R&D
❯
Automated QA
❯Predictive data quality
Predictive testing
Scope:
Automatic detection of inaccurate test outcomes in an application development
process
Goal:
Other
Automated Quality Assurance
For:
Quality Engineers
Predictive data quality
Scope:
A solution for assessing data quality in data collection systems.
Goal:
Other
Anomaly detection in sensor data using deep learning techniques
For:
Maintenance and support functions, monitoring, procurement
Scope:
Temporal data captured from sensors.
Goal:
Other
Predictive data quality
Goal:
OtherProblem addressed
Using machine learning techniques for identifying complex or unknown
correlation among data in order to score its quality and enhance the confidence
of the data consumer in using data for decision making processes.
Scope of use case
A solution for assessing data quality in data collection systems.
Description
The solution relies on four elements.
Sources: the data sources represent the subject of the
assessment. These sources can be heterogeneous
(structured and semi-structured).
Model: the representation of the ontology used as a
reference for identifying the non-conformity of data
Processes: the set of processes that produce and
consume data, whose execution can be affected by the
quality of data
Organization and governance: the set of policies and
procedures for governing data and handling the
advanced data quality techniques.
Bayesian network
AI: Understand