Explore a 50-minute conference talk from the PASS Data Community Summit that introduces a design architecture for capturing and measuring data quality issues in small to mid-size Kimball data warehouses. Learn how to relate these issues to existing fact and dimension tables. Dive into topics such as data quality definitions, mandated reporting, organizational commitment, metadata, master data, data profiling, and design implementation. Discover the secrets of sequence IDs, data quality rules execution, and the structure of data quality schemas. Examine case studies, reporting requirements, data flow, and mandatory reporting workflows. Gain insights into improving data warehouse quality and efficiency through this comprehensive presentation by Robert Hart, an Architect at the 2018 PASS Marathon event.
Overview
Syllabus
Introduction
Agenda
What is Data Quality
Poll
mandated reporting
organizational commitment
metadata
master data
data profiling
design implementation
secret
sequence ID
Data Quality Rules
Data Quality Rules Execution
Data Quality Rules Not Matching
Data Quality Schema
Data Quality Group Bridge
Select Statement
Group Structure
Data Quality Rule
Bridge Table
Dimension Provider
Dimension View
Case Study
Reporting Requirements
Data Flow
Reporting
Workflow
Output
Mandatory Reporting
Questions
Taught by
PASS Data Community Summit
