A CLOUD FRONTIER

Data quality testing & consulting

Accurate data for accurate business intelligence

Experts in data quality testing

The quality of your data is one of the most important aspects of any data project, whether that be a database or a data science project. Our consultants are experts in data quality testing and can put in place strategies and powerful tools in order to ensure the quality of your data.

The importance of data quality testing

The business intelligence you gain and use to make business decisions can only ever be as good as the raw data it stems from. If the data is of poor quality, it can lead to flawed intelligence, incorrect assumptions and ultimately open your business up to operational risk.

There are a whole host of reasons why data may be inaccurate, including:

  • Data inputting process
  • Legacy databases
  • Consolidation of data assets
  • Evolution of previously accurate data systems
  • Changes to the source systems

Data quality testing is crucial in order to ensure your data scientists, business analysts and all those who either analyse data or use the intelligence gained from analysis are able to make accurate data-driven decisions.

Watch the data quality testing video by our data scientist Sara Ruiz to find out more.

ACF consulting in data quality testing

At A Cloud Frontier our consultants are highly experienced in Great Expectations and AWS Deeque, as well as having worked with end-to-end solutions, such as:

  • Apache Airflow
  • Dataiku
  • Snowflake

No matter what your data project, our consultants can help you with your data quality testing.

Great Expectations for data quality

Great Expectations is our own powerful, open-sourced data quality testing tool, available on GitHub. It works by configuring and deploying your business rules and documentation framework and then validating all new data against these existing business rules.

Take a deeper dive into Great Expectations and watch our video to see it in action.

Why notifying the right people is critical?

When a data quality issue is detected it is crucial you notify the right people at the right time. Not providing the right notifications to stakeholders can be almost as problematic as delivering the wrong or missing data.

Therefore, when selecting the right data quality testing solution it is important to factor notifications into your data quality rules. Read our article on data quality severity handling & involving the right people to find out more.