Improve Your Data Governance Strategies to Scale Digital Transformation

Reading Time: 2 minutes

Your organization faces several challenges on its journey to successful digital transformation. Your key stumbling block is not data but the inability to make it actionable via data governance. How can you use data and analytics governance to help achieve both enterprise and business goals? Keep reading for advice on the matter from industry analysts.  

Why Do You Need Data Governance?

Data governance allows you to manage all of your business artifacts—such as business glossaries, policies, business rules, dictionaries, KPIs, and data sources all in one centralized domain. By improving your governance strategies, you can increase the efficiency in how your stakeholders collaborate internally and externally as well as enforce data quality throughout key assets.

Gartner Data Governance Strategy Recommendations

According to a 2021 Gartner® D&A governance survey, “61 percent of respondents said their governance objectives included optimization of data for business processes and productivity, but only 42 percent of that group believed they were on track to meet that goal.”

Data governance across disconnected information silos remains problematic because few organizations have developed a data management strategy that could create the ever-elusive single source of truth they envision. 

Without proper data governance, you face a lack of operational ROI from your hefty data and analytics investments. Year after year, as access to accurate and quality analytics is growing in importance, the need for these core strategies in your team cannot be ignored. 

Does Your Data Governance Strategy Connect to Key Operational and Strategic Goals?

Your digital investments will not bear fruit without a considered data management strategy to coordinate organizational efforts. Gartner analysts recommend your leadership team can:

  • Explore how data and analytics governance platforms can help achieve both enterprise-wide and business-domain goals and identify the decision point for your organization concerning investment in such capabilities
  • Establish more effective enterprise data sharing for the data you collect, use, and share by introducing independent, trust-based mechanisms for data, metadata, and data sources
  • Examine how synthetically generated data could be used in your AI development and evaluate how it could be applied to AI capabilities in both internally developed and purchased applications
  • Focus data and analytics governance on achieving specific business outcomes and measure your governance success by improvements in KPIs
  • Shut down large-scale, all-inclusive data governance councils that result in much talk but little action, and use your data and analytics governance initiative to mobilize key business leaders who impact business outcomes

Ease Your Data Challenges with TIBCO

Connecting core strategies with data and analytics is the key point behind digital transformation. For organizations that find it increasingly difficult to effectively manage their enterprise reporting and operational needs due to poor data quality, TIBCO® DQ helps by automating tasks, reducing resource effort, and increasing operational efficiency. With TIBCO® DQ software, users can quickly provide value and produce clean, harmonized, and nonredundant data that can be confidently used to discover actionable insights. 

Unlike other solutions, the TIBCO® DQ offering is part of a larger modular suite able to answer all your data needs, including master data management and data virtualization. It’s a highly capable solution you can rely on to reduce risk and ensure your data is fit for purpose and compliant for optimal decision-making across your organization.

To learn more about the best practices, tools, and strategies regarding data quality management, download our free TIBCO® DQ software complimentary guide on our website. 

For further questions, contact our team.