Ensure Dependable Data for Your Business.
Quality data is the crucial ingredient for building modern machine learning models and data analytics platforms. Qualitest ensures the quality of data to guide the business with data-driven intelligence.
Empower your data: Elevate quality, security and decision making.
Novel data sources require expertise beyond mere data verification. Qualitest integrates data quality as a fundamental Quality Engineering process earlier in the development lifecycle. These proactive quality checks provide actionable insights and automation opportunities for more reliable datasets.
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Reap returns from capital investment on Data Analytics (DA) platforms.
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Avoid data security and compliance risk by protecting privacy and sensitive information leveraging AI based sensitive data analysis.
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Reduce lead time to deliver fresh insights with improved efficiency.
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Build and maintain reliable AI models to make business decisions based on dependable data.
Create your data quality strategy effectively.
Drive organizational effectiveness and innovation with a Data Quality strategy. Enable insightful decision-making, improve your customer experiences, and expedite your time-to-market.
Implement robust data collection and leverage advanced analytics. Every step toward improved data insights is a step towards informed decision making and business success.
Vastly improve overall customer experience with a more accurate picture of customer segmentations, behavioral traits and sentiment towards your product.
Leverage AI to track privacy information across your data lineage and implement effective data obfuscation techniques to enforce robust privacy measures and reinforce your security posture
Accelerate comprehension of market demands and enable rapid response and necessary adjustments to product lines.
Data assurance from strategy to implementation.
With any organization, the data lifecycle comprises of its creation, movement, processing, retention, and archiving. It is critically important to establish data quality standards at its creation point and confirm data quality during transfer and transformation.
Qualitest data assurance solutions encompass a comprehensive testing strategy for data movement, whether within on-premises environments or the cloud, regardless of whether it’s an as-is migration or a transformative migration.
Harnessing the power of automation, we’ll help you to enable the continuous testing of data pipelines built on modern platforms such as Azure Databricks, Azure Data Factory, AWS Glue, GCP BigQuery, Snowflake and more.
We use AI–infused data quality validation to assure that a defect-free dataset is provided for data modeling and analytics. This includes comprehensive coverage of BI report validation on PowerBI, Tableau, Looker and others.
We can help you establish best-practice data standards and data catalogs by streamlining the meta data management and business glossary and terminologies. We have expertise in leveraging Microsoft Purview, Alation and Collibra.
A success story
Data pipeline migration from AWS Redshift to SnowFlake for Media and Entertainment Company.
01—Challenge
The customer transitioned from AWS Redshift to Snowflake, transferring extensive structured and unstructured data, rewriting pipelines with complex SQL queries, requiring thorough testing for accuracy.
02—Solutions
We devised a comprehensive data testing plan for migration and pipeline validation, employing well-structured data transformation mapping templates and reusable SQL queries for rule validation.
03—Results
- 100% On-time completion of the program.
- Validation assets created for future usage.
- Avoided AWS Cloud charges for Redshift.
What else can we help you with?
Let us know what your needs and requirements are and we’ll tailor a solution that will make life easier for you.
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