High-quality data is among an organization’s most valuable assets. Using it effectively is crucial for corporate sustainability since inaccurate or outdated data can result in misguided decisions. And privacy regulations, such as the California Consumer Privacy Act (CCPA) and EU General Data Protection Regulation (GDPR), demand a firm hold on data security.
Enterprise data governance addresses both data quality and security concerns. Better quality data translates directly into better business intelligence, and ensuring security tools and procedures are followed will mitigate compliance liabilities. This article examines the role of data governance, the challenges involved, and best practices to improve your enterprise data governance strategy.
What is Enterprise Data Governance?
Data governance is the set of internal policies and practices, plus the monitoring and enforcement of those policies and practices, that serve to guide data management across an organization. The goal of data governance is to balance the data needs of people within an organization with data quality and security for compliance.
Challenges for Data Governance
Enterprise data governance isn’t easy, especially with the volume of data coming into organizations from a plethora of sources. Each organization will face its own set of challenges, but several issues are common.
In the past, the enterprise data governance models kept data in the sole domain of data engineers, data analysts, and BI professionals. Data resided in an ivory tower, owned and guarded by those with the knowledge and skills to extract meaning from it. But this model created bottlenecks since data teams can’t possibly keep up with the velocity of ad hoc report requests coming from business teams in today’s fast-paced business environment. As a result, business users rely on spreadsheet extracts, which create both quality and security issues. Extracted data becomes obsolete quickly. And every time data is moved, it becomes vulnerable. Educating teams on healthy data practices will make governance much easier.
But even though self-service analytics has become a goal, a fear remains that if an organization opens up access, security will be lax, permissions will be wide open, and data of questionable quality will get used to make important decisions. Fortunately, modern enterprise BI tools like Sigma offer data governance features that allow companies to centralize data, break down silos, and get data into the hands that need it — without compromising security or quality.
First, people in an organization must recognize the value of data governance to them. Data governance requires participation and compliance, which won’t happen without creating motivation. You must clearly communicate why data governance matters to each team — and why it’s so detrimental to work with low-quality or outdated information or open an organization up to costly security vulnerabilities through the misuse of data.
How Data Governance Impacts the Enterprise
Every team in a company will benefit from data governance. It empowers teams to be more agile, harnessing opportunities and quickly identifying problems before they become significant. When every team is able to securely access insights for daily decision-making and productivity, the organization as a whole improves performance. Let’s look at several examples of how governance benefits various departments.
Sales — For sales teams, it will deliver accurate insight into evolving buyer behavior.
Marketing — For marketing, it will improve market basket analysis with better upsell and cross-sell recommendations.
Finance — For finance, it will enable up-to-date and accurate reporting. For example, Cowen, a diversified financial services firm, implemented effective self-service analytics with governance to support regulatory compliance.
Procurement — For procurement, it will ensure cost optimization based on accurate, real-time data.
Operations — For operations, it will improve AI and automation. See how Metrikus, an information technology and services company, increased operational efficiency using business intelligence driven by enterprise data governance.
7 Best Practices for Data Governance
While each organization will develop its own enterprise data governance framework with tailored systems and processes, there are several best practices that will help with implementation.
- Aim for Quick Wins. Start small to generate momentum. As your people see the impact of small actions, they’ll be more likely to adopt the governance initiative and participate moving forward.
- Identify Roles and Responsibilities. Without assigning ownership, you’ll end up with a lot of finger-pointing. Identify who will be involved, what roles they’ll play, and what their responsibilities will be.
- Develop Standard Definitions. For data governance to work, everyone must be speaking the same language. Centralize data definitions so that everyone can find and understand the data in your data platform or warehouse.
- Map Infrastructure, Architecture, and Tools. You’ll need to be sure your governance strategy fits your enterprise infrastructure, architecture, and tools. Mapping these ensures nothing falls through the cracks.
- Set Goals and Track Progress. Governance doesn’t emerge fully formed upon implementation. Setting goals will help you create a roadmap for achievement. What defines success in each area of your governance strategy? What milestones do you want to hit when? You’ll also need a way to track your progress to celebrate wins and identify what’s next on the agenda.
- Communicate Clearly and Frequently. Every new initiative requires changing habits, helping people learn new things, and redirecting workflows. Communication will help your people overcome these challenges. Err on the side of over-communication when it comes to governance.
- Remember, It’s a Marathon, Not a Sprint. Enterprise data governance isn’t a “set it and forget it” activity. It’s an ongoing program that must stay in focus, with everyone participating. For this reason, approach governance with sustainability in mind, building healthy data habits that become part of your organization’s culture over time.
Enterprise Data Governance for Data-Driven Teams
A customized data governance strategy that balances quality and security with business intelligence needs is much easier than it used to be, thanks to modern tools like Sigma. As your organization establishes an enterprise data governance framework and lives it out on a daily basis, your business intelligence will deliver better decisions, leading to a stronger organization.