How to Build a Data Democratization and Data Governance Strategy

Organizations have access to more data than they ever could have imagined. The digital channels, networks, and IoT devices they use generate rich streams of data that flow freely. Suddenly, there’s pressure to derive valuable insights and not enough resources to manage the increased load.

That’s where data democratization comes into play. Data democratization—the ability for data to be accessible—enables non-specialists to gather and analyze data without outside help. In other words, instead of bottlenecks in the communication and dissemination of data, end-users across all levels of an organization can now have access to the data they need, when they need it.

However, it’s critical that organizations have a thorough and intentional data governance strategy in place to ensure that data stays accurate, reliable, and protected, while equipping all end-users with the support and resources they need to reap the data’s full benefits.

Regardless of Your Strategy, It Must Be Intentional

There’s no right way to go about data democratization. You may choose to have a more liberal, “access for all” approach, or a more conservative approach that more strictly limits who has access and what they have access to. Organization size does impact who owns the content and how you execute—but all businesses, regardless of size, should invest in a data governance strategy. This way, as smaller organizations scale, they have a strong data strategy that grows with them.

Regardless of which method works best for your organization, it’s critical that you have a thoughtful strategy that seeks to prevent and mitigate unexpected roadblocks. For example, consider an organization that overlooks data integrity. They’ll quickly find that once an organization is exposed to flawed data, it’s hard to earn back trust in the data source.

Let’s discuss some key considerations to keep in mind as you navigate the intricacies of data democratization and the data governance that must be in place for the process to be a success.

Get Buy-In from Leadership

Buy-in from upper management is critical. See if you can get someone from your exec team to support your data democratization initiative. This is important to ensure that your approach to democratization aligns with your company’s priorities and strategies. The right individual can also provide significant pull when it comes to securing analytics budget.

So who is ideal for this role? Any sponsor should understand the value of data empowerment, and he/she should have enough influence to support your vision and help eliminate any roadblocks on the path to data diversity.

Create Policies for Data Accessibility

Traditionally, data has been managed and owned by personnel working in IT. Decisions needing data were based on the pace of access, which was usually bottlenecked or delayed. While the ownership of data may remain unchanged, successful data democratization requires universal accessibility throughout the organization.

The company’s BI team can play a crucial role in fostering data accessibility, coordinating with IT to create and deploy policies that take data out of silos and put it into the hands of users. The result? The organization as a whole can respond quickly in situations that require data-driven decision making.

Implement Master Data Management

Data democratization requires verified data accuracy and quality. Otherwise, data programs are rendered useless if users don’t have confidence in the quality of accessible information. MDM (master data management) is a viable solution for maintaining and solving quality-related issues.

For MDM to be a success, your processes, people, and technologies must work together to provide accurate and clean data for decision-making. There should be well-defined processes for maintaining information and datasets for specific attributes. Additionally, roles should be defined for data stewards to act as gatekeepers for any changes to the information. Lastly, technological implementations should be considered for integration, cleaning, and transformation of data.

Don’t Forget Self-Service Analytics

For squeezing maximum benefit out of data democratization, consider empowering your users to not only access data but also to make data reporting and analysis a part of a daily routine. Fostering a culture that facilitates data democratization while enabling self-service can help teams make decisions faster.

To do this, place data at the forefront to ensure that discrepancies in customer journeys are identified and users have a “data-informed” overview of actionable insights. The solution lies in finding a solution that offers out-of-the-box connectivity to reporting and BI tools, lets users evaluate data from previously running legacy systems, as well as allows personnel to easily modify and analyze data.

With all that said, data democratization brings its own set of challenges. The problem lies in the fact that a lot of people aren’t trained in analytics, so they could end up making flawed interpretations that could have negative repercussions down the road. This bottleneck typically leads analysts to clamp down on who can view the data and to what extent it can be viewed. As a result, one bottleneck leads to another, preventing analytics teams from being able to scale and help with the increasing volume of datasets. So, what’s an aspiring data-driven enterprise to do?

Successful Data Democratization Requires Strong Data Governance

You want everyone to be able to access the data they need, but you also don’t want them to do analysis that leads to flawed business decisions. To achieve this, consider implementing a data governance plan that weeds out inefficiencies and boosts accountability within and between business teams. Below are some tips to help get you started.

Elect and Empower Data Natives

It can seem logical to assume that, as the technical lead, a team member with an IT background is a natural fit for a data governance role in the organization. However, this is an association flaw that can devastate the organizations that fall victim to it.

To ensure that the governance and democratization of your data is managed efficiently and strategically, with careful considerations for all of the moving parts, it’s important for initiative leaders to be “data native,” or have existing understanding and expertise in these areas.

This can significantly shorten the learning curve while ensuring that the most pertinent bases are covered and there’s little-to-no room for error. In addition to electing these data experts to lead the initiative, organizations must also empower them to enforce the strategies they’re creating.

Invest in User Training

For a novice end-user, data analytics and visualization tools can be overwhelming. This can result in a two-fold dilemma: the users – and in turn, the organization as a whole – aren’t getting the most from the tools, and a lack of proper training can lead to inaccuracies in activities like writing queries and interpreting data.

To ensure that everyone understands the scope, significance, and processes surrounding the data, invest in systematized, enterprise-wide training. This training should cover the platform’s capabilities, how to navigate it, and step-by-step approaches to entering, accessing, and interpreting data. For an extra level of security, consider creating an internal exam or certification that users must pass or earn in order to have heightened access to the platform.

Create a Clear “User Manual”

The most common paths to flawed data are issues like inconsistencies in tags and definitions. You can reduce or eliminate these other potentially harmful issues by creating a “user manual” or series of resources that clearly outline and document the systems, policies, and procedures around using your organization’s tools. If you have multiple resources, consolidate them into a single database that’s always available for reference.

Creating a clear outline goes hand-in-hand with user training, providing all end-users with the resources and support they need to feel confident in the data, as well as their ability to accurately and efficiently navigate it. The clearer your process surrounding data democratization, the more streamlined your organization’s adoption and ongoing implementation will be.

Implement User Permissions

A key data governance strategy involves ensuring that end-users can only access data that suits their understanding, skills, and need. User permissions allow you to choose these access levels for different end-users in your organization.

For example, admin-level user permissions can allow qualified individuals to capture data, while lower-level permissions can restrict user activity to only consuming reports or looking at content. This minimizes the risk of confidential data getting into the wrong hands, or novice users accidentally compromising the integrity of your organization’s data.

For More Insight

While it’s easy to preach one democratization strategy over the other, the reality is that extremely liberal or conservative views rarely support the vision for company-wide data empowerment. Stakeholders, therefore, need to factor in the pros and cons of every strategy and subsequent measures to determine what approach would be the most beneficial for their companies.

Gain more insight into the current state of data democratization and data governance from this full interview with Heap’s Director of Customer Education, Christy Hollingshead.