Big Data & Analytics Services
Improve the quality and reliability of your data, increase productivity, reduce operational risk and ultimately make better business decisions with Great Expectations – a powerful data quality testing solution for all data-driven businesses.
Do not assume your data is correct!
In order to make the right data-driven business decisions it is crucial that any analysis conducted is based on accurate data, but in many cases – despite the best efforts to build reliable data assets – the data may not be correct.
Often inaccurate data goes unnoticed for a long time, until much later a problem rears its ugly head and opens a can of worms. At this stage, although you know there is a problem, it can be very challenging and time-consuming to detect where the problem originates from. Worse still, inaccuracies may go completely undetected, leading to decisions based on incorrect intelligence that open the business up to operational risk.
Typical reasons for inaccurate data
Great Expectations is an open-source data quality testing tool, available on GitHub that monitors data quality, automates the verification of new data and simplifies the debugging process. It reduces productivity drain and operational risk by improving the data quality and the trustworthiness of your analytics.
New raw data is imported
The data is validated through Great Expectations and each row of data is updated either with a 0 or 1 depending on whether it fails or passes the business rule
The invalid rows (those that ‘fail the test’) are moved into a separate ‘quarantine’ table, while the valid rows are moved into a clean table where the data pipeline can continue
All data is removed from the raw ‘staging table’, making it ready to take the new data and repeat the flow on a monthly basis.
And overall make better business decisions which is the ultimate goal!
Ready to find out more? Our team are excited to be able to show you what Great Expectations can do for your business!
Arrange a demo today or speak to one of our team for more information