Developing Data Science solutions involves the iterative inclusion of data sources into models that develop insights. Data Science depends on: Rich Data Sources: Data with the potential to show otherwise …
Big Data and Data Science – A Glance
Big Data is produced through email, social media, online orders, and even online video games. Data is generated not only by phones and point-of-sale devices, but also by surveillance systems, …
Data Quality – Policy and Metrics
Data Quality – Policy Data Quality efforts should be supported by and should support data governance policies. For example, governance policies can authorize periodic quality audits and mandate compliance to …
Data Quality Program – Readiness Assessment / Risk Assessment
Findings from a readiness assessment will help determine where to start and how quickly to proceed. Findings can also provide the basis for roadmapping program goals. If there is strong …
Data Quality Program – Implementation Guidelines
Typically, a hybrid approach works best – top-down for sponsorship, consistency, and resources, but bottom-up to discover what is actually broken and to achieve incremental successes. Improving data quality requires …
Data Quality – Audit Code Module and Metrics
Quality Check and Audit Code Modules Create shareable, linkable, and re-usable code modules that execute repeated data quality checks and audit processes that developers can get from a library. If …
Data Quality – SLA – Service Level Agreements
A data quality Service Level Agreement (SLA) specifies an organization’s expectations for response and remediation for data quality issues in each system. Data quality inspections as scheduled in the SLA …
Data Quality Rules
Data Quality Rules provide the foundation for operational management of Data Quality. Rules can be integrated into application services or Data services that supplement the Data lifecycle, either through Commercial-Off-The-Shelf …
Data Quality – Improvement (Part 1)
In order to improve the Data Quality, DQ Analysts must have the clear picture about Current State of Data Quality as well as Organizational Readiness for Data Quality. Getting a …
RDM – Reference Data Management
Reference Data is any data used to characterize or classify other data, or to relate data to information.Reference Data Management entails control and maintenance of defined domain values, definitions, and …