Abstract
The paper deals with mathematical preparation and subsequent programming of various types of financial functions with using of Transact-SQL in Database Management System MS SQL Server. Financial functions are used to automate calculations in the area of Financial Economics. In MS SQL Server, any financial functions are not offered for financial data processing, how such as in program MS Excel. We emphasize that we have used a different calculation methods to create financial formulas, not those used in Excel. If users want to work with some special functions, there is a possibility to prepare User-Defined Functions (UDFs). The use of UDFs will make it easier to work on financial calculations in large databases.
Highlights
Aggregate queries over big economic relational databases, prepared with using of Structure Query Language (SQL) and special programs belong to the most used tools in the area of Business Intelligence (BI) and Data Analytics (DA)
SQL Server runs on Transact – SQL (T-SQL), a set of programming extensions, that add several features to standard SQL, including transaction control, error handling, row processing and declared variables
C., at all described in [10], [11] vector and matrix operations programmed with user-defined functions (UDFs) in a relational DBMS and a data mining system based on SQL queries and UDFs for relational databases
Summary
Aggregate queries over big economic relational databases, prepared with using of Structure Query Language (SQL) and special programs belong to the most used tools in the area of Business Intelligence (BI) and Data Analytics (DA). Writing user-defined functions or stored procedures presents common way in application development using a relational database management system. It allows to embed application code inside of RDBMS [15]. The types of user-defined functions (UDFs), that SQL Server supports, are scalar (return a single value) and table-valued (return a table). One limitation lies in the lack of generality for UDFs to express complex applications and to compose them with relational operators in SQL queries. Another limitation lies in the lack of systematic support for a UDF to cache relations initially for efficient computation in multi-calls. Lester in [6] recommended them as alternative methods to perform duct calculations
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