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DataSpread unifies spreadsheets and databases, offering Excel

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Area of Science:

  • Data Management and Visualization
  • Human-Computer Interaction

Background:

  • Spreadsheet software excels at ad-hoc data tasks for small datasets.
  • Relational databases offer power and efficiency but lack spreadsheet usability.
  • A gap exists in tools that combine spreadsheet ease-of-use with database capabilities.

Purpose of the Study:

  • To introduce DataSpread, a novel tool unifying spreadsheet and database functionalities.
  • To demonstrate how DataSpread enhances data exploration by merging familiar interfaces with robust backend management.
  • To showcase the capabilities of an early prototype for reconciling differences between spreadsheet and database paradigms.

Main Methods:

  • Developed DataSpread with a Microsoft Excel front-end and a PostgreSQL back-end.
  • Implemented features to manage data in parallel across both interfaces.
  • Addressed challenges in reconciling schema, cell/tuple addressing, and pane concepts between spreadsheets and databases.

Main Results:

  • DataSpread retains spreadsheet advantages like ease of use and schema-free operation.
  • It incorporates database benefits such as scalability and arbitrary SQL querying.
  • Supports data modifications seamlessly from both front-end and back-end.

Conclusions:

  • Unifying spreadsheets and databases in DataSpread significantly enhances data exploration capabilities.
  • The tool bridges the usability gap between simple spreadsheet tools and powerful relational databases.
  • DataSpread offers a scalable and flexible solution for diverse data management needs.