DATA QUALITY
Assurance
Data quality assurance is the methodology used to monitor and verify data quality within the business enterprise. Data quality assurance provides transparency and is focused on root cause analysis. Monitoring data quality and fixing data errors is mission critical. Data errors quickly spread throughout the enterprise and can also infect external data sources. We create data quality assurance platforms for the business enterprise.
DATA QUALITY
Cleansing
Data cleansing is the process of detecting and correcting corrupt or inaccurate data. Data cleansing may be performed interactively with specialized data tools, or as batch processing through scripting. We leverage MetaLibrary™ and DataDoctor™ to augment traditional data cleansing. We can dynamically detect and fix data issues using the underlying metadata, or we can generate source code that integrates directly into any data platform.
DATA QUALITY
Symptoms
Data quality is emblematic of the underlying health of data management within an organization. Data errors directly impact the bottom line, drain company resources, and drive away customers. Data issues kill innovation and erode the confidence and trust of the underlying data.
DATA QUALITY
Laboratory
Data analytics are the scientific methods, processes, algorithms and systems used to extract knowledge and insights about data. Reference metadata is information about data quality. Statistical metadata is information about resources and performance. We leverage DataDoctor™ Laboratory to augment traditional data analytics. We can dynamically harvest reference and statistical metadata from existing data sources.
DATA QUALITY
Diagnosis
We leverage DataDoctor™ Diagnosis to augment traditional error pattern and root cause analysis.
DATA QUALITY
Treatment
We leverage DataDoctor™ First Aid Kit to augment traditional data error detection and correction.
