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What is the Data Quality Framework do you use/recomend ?

William_Scardua
Valued Contributor

Hi guys,

In your opinion what is the best Data Quality Framework (or techinique) do you recommend ?

 

2 REPLIES 2

Kaniz_Fatma
Community Manager
Community Manager

Hi @William_Scardua, Certainly! Data quality is a critical aspect in any organization, ensuring that data is accurate, consistent, and reliable.

 

Here are some key components of a robust data quality framework:

 

Data Governance: Establish policies, standards, and guidelines for data collection, storage, and usage within the organization. It serves as the foundation for data quality efforts.

Data Profiling: Examine available data to identify anomalies, inconsistencies, or inaccuracies. Collect statistics and informative summaries about the data.

Data Quality Rules: Define predefined rules or constraints to check the accuracy, validity, consistency, and completeness of data. These rules can be business-specific or cross-dataset checks.

Data Quality Assessment: Regularly audit data quality performance using predefined rules. Use data-quality scorecards tailored to organizational needs.

Data Cleaning: Detect and correct (or remove) corrupt, inaccurate, or erroneous records from datasets or databases.

Data Monitoring: Continuously monitor data quality to ensure ongoing accuracy and reliability.

Data Issue Management: Address and resolve data quality issues promptly.

Data Reporting: Generate reports on data quality metrics and communicate findings to stakeholders.

Continuous Improvement: Regularly review and enhance the data quality framework based on feedback and evolving requirements.

 

As for specific tools, here are some recommendations:

Remember that the choice of framework or technique depends on your organizationโ€™s unique needs and context. Consider factors such as scalability, ease of implementation, and alignment with existing processes. ๐ŸŒŸ

joarobles
New Contributor III

Hi there!

You could also take a look at Rudol, it has native Databricks support and covers Data Quality validations and Data Governance enabling non-technical roles such as Business Analysts or Data Stewards to be part of data quality as well with no-code validations and integrations with everyday tools like Slack or Microsoft Teams.

Have a high-quality day!  

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