Aquatic Informatics has announced the launch of HydroCorrect, a new automated data validation tool that can power proactive monitoring and management of groundwater, flooding, and water quality in the Aquarius platform.
HydroCorrect transforms data quality assurance and quality control (QA/QC) processes using machine-learning to automate and standardize workflows, detect data anomalies, ensure regulatory compliance, and enforce data standards organization-wide, leading to an exponential reduction in time and resources spent on the QA/QC process. The tool provides immediate recommendations on how to respond to environmental events and influence long-term decisions while ensuring the data that drives those suggestions is defensible, reliable, and timely.
Michael McCormick, Vice President of Product at Aquatic Informatics said: “Anomaly detection and correction is one of the most important and time-intensive elements of working with time series data, and it is becoming a bigger problem as data volumes grow. Aquarius already provides advanced tools to help users rapidly see and correct erroneous measurements. With machine-learning technology, HydroCorrect will transform the QA/QC process with automation and standardized workflows that save time and improve data quality.”
Trusted Automation, Estimation, and Correction
HydroCorrect enables organizations to easily transition to automation by providing support and giving operators full control. Trusted automation provides flexibility through user approved actions until operators are ready to fully automate any action as well as visibility with the audit trail and easy to understand rule creation and anomaly detection. Estimations and corrections use high-accuracy, in-situ, field-visit data to adjust the continuous time series data, creating full confidence in the abilities of the analysis.
Reduce Time and Resources Spent on QA/QC
Organizations invest a significant amount of time in the QA/QC process, with one customer estimating “approximately 210 hours” — or 26 business days — spent each year, on average, on data validation alone. HydroCorrect reduces mundane work and enables skilled workers to perform higher-value and more engaging tasks that can have an impact on making better data driven decisions. Using machine-learning technology validates water data from numerous sources effortlessly, and the suggestion-based approach means the user always stays in control while saving hours of time on manual QA/QC processes. Existing Aquarius users can implement HydroCorrect to see the benefits of automating their QA/QC processes.
