Restore Trust in Your Data Using a Business-Aligned Data Quality Management Approach
With the ever-increasing demand from the business to make data-driven decisions, IT is struggling to ensure quality in the large volumes and variety of data.
IT consistently hears that the reports that the business relies on are not accurate, and they are required to perform time-intensive and costly manual fixes to the organization’s data.
Data users do not trust the data quality in your company. Business users bypass IT and establish their own data silos to manage quality. Without governance or consistency, data quality issues are propagated further within data silos.
Data is not usable or useful to the business due to deficiencies in quality and processes, resulting in decisions being made based on intuition and weak analysis. Worse, these decisions can be based on the wrong data.
With sub-optimal data quality, companies are unable to launch related data initiatives such as business intelligence, master data management, and big data. They need a clear understanding of business requirements and the implementation of data quality processes first.
Download the Executive Brief to learn how to:
Implement a set of data quality initiatives that are aligned with overall business objectives and aimed at addressing data practices and the data itself.
Develop a prioritized data quality improvement project roadmap and long-term improvement strategy.
Build related practices such as business intelligence and analytics with more confidence and less risk after achieving an appropriate level of data quality.
