As data democratization becomes more imperative to modern collaboration, its implementation for enterprises is often oversimplified.
There are key benefits that data democratization can bring for enterprises. Understanding what data democratization is, its benefits, industry trends, as well as key strategies will provide more clarity for enterprises moving forward.
What is Data Democratization?
Data democratization refers to the accessibility of data throughout all departments of a business. Historically, IT departments had access to data and were gatekeepers for any marketer, analyst, or business leader in need of said data.
The adoption of data democratization has come in parallel with the rise of low-code solutions and software such as customer data platforms (CDPs). It shares many similarities with the concept of DevOps, . which aims to bridge the communication gap between development and IT operations.
Data Democratization Benefits
There are a number of benefits the implementation of data democratization can provide for enterprises. It’s important to identify which benefits are most valuable for your enterprise.
- Customer Intent
As more artificial intelligence (AI) tools are being adopted by enterprises in their respective digital transformations, customer intent is becoming easier to identify.
Congruent to this change, data democratization can provide a wider breadth of customer intent. This is because data is being analyzed and leveraged by multiple departments, all with different philosophies and approaches.
Ultimately, this benefit is reliant on a company culture that allows different departments to experiment and approach this data with their unique skill sets.
Tools such as AI analytics and cybersecurity software are built on data democratization. As enterprises continue to adopt these tools to house their data in a single and accessible location, the efficiency these individual tools bring is engrained in the company’s operations.
On a wider scale, data democratization is built on enterprise departments genuinely understanding the data they have access to. This allows your development team to truly grasp the issues various internal departments are facing. This minimizes confusion and builds efficiency.
- Customer Experience
Because data democratization brings a wider scope of customer intent as well as greater operations efficiency, customer experience is naturally improved.
An actionable example of this is customer-facing departments having access to preferred contact and previous shopping data. This allows your sales team to provide tailored customer experiences and service.
Data Democratization Industry Trends
There are three main trends that data democratization could usher in for enterprises. These include the increase of low-code solutions, the transformation of customer-facing roles, and employee upskilling.
Because many of the software solutions enterprises are adopting are built on data democratization, their interfaces and operation require little to no development experience. Many of these solutions are considered “low-code.”
Low-code solutions are user-friendly solutions that present data sets and application creation capabilities to the everyday user. Although developer tools are still offered in low-code solutions, their usability will surely be leveraged parallel to the rise of data democratization. Paired with the growth of various technologies such as AIOps and IT automation software, expect to see a rise in these types of solutions.
As previously mentioned, data democratization can shape the way customer-facing roles such as help desk employees and sales teams approach their customer experience.
Having vital information about a customer, such as their preferred contact method or whether they’ve submitted a ticket before, can transform the ideal customer experience altogether. ata democratization can also ensure multiple facets of your organization are sharing their vision of what the ideal user journey could look like. Data democratization opens up new doors for iterating on customer experience as a whole.
Finally, especially with the rise of hyperautomation and digital transformation, expect to see upskilling across enterprise employees. Employees will need to learn new tools that assist them in both their individual job requirements as well as interdepartmental collaboration. Again, this can be seen through the rise of low-code solutions, as previously mentioned above.
Also read: Bringing Hyperautomation to ITOps
Data Democratization Key Strategies
- Company Culture
Much like any other digital transformation, enterprise company culture must advocate for data democratization and cultivate a space where employees can collaborate.
Employees naturally being upskilled due to new technologies and AI solutions could make fostering this type of culture easier to accomplish. Furthermore, employees should feel they are in an environment where they are learning the full impact of the data sets they are working with, as well as the various applications of said data.
Moving forward, users with little to absolutely no data analytics experience will grow more confident with their findings and contribute to enterprises in ways never before seen. Fostering a company culture that upholds this future is a vital first step in any enterprise’s strategy.
- Establish Stakeholders
Although access and understanding will be open to all with data democratization, key stakeholders and leaders need to be established throughout your enterprise to make strategic decisions.
This is where a company’s DevOps and AIOps strategies will truly come to fruition. Are there key stakeholders overseeing relevant processes in your data democratization strategy? Enterprises will find that cases will differ, but having effective DevOps at the core of your business could significantly help with this strategy.
- Uphold Communication
One of the primary concerns of data democratization is misinterpretation and communication of data. Although fostering a company culture that helps teams understand the data they have access to can help, interdepartmental communication still must be at the forefront of any data democratization strategy.
Teams must uphold communication and share their interpretations about data sets to gain a multifaceted view. Your data-based strategy might make sense until the IT department and customer-facing team suggest counterpoints or their own vision.
Much like when you’re establishing key stakeholders, companies with robust DevOps strategies will find more success in this step than others. In many ways, data democratization could be considered a natural progression from DevOps. This will be accelerated even more so by the rise of AIOps technologies in the near future.
- Don’t Over Rely on Solutions
Data democratization is exciting. So are the growing number of solutions dedicated to it. However, solutions should never act as replacements for your responsibilities.
Think of AIOps, cybersecurity, and analytics tools as helpful assistants that can store data in an easily manageable and accessible manner. They can even provide insights from highly advanced machine learning and AI technology.
Ultimately, however, human analysis is essential to any data democratization strategy. The basis of it relies on the various interpretations different departments in enterprises can extrapolate. Solutions can be of great assistance to this, but should never act as an “end all, be all.”
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