The First Law of Data Quality explained the importance of understanding your Data Usage, which is essential to the proper preparation required before launching your data quality initiative.
The Second Law of Data Quality explained the need for maintaining your Data Quality Inertia, which means a successful data quality initiative requires a program - and not a one-time project.
The Third Law of Data Quality explained a fundamental root case of data defects is assuming data quality is someone else’s responsibility, which is why Data Quality is Everyone’s Responsibility.
The Fourth Law of Data Quality explained that Data Quality Standards must include establishing standards for objective data quality and subjective information quality.
The Fifth Law of Data Quality
More and more organizations are realizing the critical importance of viewing data as a strategic corporate asset, making data quality an increasingly prevalent discussion.
The perceived gap separating business and IT is starting to close as both business and technical stakeholders are coming together in collaboration around data-driven efforts to enable better business decisions and deliver optimal business performance.
The data quality market continues to evolve away from esoteric technical tools and toward business-empowering suites providing robust functionality with increasingly role-based user interfaces, which are tailored to the specific needs of different users, such as business analysts, data stewards, developers and system administrators.
The deployment of data quality functionality within and across the organization also continues to evolve, as data cleansing activities are now also being complemented by real-time defect prevention services used to greatly minimize poor data quality at the multiple points of origin within the enterprise data ecosystem.
Continuing improvements in robust reporting and data visualization capabilities are making the correlation between poor data quality and suboptimal business processes far more tangible - especially for executive management.
Despite these advances, data quality often remains - at best - a secondary consideration during the planning and execution of enterprise information initiatives such as data integration, master data management, data warehousing, business intelligence and data governance.
Therefore, The Fifth Law of Data Quality states that:
“It is because data must be viewed as a strategic corporate asset that Data Quality must be viewed as the foundation upon which all enterprise information initiatives are built, enabling them to deliver data-driven solutions to business problems.”