Data Integrity | Pricefx Knowledge Base

Series of questions to identify the level of data harmonization and synchronization within an organization. The higher this value, then the greater the data maturity.

CONSENSUS TYPE	CHARACTERISTIC	QUESTIONS
Data Quality	Defining	Can you provide a short description of the data quality in the organization? Would you describe it as Above Average, Average, Below Average, or Poor? Is data quality on critical data deemed important? Who drives data quality management in the organization?
	Process	How would you describe the process for building data quality in the organization? Is it driven top-down or bottom-up? Advantages & Disadvantages of the approach? How has this concept been embraced by the organization? If not, why? How are disagreements resolved? Do we do regular assessments to find quality gaps? How do we determine data quality? What measures are used? How do we trace and fix data quality problems?
	Ownership	Who owns this data quality process? Is it singular or multiple owners? Is this good or bad? Who is responsible for maintaining this enterprise-level data quality? How does the owner gain access to enterprise data for quality control purposes? Who approves this access? Can access to enterprise data be denied to this owner? Who is responsible for validation? Who provides access to it to the organization?
Cleansing and Validation	Existence	Can you provide a short description of your organization’s approach to data cleansing? Validation? Transformation? Would you describe it as Above Average, Average, Below Average, or Poor? Are these processes on critical data deemed important? Who drives their execution in the organization
	Ownership	Who owns these processes? Is it singular or multiple owners? Is this good or bad? Who is responsible for maintaining data cleansing? Validation? Transformation? How does the owner verify these processes for quality control purposes? How do we know? Who maintains these processes?
	Procedures	How is the enterprise data quality updated? Who manages the changes? What data quality control is in place during enterprise integration? How is the quality validated? Who does this? Is the data transformed before being loaded? Who does this? How are validation and transformation performed? What types of transformations are performed during this level of integration Is this an automated process? Manual?
	Performed	How would you describe the process for building data cleansing? Data validation? Data transformation? Is it driven top-down or bottom-up? Advantages & Disadvantages of the approach? How has this concept been embraced by the organization? If not, why? How are disagreements resolved? Do we do regular assessments to find gaps in these processes? How do we determine the effectiveness of these processes? What measures are used? How do we trace and fix problems in them?
Data Governance	Existence	Can you provide a short description of your organization’s approach to data governance? Would you describe it as Above Average, Average, Below Average, or Poor? Is the process of data governance deemed important? Who drives its development in the organization?
	Process	How would you describe the process for building data governance? Is it driven top-down or bottom-up? Advantages & Disadvantages of the approach? How has this concept been embraced by the organization? If not, why? How are disagreements resolved? Do we do regular assessments to find gaps in our governance processes? How do we determine the effectiveness of data governance? What measures are used? How do we trace and fix problems in this process? Would you describe your data governance as Strict, About Right, Needs Work, or Too Lax?
	Utilization	How would you describe the process for building data governance? Is it driven top-down or bottom-up? Advantages & Disadvantages of the approach? How has this concept been embraced by the organization? If not, why? How are disagreements resolved? Do we do regular assessments to find gaps in our governance processes? How do we determine the effectiveness of data governance? What measures are used? How do we trace and fix problems in this process? Would you describe your data governance as Strict, About Right, Needs Work, or Too Lax?
	Ownership	Who owns these governance processes? Is it singular or multiple owners? Is this good or bad? Who is responsible for maintaining data governance? How does the owner verify these governance processes are adding value? How do we know? Who maintains these governance processes?
	Implementation	How is enterprise data governance updated? Who manages the changes? What data governance controls are in place during enterprise integration? How is the governance validated? Who does this? When and where is data governance performed? By whom? Is this an automated process? Manual?