Improve Integrity With Our Data Quality Assurance Services
Quality outcomes and insights start with the quality of data. For the management of data, there is no space for inconsistencies or anomalies. At the onset address data issues by implementing stringent the process of data quality filters and cleaning raw data. At Magic Infomedia, data quality assurance service ensures that your business data is complete, accurate, consistent, reliable, valuable, timely, and interpretable to meet project requirements. If you do not trust your data, there is a good reason. Our company implements analytics, and then customizes our solutions, without any implementation to ensure data accuracy. Complete data is to provide genuine information on which you can take your business decisions. Data that is not accurate can lead you to the wrong path.
Our Automated Data Quality Assurance Bring Peace of Mind
By leveraging automated data quality assurance solutions with Magic Infomedia’s expertise. We can help you to minimize such issues and bring you peace of mind, and further evolve with your organization.
Quality of Data Matters – App analytics, web analytics, advertising and testing tools, data management, and tag management systems are good as data that they process. Our quality assurance testing team confirms the source of data including tags on the website or apps that are deployed completely and correctly.
Data Quality To Be Improved & Measured – Compared to the cost of quality assurance processes and the risk associated with inaccurate digital data, users can not afford to deploy measures of data quality assurance. Automated data saves time and removes human error.
Improved Data Quality Increases ROI – Consistently correct, compliant, and complete data helps to improve the investment return of your complete stack of digital marketing technology, by reducing manual efforts on QA flows.
Offering Comprehensive Data Quality Assurance Services
Data Quality Consultation
- Fix problems with data quality in software systems.
- During migration, relocate data to a new system.
- Integrate data from different software systems.
- Identify data quality improvement, etc.
Assessment for Data Quality
- Define data quality rules and thresholds.
- Evaluate data quality based on thresholds and rules.
- Report conduct root cause analysis and identified issues in data quality.
- Design data quality rules to establish processes for data quality management.
Data Quality Assurance Management
- Data quality standards and rules definition.
- Regular monitoring and controlling of data quality.
- Monitoring and reporting of data quality variations.
- Resolution of issues in data quality.
Testimonials
We have worked with Magic Infomedia for many years. Now I can speak about his effectiveness and accomplishments. In addition to his capabilities, we ensure their level of quality infrastructure and applications. They do fantastic work as a business partner. We also earned respect and appreciation from the Magic Infomedia professionals team.
George Ben, New York, United StatesWe’ve been working with the quality assurance team of Magic Infomedia for many years. During this time their quality assurance team of experts shows us a high level of work quality. We depend on their expertise and hard work. They are providing experienced and qualified resources at a reasonable price.
Enrich Fernandez, New York, United StatesThe Quality Assurance team at Magic Infomedia has consistently provided high-quality testing services for our company that has been very accommodating when we were on tight schedules to complete our projects on time. Scripts which they make for us helped our company to achieve quick health checks and faster regression cycles. We are looking forward to our continued testing efforts with their professional team.
Nick, New York, United States