Shift governance and data management to enable, not restrict, your organization

Did you know 80% of data-driven businesses said they gained a critical advantage during the pandemic? Having complete, accurate data in all employees’ hands and workstreams helps organizations solve business problems with the customer journey in mind—especially in rapidly changing markets. With organizations accelerating to digital business practices, data is the key to transformation. But most organizations still struggle to achieve data and analytics at scale—and governance is the most foundational challenge to overcome. 

IT faces hurdles in equipping people with the necessary insights to solve strategic problems quickly and act in their customers’ best interests; likewise, business units can struggle to find the right data when it’s needed most. Typically, enterprises face governance challenges like these:

• Disconnected data silos and legacy tools make it hard for people to find and securely access the data they need for making decisions quickly and confidently.
• Data management processes are not integrated into workflows, making data and analytics more challenging to scale.
• Evolving regulations make it challenging to maintain business agility alongside compliance, risk, and policy requirements.

As the stewards of the business, IT is uniquely positioned to lead organizational transformation by delivering governed data access and analytics that people love to use. IT also is the change agent fostering an enterprise-wide culture that prizes data for the impact it makes as the basis for all informed decision-making. Culture change can be hard, but with a flexible data governance framework, platform, and tools to power digital transformation, you can accelerate business growth. Let’s start with how governance helps employees use data responsibly. 

Bring your governance and data management practices out of the past

Visual analytics and BI platforms today have shifted IT’s role from building reports to maintaining and securing the systems that increase data self-sufficiency. IT is implementing governance strategies to create guardrails to data and analytics exploration, rather than restricting access and causing bottlenecks. There are three areas to consider as you create a holistic approach to address governance: data access, quality, and scalability. Take steps in these areas to reduce chasing one-off issues and overcome organizational challenges.

1. Access: Securely connect people to the data they need

To enable success from anywhere, IT must meet compliance, cybersecurity, and governance protocols while making data access seamless and simple for users. Flexible controls will help IT customize access to meet unique requirements across teams, use cases, and user skill levels.

Choosing an analytics platform that integrates with your existing solutions for identity and access management will also help streamline the authentication process for users while maintaining security down to the row level.

2. Quality: Ensure and communicate trusted data

Self-service relies on maintaining quality data that people can trust. Establishing repeatable processes to prepare data, build data models, publish, and certify them ensures that your data is ready for analysis and trusted for decision-making.

Analytics solutions with an integrated data catalog can bring metadata directly to people in their analytics workflows so they understand more about the data and its quality before making decisions with it. This increases the discoverability of data, helps people know to trust it, and can extend the value of your existing data management solutions.

Should data tables or calculations change, IT can perform impact analysis to understand which data assets and people will be affected downstream, and then inform them. Business users should also be able to see the lineage of data they are using for analysis, including the origin and owner of the data, whether or not it’s certified, and other important details of the data’s history—all before opening a dashboard.

3. Scalability: Automate and monitor your governed data environment

Scaling self-service analytics to a broader audience also demands that IT operationalize and automate processes. Operationalizing and automating data flows helps ensure access to the latest clean data, while making it easier to track and manage everything you’re bringing into your analytics platform.

Additionally, monitoring data usage to get greater visibility into usage—who is accessing what data and how often—also helps to inform and iterate on governance as adoption grows and business requirements change. Finally, as your environment grows and people increase their analytical skills, delegating some of the administrative responsibilities to advanced users will help reduce bottlenecks as you scale.

Implement a proven governance framework—and iterate

With effective data governance, people trust analytics, systems, and processes to make data-driven decisions. Governance with integrated data management provides secure access, so IT can effectively manage the proliferation of data sources and analytical content, while meeting compliance, risk, and policy requirements. Line-of-business employees can quickly find the data they need and feel confident with self-service analytics. 

It’s important to remember that governance is not a destination, but a journey of iteration. As teams increasingly rely on data to inform business decision-making, it’s critical that people, process, and technology work in unison to address the evolving needs fueling a strong Data Culture. You are the change agent and can ultimately shift the perception that governance is empowering the organization, not restricting it. 

If you want to learn more about governance in Tableau, check out our governance ebook. 

Editor's note: This article originally appeared on CIO.com.