Practicing Data Democratization: What’s Stopping Us?

Image credit: iStockphoto/alphaspirit

If you are a data leader, you will understand the concept of data democratization.

It is the practice of putting digital information in the hands of the average non-technical data user without involving IT. It’s not just data sharing; it takes a step beyond by making the raw numbers and figures palatable for those who have no analytics training.

The concept is now gaining traction because the technology is ready. The advent of new self-service data science tools and visualization advances allows non-data science workers to visualize patterns quickly and make data-driven decisions. The development of data infrastructures enables companies to create data lakes with different data streams, allowing better analysis.

Yet, technology is only half the puzzle. In a virtual roundtable, organized by CDOTrends in partnership with Informatica, IT and data leaders argued that the main hurdles are often not technology-based. Data governance, privacy fears, data trust, and a company’s misgivings about giving data to their employees often stand in the way.

It’s a mindset problem

Jon Teo, healthcare and data governance specialist for APJ at Informatica, started the discussion by pointing out that broader use cases of data analytics require data democratization. Without it, companies are left with limited use cases and being unable to scale them. Eventually, it impacts the return on investment of such projects.

Yet, putting data in the hands of all their users is not something most companies are comfortable with. One participant noted that as some businesses are traditional, people will need to go through a journey of understanding what data means to them and how it applies to their work and their tasks.

The real challenge is not offering all data to their employees either. Instead, it is having the right pieces of data or information flow to the right people when they need it, and when it's usable.

Another participant noted that data democratization comes down to empowering self-service. It is about making sure that there's access to them so that they can do self-service for the insights that they need to be able to support their business.

Using the pharmaceutical industry as an example, the participant observed that data management is changing. 

One significant change is that the data roles are no longer under IT but now support different business lines. This makes it important to have people who are savvy about their data because they're the ones who will make decisions for their business.

It makes data democratization important as the data users are now sitting with the business and need to access the correct research and decision-making data.

Education and data literacy plays a central role

Informatica’s Teo shared a case study about the Bank of Ireland, which rolled out a video for all its employees on the value of data governance and data democratization.

While the video introduced the concept, it also highlighted the need for data literacy and governance. Essentially education can help to break down legacy thinking.

For education to work, you need the right culture. Such a culture will be crucial for companies to maximize data value, said one participant. A data-savvy culture allows Lee’s company to buy external market data and correlate it with internal knowledge and first-party data.

Still, data security and governance fears persist. In highly regulated industries like banking, people can be afraid of data leakage in the cloud. So, making them accept data democratization can be a hard pill to swallow, noted one participant from the banking industry. 

Over time, the hope is that people would learn better data skills and appreciate governance. But this will take time and effort that companies will need to invest in.

Start with the right use cases and data governance

Data democratization is never a means to an end. Informatica’s Teo emphasized that it should be an integral part of a company’s data modernization journey.

However, data democratization's most significant challenge lies in the idea of employee empowerment. The problem is not whether employees are ready but whether companies are prepared to empower them.

It does not help that there is no clear use case of data democratization success, even for those ahead in the game.

For example, one participant from the healthcare sector noted how they embarked on business intelligence to provide information to our line leaders, including heads of departments, etc., to make use of the information to slice and dice to be able to look at improvement programs and enhance their insights.  

To date, the participant noted that they're still struggling to drive data usage among its users because it's not a subject taught well in medical schools until recently.

You’ve no choice but to democratize

Informatica’s Teo acknowledged the various non-technological challenges but noted that companies could not stay on the sidelines.

COVID-19 created a massive gap between information brokers and savvy users and traditional business lines that keep vital information within ranks and departments. 

One participant advised companies to start first with the copious amount of first-party data that many companies already have. Then, to drive data democratization — an effort echoed by Teo’s Bank of Ireland example — they need to start breaking down the silos and mindsets about data sharing.

Companies have a part to play in driving data trust as well if they want data democratization to succeed. Having a solid data governance framework from the onset helps. And here, technology plays a crucial role.

Informatica’s Teo noted that all these concerns do not require rocket science, and the technologies are here. However, it needs companies to start their journey, create the right foundations and governance framework, and look for the right solutions.

Otherwise, they risk being left behind by other competitors who maximize the value of their data, he concluded.

Winston Thomas is the editor-in-chief of CDOTrends, DigitalWorkforceTrends, and DataOpsTrends. He is always curious about all things digital, including new digital business models, the widening impact of AI/ML, unproven singularity theories, proven data science success stories, lurking cybersecurity dangers, and reimagining the digital experience. You can reach him at [email protected].

Image credit: iStockphoto/alphaspirit