Data democratization is being labeled as one of the most attractive trends in data science and data management for the upcoming years. It’s been raising hype for quite some time and it’s not slowing down. As companies face more and more data, they need effective ways of handling it, but at the same time, they need to give their employees access to it. Long gone are the days when the IT department was the only one with access to important data. With how fast the market and business environments change, on-time responses and actions are vital to staying on top of things.
So what is data democratization? Simply put, it means that everybody has the access to data they need, relevant to their role in the company. Its main purpose is to allow users, or employees, in this case, to use data for drawing insights and metrics much needed to form decisions. Data democratization implies that users need to be educated on how to work with data and that data literacy is a top priority. What’s important is to cut out the middleman, the IT, so information can move faster and new opportunities can be spotted more easily. This is where self-service analytics come into play.
Why is it a good thing?
There are vast benefits when it comes to data democratization and each one meets a rise in importance.
Employees empowerment & better collaboration
By giving employees, on all levels, access to data, companies empower them to make decisions that matter. They get a sense of a collaborative environment that focuses on the team. If employees can analyze and use data on their own, they can upgrade their skills and communicate better with others across different departments and teams. It enables knowledge sharing among employees and drives innovation. With more freedom in data handling, employees get a greater sense of purpose.
If employees don’t have to go through the IT department each time they need access to some data, they can save time immensely. If users get instant access to insights and metrics, they can make decisions faster and more accurately. Information flow is more efficient and reaction time is reduced.
Faster decision-making and cutting out the hierarchy in data accessibility, lower cost in the long term. Business operations and people are more effective, and with data in their hands, they more easily spot areas where costs can be reduced and revenue increased.
Data democratization provides more agility to business operations. By spreading data through all hierarchical levels, cooperation is more fluid. Reactions to changes are quicker and users are more adaptable to certain micro and macro influences since they don’t have to wait to analyze much-needed data or information. There is no rigorous structure regarding data access and teams can be more agile in their work.
If more people have the skills and knowledge to analyze data, there are more eyes that can spot opportunities or threats, for that matter. Faster data accessibility means that certain tasks are performed more quickly. Employees perform better since they have information at their fingertips. Certain business operations can be sped up and done better.
Amplified data-driven culture
Data literacy is an important aspect of data democratization. If all employees get skilled in data management and analysis, it can promote data-driven culture and performance based on data. If all employees understand data and how to utilize it, then they’ll more confidently explore data and convey findings between departments or across teams.
When data democratization goes wrong
Even though data democratization has a lot of benefits, there are always some downfalls. Especially, if the company hasn’t prepared itself correctly for data democratization implementation. There will always be a level of mistrust in giving everyone access to data. And if not implemented correctly, it can cause quite a stir in the company.
If everyone gets access to data, then how can data privacy be enforced? What if someone unintentionally misuses data and breaks privacy regulations and laws? This is a valid issue because we all know mistakes happen. Data leaks can slow down or even endanger business operations.
Data silos are still an issue when data is not centralized or organized in a way that it can’t be duplicated or found across various databases and in different formats. If the initial setup doesn’t support a single source of data, then this can prove to be complicated and difficult in the long run. If each department has or creates its own source of data and isolates it from the rest of the organization, then data democratization can’t be integrated fully.
There has to be a certain level of trust that employees or users won’t misuse data to their or someone else’s advantage. Companies generate or collect sensitive data that has to be handled carefully and in line with regulations. Fraud and risky activities can easily damage not only private data and business, but their reputation as well.
Misrepresentation or misinterpretation of data
One of the biggest challenges in data democratization is that different users will differently interpret data and the information it provides. Often the same piece of information can be shown in different graphs like in the example below. It’s the same data, the only difference is in how an axis is numbered or labeled. A different interpretation caused by different representations can lead to wrong conclusions and insights. Misinterpretations can lead to instability, costs, and loss if the decision, based on inaccurately presented data, was the wrong one.
Image 1: Example of the same data visualized in different graphs
Cost of democratizing data
Some might get discouraged in implementing data democratization because of the initial cost. You have to educate your employees about data, how to utilize it, and how to work with analytics tools. Amplifying data literacy comes at a cost and initial technological infrastructure comes at a price as well.
Data democratization is a continuous process that doesn’t stop once you give employees access to data. It’s a process of ongoing data literacy education and data management so it serves everyone in the organization. Achieving perfect data knowledge and confidence doesn’t come easily and it will always have some risks attached to it. But, benefits can surpass those risks and lead businesses to higher operational efficiency and bigger ROI in the long run.
What makes a difference is how the company approached data democratization integration and what were the initial goals. Only through structured and organized data democratization processes and data management optimization can businesses achieve their full potential and minimize risks.