translating relational queries into spreadsheet
R.Kiruthika,K.Deepika
Published in International Journal of Advanced Research in Computer Science Engineering and Information Technology
ISSN: 2321-3337 Impact Factor:1.521 Volume:4 Issue:3 Year: 01 April,2016 Pages:796-802
Abstract
Data mining the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. Spreadsheets are the desktop counterpart of databases and OLAP in enterprise scale computing. They serve basically the same purpose data management and analysis but at the opposite extreme of the data quality scale. We demonstrate that a spreadsheet can implement all data transformation definable in SQL merely by utilizing spreadsheets formulas. We provide a query compiler, which translates any given SQL query into a worksheet of the same semantics, including NULL values. Thereby database operations become available to the users who do not want to migrate to a database. They can define their queries using a high level language and then get their execution plans in a plain spreadsheets. Spreadsheets are among the most commonly used applications for data management and analysis. They combine data processing with very diverse supplementary features: statistics, visualization, reporting, linear programming solvers, Web queries periodically downloading data from external sources, etc. However, the spreadsheet paradigm of computation still lacks sufficient analysis.
Kewords
Relational databases, physical database design prototypes, spreadsheets, query languages.
Reference
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