Supportsoft Glossary

Structured Data Management for Enterprise Applications

Structured data can be defined as the format information takes when it is organised in a predetermined way, allowing for quick storage, retrieval, and analysis of the information. Structured data is commonly found as rows and columns in various systems or programmes (database systems or spreadsheets) and follows a defined schema or structure when storing the data.

Structured data has been the primary source for enterprise systems that support the backend of business operations like ERP, CRM, finance and inventory management, as structured data is already organised into a specific structure, enabling businesses to quickly create reports, conduct analytics, and integrate systems efficiently.

The use of structured data management practices by IT and ITES service providers provides assurance that organisations' data remains accurate, consistent, and accessible. This encompasses practices such as database design, data normalisation, data validation and governance; through utilising the correct structured data management methodologies, organisations can decrease their error rates, optimise operational efficiency, and maintain compliance requirements.

Analytics and AI projects are dependent on structured data as the basis for developing models and generating reports, so having accurate and clean (maintained) structured data can significantly enhance training the model and synthesising the information to provide accurate reports for users to base their decisions upon. Additionally, structured data provides a clean basis for integrating it with other unstructured data sources and allows organisations to derive actionable insights from their analysis of both data types.

Through excellent structured data management practices, organisations can increase their systems' reliability, optimise operational efficiencies, and create scalable enterprise solution architectures.