modeling enables an enterprise to communicate its data entities, attributes and relationships, as well as support system development and maintenance projects. The classification of data within an enterprise is known as data taxonomy. It applies to both structured and unstructured data. For example, data taxonomy could be a product catalog, including components and part numbers (structured data), and it could be the classification or grouping of documents (unstructured data). Through our many years working in the data management and architecture landscape, Accenture has gained insight into how a company's data structure must underlie and support the business processes. Our consultants bring an understanding of real-world business processes that accommodate change and growth. Our business perspective and modeling expertise enables organizations to better manage their business, interact with customers and make strategic, financial and operational decisions. Return to Data Management & Architecture Home. |