Mastering Data Quality Management with Alydata and Collibra
As businesses continue to generate vast amounts of data, the need for effective data governance and quality programs has never been greater. At Alydata, we recognize that scaling these efforts can be daunting, but taking the right approach can lead to significant gains for your organization. In this post, we'll explore how Alydata works with Collibra to implement a data quality rule of 1 strategy that maximizes the return on investment (ROI) for our clients.
Start Small, Focus on High-Impact Areas
To achieve successful ROI with data quality, it's crucial to start small and focus on high-impact areas. Many organizations make the mistake of trying to clean all of their data or solve every data quality issue at once. This approach can be overwhelming and often results in little progress. On the other hand, starting small with a defined set of Critical Data Elements (CDEs) enables you to effectively assess your data health and take appropriate actions. At Alydata, we use the Collibra Data Governance Center to manage and govern our clients' CDEs.
Automate Rule Writing to Save Time and Effort
Writing millions of data quality rules manually is not feasible. At Alydata, we use Collibra's automated rule writing feature to define rules for our clients. This feature saves time and resources while also ensuring that the rules are consistent and accurate. Automated rule writing also helps your data quality analysts to focus on high-value work, such as analyzing the output and taking the appropriate actions.
Ensure You Have the Resources and Processes in Place
Data quality programs require teams with the right skills and processes to manage daily incidents. By setting up proper governance processes, regular check-ups, and focused training sessions, your team will be well-positioned to manage daily data quality issues and avoid escalating problems.
Active Governance and Quality Checks on Reported Data
It's important to actively govern and run quality checks on data that will be reported or potentially acted upon. The use of Data Quality Metrics and active measurements alerts the team to any issues before they become more difficult to resolve. This approach also ensures that your downstream data consumers have confidence in the data they receive.
Mastering data quality in today's data-driven world is challenging but crucial. That's where Alydata and Collibra come in. By starting small, automating rule writing, ensuring you have the right resources and processes in place, and actively governing and running quality checks on reported data, Alydata ensures that your organization can size for success with data quality. To learn more about how we can help your organization, visit our website at www.alydata.com or contact us at info@alydata.com.