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ADQT – Anblicks Data Quality Tool

An open-source-based data quality tool enabling proactive data monitoring.

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About ADQT

Data quality pertains to the accuracy, completeness, consistency, timeliness, and relevancy of data. Poor data quality can result in expensive mistakes, lost chances, and decreased efficiency. As per the most recent report by Gartner, businesses suffer an average loss of $15 million per year due to low data quality. Several tools for data quality have emerged in the market to tackle these challenges, each with distinct characteristics and abilities. These tools typically offer a range of functionalities, including data profiling, data cleansing, data matching, and data monitoring.

ADQT – Data Quality Tool combines all these features and functionalities in a single, easy-to-use platform, enabling organizations to improve data quality, reduce errors and redundancies, and drive better business outcomes. The tool integrates with Snowflake and Databricks and popular data catalog or metadata management systems, allowing for easy deployment and management on the cloud or on-premises. With its user-friendly interface and customizable rules, the tool can help businesses elevate their data quality and reduce the risks and costs associated with poor data quality.

The Challenges

Inaccurate or Incomplete Data

Incomplete or inaccurate data can lead to incorrect decisions, inaccurate analysis, and flawed insights.​

Data Integration Issues

When data is collected from multiple sources and is not properly integrated, it can lead to inconsistencies and errors.​

Data Security Risks

Poor data quality can increase the risk of data breaches and other security incidents, potentially exposing sensitive information.​

Increased Costs

Poor data quality can lead to increased costs associated with data cleanup, correction, and rework.​

Compliance Risks

Inaccurate data can result in compliance risks, such as failing to meet regulatory requirements or providing inaccurate financial reporting.​

Difficulty in Data Analysis

Poor data quality can make it difficult to conduct accurate data analysis, which can result in flawed insights and missed opportunities.​

Our Offerings

Optimize your data quality to drive better decision making ​

Anblicks’ data quality tool is a comprehensive solution for ensuring the accuracy, completeness, and consistency of your data. The tool is customizable, and you can set up data quality regulations to suit your specific requirements. It offers advanced features that can identify data quality problems throughout your entire data ecosystem. The features include:

    • An intuitive user interface for stakeholders to define data quality rules​.
    • Simple configuration for implementing the shift-left approach in existing data pipelines​.
    • Inline rules execution for real-time data quality testing during data processing​.
    • Pro-active data monitoring through​ Audit dashboard​.
    • Seamless Integration with Snowflake.
    • Integration with popular data catalog or metadata management systems​.

Solution Architecture

Unlock the Benefits of ADQT

1

Improved data quality​

The tool provides a powerful set of features for detecting data quality issues across your entire data ecosystem, helping to ensure data accuracy, consistency, and completeness.​

2

Increased efficiency​

With an intuitive and user-friendly interface, the tool makes it easy to define and execute data quality rules, saving time and effort compared to manual data validation.​

3

Flexibility​

The tool is built on top of the Great Expectations framework, which is an open-source solution that provides a wide range of customization and integration options. With support for Snowflake integration, the tool can seamlessly integrate into your existing data workflows.​

4

Configurability​

The tool is highly configurable, allowing you to define and customize data quality rules to fit your specific needs and requirements.​

5

Shift-left approach​

By shifting data validation left, the tool helps to detect and resolve data quality issues early on in the data pipeline, reducing the risk of downstream data problems.​

6

Improved collaboration​

The tool provides a centralized location for defining and managing data quality rules, which can improve collaboration and ensure consistency across your organization.​

Elevate your data quality with our Intuitive Data Quality Tool. Schedule a Free Demo.
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