Data-representation-focused

Describing a method, system, or approach that prioritizes the structure, format, and organization of information for optimal analysis, communication, and utilization. This involves selecting and implementing techniques to encode data efficiently, clearly, and in a way that aligns with the intended purpose, whether it's machine learning, visualization, storage, or human understanding. It emphasizes the relationship between the data itself and the form it takes.

Data-representation-focused meaning with examples

• The project team adopted a data-representation-focused strategy when designing the database schema. They carefully considered data types, relationships, and indexing to maximize query performance and reduce storage space. This involved optimizing the use of different data structures for specific data sets to enhance processing speed and minimize redundancy.
• Effective scientific visualizations are inherently data-representation-focused. Researchers employ color maps, graphs, and other visual elements to transform complex numerical findings into understandable forms. They ensure each representation accurately conveys trends and key findings, which is crucial for communication and deeper insights into the phenomena.
• In machine learning, choosing appropriate data-representation-focused techniques (e.g., feature engineering) can significantly improve the performance of models. Transforming raw data into a suitable format, considering specific algorithms requirements, improves the training efficiency of the model, thus improving the prediction accuracy.
• When converting financial data into a standardized format (e.g., JSON or XML), the process becomes data-representation-focused. Ensuring consistency in data types, including precise naming of fields, will facilitate sharing and integrating data across multiple systems. It also makes data easier to process by automating business reports.