CWDS Glossary
The CWDS Glossary includes a List of Acronyms and defined terms captured from various models, reports, and other artifacts pertaining to the Child Welfare System – California Automated Response and Engagement System (CWS-CARES) Project. The Glossary standardizes terms used across the various project disciplines; each term is defined with its meaning specific to the project domain.
The State may update the CWDS Glossary at any time. Any questions please contact CWDS Communications.
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
Dashboard
In information technology, a dashboard is a user interface that, somewhat resembling an automobile's dashboard, organizes and presents information in a way that is easy to read.
Data Access Services
A set of services within the Application Program Interface (API) layer that support create, read, update, delete (CRUD) functions with existing data stores (e.g., Child Welfare Services/Case Management System), new data stores (e.g., PostgreSQL), and integration partners.
Database Administrator
A resource that provides technical leadership and operational expertise for the implementation, architecture, design, ongoing support and maintenance of databases and related software tools. Designs, develops, and maintains data models utilizing data modeling and code generation tools.
Data Center
A large group of networked computer servers typically used by organizations for the remote storage, processing, or distribution of large amounts of data.
Data Exchange(s)
The automated, electronic submission or receipt of information, or both, between two automated data processing systems.
Data Loss Prevention (DLP)
The practice of detecting and preventing data breaches, exfiltration, or unwanted destruction of sensitive data.
Data Modeling
A software engineering process of creating a data model for an information system by applying formal data modeling techniques.
Data Quality (DQ)
A measure of the condition of data based on factors such as accuracy, completeness, consistency, reliability and whether it's up to date. Measuring data quality levels can help organizations identify data errors that need to be resolved and assess whether the data in their IT systems is fit to serve its intended purpose.
Data Quality Audit
The auditing of data to assess its quality or utility for a specific purpose.
Data Warehouse
A system where data is stored for archival, analysis, and security purposes, and that is the platform used to support business intelligence processes and facilitate analysis and reporting.