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Support data governance beyond IT with these effective tools


Strong data governance requires buy-in from the top down, along with tools that empower multi-disciplinary teams to use data effectively.

While 98% of organizations recognize the importance of data governance, just 12% of them have fully embraced governance programs.

This isn’t an IT problem. Strong data governance is bigger than IT. It requires buy-in from the top down, along with tools and strategies that empower multi-disciplinary teams to use data effectively.

Learn the common barriers to strong data governance and find recommended tools and strategies designed to foster data competency throughout your organization.

5 common barriers to widespread data competency

To promote data stewardship, you need a sound architecture. Several common barriers that prevent organizations from effectively managing and securing their data are:

1. Data silos

The average organization has 23 separate data silos. Each requires its own governance policies, security protocols, and life-cycle management strategies.

Having this many redundancies complicates data sharing and management. It stalls the flow of information and makes cohesive data governance an uphill battle.

2. Poor data quality

Dataversity found that 58% of organizations struggle with assessing data quality. This should be a foundational goal for all businesses — valuable insights are impossible with poor-quality data. Garbage in, garbage out.

3. Not enough data

There’s no silver bullet for achieving data management maturity. However, more data helps — an IDC report found that “leading innovators have two to six times the data of their peer groups.”

4. Data sprawl

Data security hinges on knowing its origin, location, access, use, and deletion protocols. With this level of complexity, it’s no surprise that data sprawl is a problem for 80% of IT leaders, according to IDC.

Scattered data creates many headaches. It needs to be wrangled from different sources, cleaned, and put into a standard format. Without a single source of data truth, meaningful analysis becomes much harder.

Related: How to avoid SaaS data fragmentation

5. Lack of a future-ready framework

IDC expects that as many applications will be deployed between 2020 and 2025 “as have been deployed in the previous 40 years.”

As data complexity grows, so does the need for well-built architectures that everyone in the organization understands.

Streamlining data governance and management: tools and techniques

An IDC report found several benefits tied to mature data management practices:

  • 24% higher staff productivity
  • 59% less unplanned downtime
  • 90% lower compliance fines

These benefits are significant but only enjoyed by a select few. The same report found that around half of organizations “believe they derive less than half of the potential value from their data due to data management deficiencies.”

The solution? Tools and strategies that cut across all levels of the organization, demystifying data management. As noted by Forrester, organizations are making progress on data governance by “activating strategic and unified data, analytics, and data governance competency centers.”

Essential tools for data governance and management

Here are some of the tools and techniques you should consider:

Data quality management tools

Dataversity found that more than half of organizations have deployed data quality management tools to guarantee data accuracy and consistency. They play a critical role in establishing trust in insights derived from data.

Metadata management tools

With unstructured data representing an increasing share of an organization’s data stack, metadata management tools have become indispensable. They act as a detailed map, streamlining the discovery process by helping users easily locate and utilize relevant data.

Felipe Santos, senior data engineer at Lumenalta, highlights that “a metadata approach empowers organizations to unlock the full potential of their data. This translates to improved data security, governance, and disaster recovery capabilities, regardless of where the data resides.”

Data cataloging system

Imagine a library without its catalog system. Finding the book you’re looking for would take hours.

The same principle applies to organizational data. Data cataloging tools enable users across an organization to easily find and use information. This boosts the value of an organization’s data immensely.

Unified data governance solution

Non-IT users won’t use data management tools unless they’re easy to use. A unified, user-friendly data governance solution cuts through the complexity of managing data across platforms. This boosts adoption rates across the organization.

IDC found that “leading innovators are…frequently organized around one centralized group for data management and 86% have already invested in a single unified…system for the control and management of data.”

Tools for end-to-end data lineage

62% of respondents to an IDC survey pointed to “documenting complete data lineage” as their top bottleneck to improving enterprise data management. 

Employing tools that provide end-to-end data lineage offers transparency into the data’s evolution, usage, and transformation. This visibility is essential for compliance, security and for users to trust the data they’re working with.

Techniques to enhance data governance

Data literacy improvement

Many organizations neglect the importance of data literacy. Just 14% of respondents to a recent survey said it was a top driver of their data stewardship program.

Fostering a data-driven culture is a great way to promote data literacy. Giving business users the right tools enables them to discover firsthand the power of data in their roles.

Stakeholder engagement and management

Stakeholders in data governance encompass a broad spectrum. From influencers and operational staff to compliance experts and data consumers, each group brings unique perspectives and goals to the table.

Not every stakeholder group needs to be represented in every data stewardship initiative. However, organizations do need to take the time to identify which stakeholders are required for a particular initiative and design it according to their needs.

Automate key data operations

Organizations with immature data management tend to “procrastinate in automating [data] processes and therefore aren’t positioned to achieve data governance and intelligence at speed or scale,” according to Dataversity.

Automating data operations — namely, harvesting, mapping, and cataloging — shouldn’t be put on the back burner. It drastically reduces manual effort for both IT and business users.

Related: Is your company AI ready?

The path forward for enterprise data management

Strong data governance is built from the ground up. Organizations that think governance is IT’s job need a shift in perspective — everyone needs to be along for the ride.

The obstacles of data sprawl and departmental silos underline the critical need for tools and strategies that connect IT with the broader organization. By simplifying data stewardship and fostering data literacy, these approaches streamline the management and use of data at all levels.

At Lumenalta, we’re dedicated to helping organizations reach data management maturity. Let’s maximize the value of your data together — reach out to us and we’ll talk.

Read next: The true cost of your data, beyond server costs

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