The dq framework is a Data Quality Framework that integrates with SQL databases to enable data quality measures by design in projects. It supports SQL-driven automation, standardizes data validation, and provides custom insights with streamlined monitoring for compliance and team efficiency.
Features
Generic framework
Addresses the enterprise data quality needs of all projects by providing a standard framework adaptable to various demands.
Effortless setup
Allows users to set up their Data Quality Framework quickly without needing development overhead, making it accessible to all project sizes.
SQL-Driven automation
Facilitates easy integration with SQL database projects like MS-SQL, Azure SQL, and AWS RDS, automating tasks for efficiency.
DQ by-design
Integrates data quality measures directly into every project, ensuring quality is built into the data handling processes.
Sets reference
Creates a trustworthy Data Quality reference among stakeholders and team members, improving collaboration and clarity.
Compliance
Supports data governance initiatives and ensures projects can embark on compliance with ease.
Standardized
Enables organization-wide data quality assurance by standardizing processes, improving the validation process.
Boost team efficiency
Eliminates costly data discrepancies and automates operations to enhance company income and productivity.
Integration
Provides insights using SQL views, facilitates DQ scores, and integrates seamlessly with reporting tools.
Streamlined monitoring
Offers SQL views for continuous monitoring of data quality across your data domain, maintaining high quality standards.
Generic framework
Addresses the enterprise data quality needs of all projects.
Effortless setup
Get started quickly with your own Data Quality Framework without any development overheads.
SQL-Driven automation
Integrates easily with SQL database projects like MS-SQL, Azure SQL, and AWS RDS.
DQ by-design
Enables data quality measures by design in every project.
Sets reference
Creates a trustworthy Data Quality reference among stakeholders and team members.
Compliance
Supports data governance initiatives focusing on compliance.
Standardized
Applies organization-wide for all projects, facilitating an efficient and effective data validation process.
Boost team efficiency
Eliminates costly data discrepancies and automates operations to improve company income and productivity.
Integration
Provides insights using SQL views, facilitates DQ score, and integrates well into reporting tools.
Streamlined monitoring
SQL views for continuous monitoring of data quality across your data domain.