- IT and the business do not understand the root causes behind data quality issues when developing corrective initiatives.
- Small enterprises lack the resources that larger organizations possess to dedicate toward improving and maintaining high data quality.
- Maintaining data quality requires a culture that views data quality as an ongoing, iterative process and not merely a one-off project.
- Building a data glossary is a low-cost, high-impact method of maintaining data quality in a centralized location that small enterprise IT shops can leverage. The data glossary serves as a solid stepping stone in the process of building a data-centric mindset amongst stakeholders and end users.
Impact and Result
- Info-Tech’s tailored small enterprise research provides a clear roadmap to help IT leaders better understand the underlying issues from which poor data quality frequently arises.
- The organization is then able to develop a set of short- and long-term initiatives to improve data quality.
This guided implementation is an eight call advisory process.
Guided Implementation #1 - Scoping call to understand the organization’s data quality concerns
Call #1 - Overview of Info-Tech’s applications practice and its services.
Call #2 - Review the blueprint’s structure, outputs, and content.
Call #3 - Determine the most pressing data quality issue.
Call #4 - Establish the desired data quality standard.
Guided Implementation #2 - Create short-term improvement initiatives
Call #1 - Review interview results.
Call #2 - Walk through the process of performing a technical assessment.
Call #3 - Walk through the data assessment scorecard.
Guided Implementation #3 - Review possible long-term improvement strategies
Call #1 - Review long-term data quality improvement strategies.
After each Info-Tech experience, we ask our members to quantify the real time savings, monetary impact, and project improvements our research helped them achieve. See our top member experiences for this Blueprint, and what our clients have to say.