SQL Server Database Engineering and T-SQL Optimization

Authors

  • Durga Prasad Independent Researcher Author

DOI:

https://doi.org/10.32628/IJSRSET261353

Keywords:

T-SQL Optimization, Relational Schemas, SSIS ETL, Performance Tuning, Azure SQL Migration

Abstract

Enterprise-scale relational schemas demand engineering portfolios exceeding 75 stored procedures, triggers, functions, pointers, and views across SQL Garçon performances from 2008 to 2019. Query execution times drop by over 45 on high-volume line-of-business reporting workloads through targeted T-SQL optimization. SQL Garçon Integration Services packages automate data backups and serialization, while SQL Garçon Reporting Services delivers parameterised dashboards, adding up knockouts of thousands of records daily for stakeholder opinions. Proficiency in Language-Integrated Query to SQL, Extensible Markup Language handling, exception operation, and performance tuning tackles trade channels and compliance reporting. This capability extends to DB2 hybrids with cursor control and package design for data integrity. listed views in Azure SQL migrations maintain sub-second responses under peak loads, icing robust data layers for Model-View-Controller architectures.

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References

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Published

26-06-2024

Issue

Section

Research Articles

How to Cite

[1]
Durga Prasad, “SQL Server Database Engineering and T-SQL Optimization”, Int J Sci Res Sci Eng Technol, vol. 11, no. 3, pp. 699–705, Jun. 2024, doi: 10.32628/IJSRSET261353.