Data Science Process: A Step-by-Step Scientific Approach The Data Science process follows the scientific method of refining knowledge by making observations, formulating and testing hypotheses, observing results, and formulating general …
Data Science – Dependency
Developing Data Science Solutions Developing Data Science solutions involves the iterative inclusion of data sources into models that develop insights. Data Science depends on: Rich Data Sources in Data Science …
Big Data and Data Science – A Glance
Big Data and Data Science: Driving Innovation Through Insights Big Data is produced through email, social media, online orders, and even online video games. Data is generated not only by …
Data Quality – Policy and Metrics
Data Quality Governance and Policy Integration Data Quality efforts should be supported by and should support data governance policies. For example, governance policies can authorize periodic quality audits and mandate …
Data Quality Program – Readiness Assessment / Risk Assessment
Importance of Readiness Assessments in Data Governance Findings from a readiness assessment will help determine where to start and how quickly to proceed. Findings can also provide the basis for …
Data Quality Program – Implementation Guidelines
Data Quality Implementation Guidelines Typically, a hybrid approach to executing data quality initiatives works best – top-down for sponsorship, consistency, and resources, but bottom-up to discover what is actually broken …
Data Quality – Audit Code Module and Metrics
Data Quality Checks 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. …
Data Quality – SLA – Service Level Agreements
What is Data Quality Service Level Agreement? A data quality Service Level Agreement (SLA) specifies an organization’s expectations for response and remediation for data quality issues in each system. Data …
Data Quality Rules
Data Quality Rules – Foundation of Operational Management Data Quality Rules provide the foundation for operational management of Data Quality. Rules can be integrated into application services or Data services …
Data Quality – Improvement (Part 1)
Data Quality Improvements – Assessing the Current State In order to improvements the Data Quality, DQ Analysts must have the clear picture about Current State of Data Quality as well …