In previous articles, we have broken down the modern data management trend of data mesh. This new and disruptive decentralized approach to data management is a popular topic of Gartner and Forrester reports. We have also explained in detail a crucial element of a data mesh approach, the data products. Now we will break down another key element without which, achieving a data mesh is surely impossible, but can also bring many benefits of its own – data democratization.
This is probably the most well-known benefit of data democratization. And the one that remains the driving force behind the trend of widespread education of the workforce about data. By decentralizing data initiatives and allowing business units to solve their own issues on their own at a local scale, your organization’s employees become a powerful force for flexibility, able to quickly and efficiently adapt to many technological challenges that will inevitably come in the following years due to the gradual shortening of the interval between major innovations.
Ever since the speed of innovation outpaced the speed of specialized education, it has been clear that the future of adaptability doesn’t lie in teaching people to use newer and newer technologies but instead in teaching people how to learn on their own, how to self-develop into flexible and adaptable powerhouses of efficiency, and data democratization certainly has a role to play in it.
That data democratization makes data a responsibility of many others outside just the data team is well known. Viewing this trend within the context of a data mesh architecture may highlight a key reason why one should want such a thing. You might think, what good will it bring that HR professionals, business analysts, and other non-technical professions within your ranks now know how to work with data if data isn’t at the core of their jobs?
Well, the fact that data democratization and data mesh bring to light is that just working with data being your job isn’t worth anything if you don’t have a clear understanding of what your business is supposed to gain from the data.
By extending the data proficiency from a centralized data or IT team more broadly to the general workforce of a company without making data the core of their jobs, brings the purpose of data and what actually happens to data into clear alignment. Each non-technical specialist is aware of the results they are supposed to bring, and data can serve as a newfound resource for them to achieve those results more easily and efficiently.
Perhaps the most vocally heard objection to the idea of data democratization and data mesh more broadly is: ”If we let everybody work with data as they see fit, choose their own technologies on a team or even individual level, won’t it result in us having hundreds of mutually incompatible systems, each used by only a small fraction of people? If we don’t have a centrally planned architecture that is generalized enough to support the needs of everyone, is it not going to be utter chaos?” And the answer is: “Probably, yes”.
However, people who use this argument quite often see this as an unavoidable effect of data democratization when it, in fact, is just a symptom of badly handled data democratization. The idea behind data democratization that is so attractive to so many people is that centrally planned, generalized systems tend to be so general in their design to support the data needs of every stakeholder in the company that they tend to make a lot of compromises. That may not sound so bad on paper, but in practice, these compromises often defeat the purpose of why a stakeholder required a data system in the first place.
For example, data that a certain data analytics team needs for their analyses need to contain crucial metadata about references and relationships between attributes and, therefore, would benefit the most from having their data in a graph database. However, the rest of the company needs data structured in clear-cut tables. So, a traditional relational database is implemented in the central system, leaving data analytics without the important context of the information they are getting, and their efficiency and results suffer for it. And by extension, so does the entire company.
To avoid the worst aspects of both centralized and decentralized architectures, it is important to realize why many systems are unable to exchange data with one another by default. There are tools that function as reducers between systems, allowing you to plug all of your many disparate systems in and have them use the framework of such a tool to mitigate your greatest fear of democratization.
As mentioned before, we live in an age where technological breakthroughs come quicker and quicker, one after another, leaving many previous developments in their fields obsolete. Many programming languages and data concepts never got off the ground fast enough before their next-generation replacements were introduced.
Quite similarly, companies across all markets have decided to speed up their race to see who can get more added value from the data they generate. Statista estimates that 328.77 quintillion bytes of data have been created every day so far in 2023. That is already an estimated 23% increase from 2022, and it hasn’t even been half a year yet.
Companies across the globe all try to be those that use their data with the greatest efficiency and achieve the highest degree of data monetization possible. And it is being proved time and time again that in this fast-paced race, centralized data teams are simply falling behind. They cannot keep up with the pressure being put on them by the market as well as every department in their organization. There are simply too few of them compared to the entire company servicing their own needs. In order for your organization to keep up with the competition, you will need to embrace the more flexible and adaptable option.
An opinion you might have read already is that data democratization by itself lowers the costs of maintaining a specialized data or IT team. That assumption is incorrect for two reasons.
First, you don’t go into a data democratization initiative in order to get rid of your data team but to free up their capacity. The reason they are currently underperforming is due to them not being able to handle all of the commercial teams’ requests along with their data management duties.
In fact, a data democratic organization would have a need for even greater specialization of the data team. Granted, they would no longer be in charge of determining what systems are to be used across the entire company, but another crucial task would fall into their responsibility – ensuring the compatibility of systems and visibility of data. They would become the stewards responsible for making sure the architecture works in a way that everyone who needs to work with data can do so and to the maximum possible efficiency.
The second reason is that in order to work, data democratization requires an investment on the company’s part. There are costs associated with training of non-technical personnel to work with data and procuring licenses for tools that allow even little-trained business users to get into complex data management tasks.
This may all sound challenging and intimidating but remember that this investment is a one-off and that there is a huge return on it in terms of continuous operational cost reductions due to gradually increasing efficiency. That is a reward for dedication to long-term transformation.
We have mentioned tools a couple of times in this article. Indeed, there are hundreds of tools on the market claiming to help with bringing about data democratization. So, which are the best? Is there a tool you should purchase that will make your organization data democratic with the click of a few buttons? Well, no. The tools serve a good purpose, but they alone will not make data democratization work.
The true force making data democratization happen is always the people. The concept and its benefits hang on how well can your people not only train to use data but also train to be independent in fighting their own data battles and proactively seeking individualistic solutions to individualistic problems. Data democratization is just as much about internal culture as it is about technology.
If you can ensure people understand the data, their tasks, and responsibilities with them, and most importantly, know how to work transparently together within and across departments to promote openness of information and avoid data silos, then you can bring about true data democratization with all its benefits.
And while there aren’t tools to solve the culture for you, there are tools to make almost each of the steps your people need to take while they learn easier.
For instance, Accurity is a tool that helps business users understand the meaning of data, align it with business KPIs, tie KPIs to specific data locations, and then measure the quality and reliability of data based purely on business merit. A decade ago, something like this would be a gargantuan undertaking that is now incredibly simplified.
Since everyone in centralized data teams is often required to possess extensive technical knowledge, it would be quite natural to assume that if we want the same or similar work to be done by non-technical personnel, we must increase their expertise to the same level.
Logical but imprecise. Many of the jobs your centralized data team has to do require them to have such a high level of expertise due to the wide variety of those jobs. By giving away the responsibility for those jobs to those who are the key beneficiaries and stakeholders of the jobs, their tasks will become much more streamlined, and the spectrum of what they need to know to service themselves will narrow considerably.
Moreover, one of the key tenets of data democratization is allowing the responsible parties as easy access to data and the ability to work with it as possible. And there are many highly specialized tools out there that they can utilize to enable them to do just that and make their learning curve very flat.
As mentioned previously, the fact that your organization’s business units will now be able to sustain themselves in terms of their data requirements doesn’t mean it is time to abolish a centralized data or IT unit. Highly specialized IT personnel are still crucial even if they no longer need to satisfy the many data-related requests of non-technical employees. Their role shifts in a data democratic setup, this time towards enabling the self-service capabilities of the new architecture.
Connectivity of systems, data pipelines, flows, and extractions – that becomes the bread and butter of the data team. In an organization where most know how to work with data and what data they need, all that needs to be centrally ensured is universal access, as well as enforcement of security and privacy policies. When a new data product on a business unit level is created, it must not be hindered by its creator not knowing where to find or how to access the data to feed it. Just like that, it is also unacceptable for the data product to be fed non-anonymized personal data for regulatory reasons.
Data teams will still have their work cut out for them. Only this time, they will not be doing someone else’s job for them.
Data democratization has proven to be a pure-blooded tech trend, at least by the metric of how many misconceptions and generous interpretations of it are out there. What is, however, universally agreed upon is that data democratization opens the door for more business-aligned IT solutions, data democratization is becoming widely adopted, and there are tools that make data democratization a much less intimidating challenge. With regard to that last point, we believe we can truly help your organization get on track toward a transformation into a data-democratic powerhouse.
The Accurity data governance platform gives full control of data management to business users. It lets non-technical personnel decide what data should be kept, where to keep it, for what purpose, and how to measure its correctness and accuracy.
If you think your organization could benefit from having its data initiatives aligned with its business plan, let us know. We can show you what steps you can take in this direction and guide you from start to finish toward data democracy. Schedule a demo.