Updated
November 12, 2024

Part 1: Introducing the Secoda Data Quality Score - Your data quality, quantified

Introducing Secoda's Data Quality Score: empower data teams to measure, manage, and improve data quality, driving better decisions and operational efficiency.

Etai Mizrahi
Co-founder
Introducing Secoda's Data Quality Score: empower data teams to measure, manage, and improve data quality, driving better decisions and operational efficiency.

“What gets measured gets managed”, and what can’t be measured gets lost in the noise. 

Companies produce, store, and manage more data than ever before - ensuring data quality is paramount, but this has always been a huge challenge for data teams. 

Managing data without assessing its quality is a recipe for inconsistency and inefficiency. This is why at Secoda, we’ve developed our new Data Quality Score (DQS). Our goal with DQS is to provide a clear, actionable metric that empowers data teams to elevate their data quality and consequently, their decision-making and operational efficiency. The ability to quantify and improve data quality is no longer a “nice to have” - it’s essential.

Why measuring data quality is crucial today

Every year, poor data quality costs organizations an average of $12.9 million dollars, and is linked directly to quality of decision making. Data quality is a competitive advantage, with good data quality leading to better decisions, leads, higher customer satisfaction, to name a few benefits. 

Data quality scores play a crucial role in data management. It provides a tangible, quantitative metric of the quality of data in a dataset, taking into account factors such as accuracy, completeness, validity, and consistency. This score helps in identifying the reliability and trustworthiness of data for analysis, reporting, and decision-making.

When beginning the process of creating our DQS, we learned about the internal DQS that Airbnb has developed, faced with the challenges of managing vast amounts of data, and recognizing the need for a system to measure and improve data quality. The data team at Airbnb built their own data quality scoring tool, which would provide a quantitative measure of data quality, and has become a critical part of Airbnb’s data strategy, helping to ensure the reliability and trustworthiness of their data. 

Airbnb’s data practitioners struggled with the volume of data, and its decreasing quality. Low-quality data would cause delays in decision-making, and lead to poor decisions - does any of that sound familiar? Airbnb isn’t alone. We have heard similar pain points and stories across the board from our users as well as the broader data community.

Secoda is the natural home for data quality

At Secoda, we believe that data management requires a holistic approach. Our platform is designed to integrate seamlessly into your workflows and offers a 360-degree view of your data, so introducing the data quality score was a natural next step. It just makes sense.

Fragmented data management leads to inefficiency and missed opportunities. Our unified platform, with the new addition of DQS at its core, brings everything a data team needs into one cohesive, intuitive environment:

  • Increased efficiency: Centralizing tools and metrics within Secoda saves time and reduces complexity, eliminating the need to switch between disparate systems.
  • Enhanced collaboration: A unified platform promotes better communication and collaboration among team members, with everyone accessing the same data quality metrics.
  • Improved decision-making: Easily accessible and understandable data quality metrics empower your team to make informed decisions quickly.
  • A holistic view of your data: Our DQS provides a comprehensive view of your data’s health, ensuring that every aspect of data quality is accounted for and improved across your entire stack.

Within the Secoda environment, we gather all your data knowledge in one place, from metadata, to monitoring, to governance. This deep integration and understanding of your data landscape makes it incredibly simple to plug in and get started with your data quality score. 

With everything already connected and accessible within Secoda, implementing DQS becomes a seamless process, allowing you to start measuring and managing your data quality without any additional complexity. Like the final piece of a puzzle - everything clicks into place.

Implementing a Data Quality Score: a straightforward path

Data teams today are tasked with ensuring that data is not just accessible, but reliable, accurate, and ready to drive impactful decisions. DQS fits seamlessly into this mission by providing a straightforward solution to measure and manage data quality. 

By adopting DQS within Secoda, data teams can immediately start leveraging a comprehensive and intuitive metric that simplifies the complexity of data quality management. A plug-and-play solution that doesn't require reinventing the wheel, for data teams aiming to stay ahead of the curve, DQS is the clear, straightforward path to better data and better decisions.

With Secoda’s DQS, you can set the benchmark, quantify excellence, and assure accuracy in your data operations. 

Head over to Part 2 where we’ll explore the inner workings of DQS, including a deep dive into how DQS is calculated, real-world applications and steps to implement this in your organization.

Also check out Part 3 where we uncover how to implement Secoda's DQS to enhance data quality

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