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AquaQ Analytics releases TorQ DQS for kdb+
AquaQ Analytics releases TorQ DQS, a Data Quality System for kdb+
TorQ DQS, which includes pre-defined data quality checks and user-defined data quality breach alerts, allows developers to easily set up customizable checks on the quality of their kdb+ data. Examples include table schema consistency checks for streaming data and the detection of data attribute anomalies, both of which can be parameterized by the developer.
"Data Quality is integral to any analytics platform today and is of the utmost importance in ensuring that actions and decisions, enacted off the back of models and algorithms, can truly be trusted ", noted Jonny Press, CTO at AquaQ Analytics.
The system broadly consists of a Data Quality Checker component (DQC) and a Data Quality Engine component (DQE), with the results of the checks being stored to a results table. The results can be plugged into a client's existing monitoring dashboards or can equally be plugged into a Grafana dashboard using AquaQ's recently released Grafana Adaptor for kdb+.
TorQ DQS can be used to monitor data quality in a TorQ-based kdb+ setup or separately in an independent kdb+ setup.
To download TorQ DQS, which forms part of TorQ release 3.7, please see https://aquaqanalytics.github.io/
An example DQS, running with data from the TorQ Financial Starter Pack, can be found here https://github.com/
About AquaQ Analytics: AquaQ Analytics Limited is a provider of specialist data management, data analytics and data mining products and services to clients operating within the capital markets and other sectors. With over 160 employees operating globally, our domain knowledge, combined with advanced analytical techniques and expertise in best-of-breed technologies, helps our clients get the most out of their data. For more information, visit www.aquaq.co.uk
About AquaQ TorQ Framework for kdb+: TorQ is an open source framework for kdb+ released by AquaQ Analytics. TorQ forms the basis of a production ready data capture and analytics system, by implementing some core functionality and utilities on top of kdb+. TorQ significantly reduces the time-to-market of any kdb+ implementation. It incorporates best practice kdb+ system development, with particular focus on performance, process management, diagnostic information, maintainability and extensibility.