Data Quality: Do You Know How Much It Is Affecting Your Bottom Line?

“Research estimates that an average of 20-30% of any analytics and reporting project is spent identifying and fixing data issues. In extreme cases, the project can get abandoned entirely.” 

This is according to research carried out by Dataversity and highlights the huge commercial significance of addressing data quality.

High-quality data is essential for accurate insights and fuels data-driven decision making, so it follows that ensuring data quality should be a high priority for any organisation when embarking on its data journey. This however is often not the case, being pushed down the line to a future time, leading to costly time, trust and financial losses.

So how can you improve your data quality? 

Data Quality Assessment

A data quality assessment considers all data sources and business goals relative to this information and results in a bespoke data quality framework, tailored to your required business outcomes.

Data Quality Framework

A data quality framework sits within your data cloud platform (Snowflake in our case) as a channel for all data sources to pass through on their way to warehousing and other lucrative use cases within the cloud environment. 

This framework ensures the quality and usefulness of all data which enters and flags any issues, so preventing them from passing through. By removing the need for active monitoring, the framework immediately provides a commercial return by eradicating a significant source of time loss from the business.

The framework generates commercial value in a multitude of ways, such as:

• Removing the risk of missed issues eminently possible with manual monitoring.
• Providing the opportunity for cause analysis for all data issues at source.
• Increasing trust in data warehousing capability as issues are identified proactively, reducing time and cost to address and fix.
• Shortening build phases of data projects and so reducing costs.

Data Quality Framework

As a data quality framework sits within a cloud environment such as Snowflake, all processing done by the framework makes use of credits. This is an extremely cost-efficient data operating model and a valuable use case for existing Snowflake customers.

Not sure how good your data is or how to improve it?   

Clekt support our customers with data quality assessments and the development of a bespoke data quality framework to ensure ROI in their investment in data. 

Enter your details below to discuss how we can support you with your data quality needs.