How has the recent turmoil within the OpenAI offices changed your plans to use GPT in a business process or product in 2024?
Increased uncertainty means we are more likely to evaluate alternative AI chatbots and LLMs.
No change in plans, though we will keep an eye on the situation.
With Sam Altman back in charge, we are more likely to go all-in with GPT and LLMs.
What recent turmoil?

How Enterprises Can Democratize Their Data

Data democratization is the process of increasing data accessibility and eliminating the bottlenecks that stand in the way of that access.
Apr 22nd, 2022 10:00am by
Featued image for: How Enterprises Can Democratize Their Data
Feature image via Pixabay. 

Andrey Koptelov
Andrey Koptelov is an Innovation Analyst at Itransition, a custom software development company headquartered in Denver. With a profound experience in IT, he writes about new disruptive technologies and innovations.

In our times of uncertainty, when market conditions and customer behavior are changing drastically, enterprises have to adapt to survive. Obviously, this is impossible without data management. Only those companies that gather and analyze data can get a complete view of their business and make viable decisions in order to stay competitive and profitable.

To be able to collect large volumes of data and transform it into valuable insights, enterprise managers have continuously expanded their IT departments and adopted sophisticated analytical tools. Unfortunately, this shift is not always easy on many business units, such as marketing, sales, and customer support, which often cannot access the data they need without the help of IT experts. As a result, teams often discover new business opportunities and challenges with delays, which negatively impacts business flexibility and competitiveness.

At Itransition, we believe that data democratization is one of the most expeditious ways to overcome the dependence of business-focused departments on IT specialists. This article will discuss the meaning of data democratization, describe its benefits, and provide some practical tips.

The Meaning of Data Democratization

In short, data democratization is the process of increasing data accessibility and eliminating the bottlenecks that stand in the way of that access. Its purpose is to allow non-specialists to obtain data and analyze it independently, without any intermediaries. In practice, this may provide enterprises with multiple business advantages.

Firstly, the more diverse specialists can access the data, the more insights a team can generate. Thus, an enterprise can become more competitive; after all, teams with quick data access can exploit business opportunities or predict critical trends faster than their competitors. Second, data democratization can help enterprise managers improve performance across multiple departments. If managers can easily access relevant data, they can quickly gain insights to eliminate inefficiencies and streamline workflows.

Despite all of these benefits, however, data democratization is a challenging task. Some enterprise managers may remain concerned that non-specialists may misinterpret the data, leading to erroneous conclusions and business decisions. Besides, the more users have access to corporate data, the more risks associated with cybersecurity may occur. Fortunately, enterprise managers can avoid all these issues and mitigate risks if they choose the right approach to data democratization. Here are some recommendations that might come in handy.

How to Democratize Corporate Data

Auditing Data

As we mentioned, data democratization is often a challenging and complex procedure. To make it as smooth and quick as possible, enterprise managers should start with data audit. With its help, managers can learn how team members are currently working with data, understand if data accessibility can be improved, and also define specific technologies that can facilitate data management and analysis.

While the specific steps towards democratization will largely depend on the results of data audit and the requirements of a particular team, some technologies can enable enterprises to make data more accessible to non-specialists in any case, as described below.

Data Virtualization

Data virtualization software pulls data from various sources and processes it without requiring such technical details as its location or format. Enterprises can implement these solutions to enable team members to access relevant information without manually searching, moving, or copying data, by obtaining it via in-built dashboards and visualization tools.

Self-Service BI

While traditional BI software requires the involvement of IT specialists to analyze data and control its quality, self-service BI solutions enable even non-technical users to operate data. Thus, a company can reach two goals at once: non-technical users can independently analyze data and generate insights, and IT experts can utilize their skills to perform more complex and challenging tasks (such as data mining or data modeling).

Migration to the Cloud

For enterprises, moving to the cloud is a natural step towards data democratization. As the cloud technology itself is very flexible, when using it for storing data, enterprises make computing capabilities available to all team members and can quickly scale on demand if necessary. So, given that employees can access a cloud-based data solution from any device, they can make data-driven decisions anytime, anywhere.

Final Thoughts

Enterprises depend on data much more than a few years ago, so it’s not surprising they now strive to collect and process as much of it as possible. However, the increased complexity of data management leads to situations when independent data analysis becomes almost unavailable for non-techies who populate departments like sales, marketing, and customer support. As a result, the decision-making process becomes slower while teams are getting less productive and competitive.

To address this challenge, enterprises can democratize their data and enable employees from different departments to analyze and interpret data unaided so that team members can react quicker.

To start with, companies can run data audit to get a complete picture of their workflows and see how they can be facilitated. After that, they can implement solutions for data virtualization and cloud-based self-service BI that will enable teams to access and analyze data quickly and easily.

Group Created with Sketch.
THE NEW STACK UPDATE A newsletter digest of the week’s most important stories & analyses.