You know by now that we say “data is beautiful” all the time at Funnel – but today we’re changing the record, because data democratization is beautiful, too.
Democratization is an essential part of our digital lives today. Access to the internet gives us a democratization of knowledge. Social funding and investment apps democratize money. And in business, our data-driven world means data democratization is vital.
A quick Google search for "data democratization" will lead you to dozens of in-depth resources, all focusing on better data access. But the concept of data democratization involves much more than just opening the data floodgates. It’s an ongoing process that enables and empowers everyone to work with data in a way that leads to better decision-making and a more optimal customer experience.
So, while a data democracy may seem complex and overwhelming, especially among marketers with little data analysis experience, data democratization becomes second nature with the right mentality, tools, and cultural shift.
What is data democratization?
The core concept of democratization is about breaking down elitism and empowering a wider group of people to participate in something that was previously exclusive. It's a way to create a more level playing field and foster a more inclusive environment.
Data democratization is the process by which organizations not only make data accessible to all stakeholders and employees, but also help them understand what it means and how to use it – regardless of their background. This approach is entirely different from the historical approaches. Before data democratization was widespread, IT teams were the ones who owned and reported most (if not all) of the company's data. Teams would waste time requesting data and waiting for approval to use it. And even when they did have access, it was challenging to make sense of it.
In many companies, only top-level executives can access and utilize the company's data, as the BI teams prioritize serving them over lower authority colleagues. However, this elitist approach prevents other teams in the company from learning and putting the data to good use, resulting in missed opportunities.
Restricting data vs democratizing data: which is best?
Data democratization seems like a no-brainer, but some businesses choose to restrict data access for various reasons. Let’s look at the pros and cons of both data restriction and data democratization.
Data restriction:
Ensures data security: Opening up data access increases the number of potential entry points for security breaches or data leaks. Businesses need robust security measures and data governance policies to ensure sensitive information is protected.
Limits data misuse or misinterpretation: When data is widely accessible, there's a risk of people misinterpreting or misusing it. Those without a strong data analysis background might draw incorrect conclusions or overlook crucial details. This could lead to poor decision-making, skewed conclusions or wasted resources.
Avoids information overload: With more data readily available, employees can become overwhelmed. Data restriction means there’s less need to implement clear data filtering and visualization techniques to present information in a way that's easy to understand and act upon.
Reduces data quality issues: Data restriction can enhance data quality. When multiple users are generating and manipulating data, inconsistencies or errors can creep in more easily.
Can reduce time investment into educating and reviewing skills: Simply providing access to data doesn't guarantee everyone can use it effectively. Businesses might need to invest in data literacy training to ensure employees have the skills to understand, analyze, and interpret data correctly.
Data democratization:
Faster decision-making: When data is siloed and restricted to a limited group (often data scientists or IT), it creates a bottleneck for accessing insights. Freeing this up speeds up decision-making processes, especially for time-sensitive issues.
More innovation: Data is the fuel for innovation. When access is restricted, it stifles creative problem-solving and the exploration of new ideas. Employees with valuable insights from data can contribute to brainstorming or developing innovative solutions.
Better communication and collaboration: Working with up-to-date data and sharing insights mean teams can collaborate on shared goals. Good data literacy means more engagement cross-department.
Increased value: Investments like data collection and storage are worth more when more people can use their data.
More agile: Moving with the times means your business and teams are more agile and better prepared for data-driven future opportunities.
The greatest issue with restricting data access is that it stops companies from using data-driven processes across the entire organization. When company data is siloed, its value is lower. In contrast, data democratization and data literacy allows people without tech expertise to access data and analyze it without the support of data experts, like data scientists or data analysts.
Marketing professionals have struggled with data problems for years. Some of the most common issues include:
- No data access
- Siloed data
- Unusable raw data
- Scattered data
- Lack of data skills
An insight that comes too late is a common, frustrating problem. If there is relevant data, but marketers don't have access or need to wait for approval, it will take increasingly longer to make critical connections and leverage that data to drive higher conversions and better ROI.
Data democratization has many benefits, but that doesn't mean that it's risk-free. Some leaders worry about data security related to data misuse, especially when companies hold sensitive personal data. Creating a strategy that makes the most sense for your organization is also crucial. Should everyone have access to all data, and what will that mean for security, privacy, automation, and scalability?
The importance of data democratization in modern businesses
Whether your goal is greater efficiency, profitability, or growth, data democratization can help. For example, marketing teams could access sales data to test different campaign variations. The results can help them better understand which option will reach their target audience most efficiently.
Sales reps could also leverage data to understand the most valuable opportunities in their pipeline, working with the marketing team to boost revenue. The possibilities continue to expand as you consistently centralize your data.
While data democratization serves different purposes based on varying departments, some company-wide advantages stand out.
- Informed decision-making — Data democratization helps break down data silos, allowing everyone in the company to be an analyst. For example, digital marketers could access the data they need to ensure common audience definitions across the entire team. Each team member can then utilize audience definitions to ensure they meet consumer expectations.
- Empowerment and innovation — When employees have access to data, solid data literacy, and are encouraged to use it, this can spark confidence and innovation. For example, without gatekeepers preventing marketing professionals from accessing product and customer data, they can make time-sensitive, data-driven decisions that allow the right message to reach the right person at the right time.
- Increased collaboration — When data is no longer siloed, marketing teams can communicate with the sales team and vice versa. For example, marketing teams can analyze past data to develop personalized marketing campaigns to attract target customers, working alongside the sales team to improve revenue. By creating cross-functional teams within the organization, you'll experience better insights in less time, resulting in more revenue and a healthier bottom line.
- Competitive advantage — Companies with a better understanding of the market (both the customer and the competitive landscape) can create products with a better product-market fit. This understanding of the market can be realized from data.
The benefits of a data democracy
The role of data access in data democratization
The concept of data access sounds simple enough, but there's more to data democratization than simply providing access to data. You'll need to invest in data literacy and generate actionable insights to move forward. This helps marketing teams transition from being data-driven to insights-driven.
But how?
Offering access to company data, whether raw in a data warehouse or perfectly organized in a marketing data hub, is just the beginning. And even when you want to grant access, it's not always a straightforward journey. You will likely face significant challenges.
One of the greatest hurdles in providing universal data accessibility is the requirement of a cultural shift. An organization can offer access to data, but the advantages of data access can fall flat when employees don't feel comfortable using it, lack the tools they need to make sense of it, or aren't empowered to make data-driven decisions.
Another challenge is making sure you create a robust data governance framework.
Despite these hurdles, when organizations have the right leaders, level of education in data literacy, and tools, non-technical users across marketing and sales departments can discover incredible opportunities.
Solutions and best practices for improving data access
Providing complete data access isn't as simple as the flick of a switch — well, not if you strive to make the most of your data democratization strategy.
To enable data democratization in a smart way, consider the following:
- Invest in the right tools — Providing access to data isn't enough if employees don't know what to do with it or don't feel confident in their ability to understand it. The data presented to them must be easy to find, comprehend, and analyze. Some platforms allow users to collect data from various channels and platforms, providing a more unified view. This presentation allows non-technical teams to find patterns and trends.
- Establish a data literacy culture — This best practice reverts to empowering every team to extract insights from available data. When an organization prioritizes data literacy, this will help marketing professionals incorporate data analytics into everyday operations.
- Create policies surrounding data credibility and quality — When there are concerns about non-technical users modifying or deleting data, you must create clear policies and update them regularly. These policies should highlight authentication, authorization, and documentation measures. Once teams gain a deeper understanding of existing data assets, turn your attention to proactively managing the quality of your data. Focus on accuracy, consistency, and the importance of complete data sets.
Now you understand the benefits of data democratization, here’s how to put it into practice.
Are data warehouses the solution?
Data warehouses are systems that pull data from various sources within an organization to allow for better reporting and decision-making. Some leading solution providers today are Snowflake, Amazon Redshift, and Oracle, all of which help amplify business intelligence.
Under the right circumstances, data warehouses offer many advantages, including easy integration and data consolidation. These warehouses provide a single source of truth, storing and organizing data from marketing platforms, analytics tools, websites, and your CRM.
The disadvantage with data warehouses, however, is that they often unnecessarily confine useful information, creating issues for non-technical users and making true data democratization within an organization harder to achieve.
Related: What is a data warehouse?
Pros of data warehouses
- Centralizing of data
- Data governance is possible
Cons of data warehouses
- Technical barriers for non-technical users
- Scalability and performance issues
Alternative solution for data storage and data management
A marketing data hub is a more accessible solution that can make data readily available to all marketers in an organization without needing to rely on IT or a BI department. Some companies even find that using both a data warehouse for a technical team and a marketing data hub for their marketing team is the ideal setup.
For this very reason the marketing data hub has become a central component of the modern data ecosystem in recent years. Unlike data warehouses, which act as an endpoint for data collection and analysis, a marketing data hub is a centralized place to help businesses gather, organize, analyze and share data from different marketing channels and sources.
By consolidating data from the plethora of different sources like advertising platforms, web analytics, and CRM systems, a data hub eliminates data silos and offers a comprehensive understanding of marketing efforts. Furthermore, it acts as a central storage unit, providing a complete view of all performance.
For marketing teams, this often means:
- Increased agility
- Reduced complexity
- Easier integration
- Improved data quality
- Faster time-to-value (supporting real-time decision-making)
- Better visibility
- Improved data governance
By improving data integration, accessibility, and data management, marketers can track, report, and act quickly based on data-driven insights. This leads to better marketing performance and ROI as teams uses essential control instruments to reach their desired goals instead of operating blindly.
Data analysis
The amount of data created daily is hard to wrap your head around. The total amount of data created, captured, copied, and consumed globally was 97 zettabytes in 2022. By 2025, that number is expected to nearly double to 181 zettabytes. To put that number into perspective, back in 2011, Cisco described one zettabyte as the equivalent of around 250 billion DVDs.
Companies are swimming in data, which is why data democratization is so important when aiming to better analyze and monetize data. Optimizing your data is no longer a matter of good case practice; it has quickly become the new norm. Organizations that adapt will outcompete those that don't.
For example, when democratizing data becomes a top priority, marketing teams can capitalize on more efficient brainstorming and greater creativity. They can understand campaigns and products quantitatively by accessing and feeling comfortable using the data they need. Instead of guessing, marketers can dig deeper into key metrics to confirm or pivot ideas in real time.
Tools and techniques for empowering non-technical users to analyze data
Tools exist today that allow non-technical users to access data in ways that make sense. For example, a marketing data hub can be an excellent solution as your organization moves toward data democratization, especially when working with a lot of marketing data.
When marketing data lacks context, it's useless or misleading. So, again, a move toward data democratization won't be overly successful if marketers don't know how to analyze the data available to them — or if they lack the confidence to leverage key insights.
A marketing data hub is vital to any modern data stack, as it helps integrate real-time data to present actionable insights. In 2023 and beyond, marketers need to act fast. Data that was relevant last week may have since lost its significance. Non-technical users need the right tools to develop the right skills.
The future of data democratization
As more businesses focus on the power of data democratization, relevant trends will emerge.
Technology will play a significant role in how the future of data democratization unfolds, shaping how businesses operate and grow. For example, innovation will soar as technology evolves and organizations grant access to data and self-serve analytics. Gartner estimates that by 2024, 80% of tech services and products will be built by professionals outside of IT.
Artificial intelligence (AI) will also play a significant emerging role, allowing organizations to access greater predictive capabilities and better analytical processes. Users can better understand why certain data matters and, more importantly, what to do with it.
AI democratization will grow alongside this concept, helping to train AI algorithms to correct for bias that may be present in data sets while significantly boosting efficiency. Terms like "machine learning" and "process autonomy" are already familiar among business leaders. In the coming years, the evolution of AI will likely lead to smaller data science and analytics teams. AI-powered tools will do all the number-crunching to develop trends and insights, allowing these expert team members to focus on bigger-picture tasks.
Recap of key points
- Data democratization definition: The concept that everyone has access to data because there are no gatekeepers to create bottlenecks. Non-technical users gain greater accessibility and, among those most successful, are empowered to use that data for insight-driven strategies.
- For modern businesses, democratizing data can lead to better decision-making, greater innovation, and increased collaboration.
- While data warehouses offer many benefits under the right circumstances, a marketing data hub is best suited for non-technical users who want to improve their performance and ability to scale.
- Ensuring a successful transition toward data democratization requires the right tools and skills to leverage actionable data and an organization-wide culture prioritizing data democratization.
Bottom line: Data democratization is good for marketers as long as they are empowered with tools and processes that support the unique needs of marketing departments and marketing data.
Related reading: What are misleading visualizations and how do you avoid them?
