Imagine your team losing an entire workday each week. That's what’s happening when workers spend nearly 8.4 hours weekly simply trying to find—and get access to—the data they need.
That is time they could use to develop new products and features, optimize the supply chain process, implement customer loyalty initiatives, develop sales funnels, or improve the customer experience instead of hunting for data.
This time spent away from tasks that have a more positive impact on your business is a consequence of data silos, which occur when different teams or employees manage their data sets independently, making it challenging for the rest of the organization to access and use this data.
And it’s only one of many negative repercussions. Others include:
Duplicated efforts and data creation across the organization, as different teams may unknowingly work on similar tasks due to a lack of shared information.
Employees using inconsistent, outdated, or inaccurate data because it’s not centralized.
Critical insights being missed when data isn't accessible, impacting strategic decision-making.
Higher operational costs because of fragmented data systems, as well as the cost of time lost trying to find and get access to the data.
Data silos are detrimental to organizations, and data democratization is the best answer to these daily frustrations.
What is data democratization?
Data democratization is the process of providing data access to everyone in your organization, regardless of their technical skills. It empowers employees to find, understand, and use data themselves without needing help from your IT department.
Data democratization won’t turn your whole team into data experts, but it can help break down the barriers that data silos perpetuate by making data accessible to everyone.
Where data silos can exist in an organization
Data silos occur when data sets are isolated in various places and various forms in an organization, preventing different teams from being able to access data.
People’s heads—Organizations without a culture of documentation may find a lot of knowledge is not recorded. Instead, employees retain this knowledge as things only they know, and it’s permanently lost when the individual leaves the organization.
Physical files, papers, and spreadsheets—Despite the ubiquity of smartphones and computers, we often create a lot of information in physical formats, such as architectural plans and blueprints, inventory lists, official communication, tax returns and audit reports, and contracts. This physical data requires physical storage space and precise cataloging for employees to find later. It can be easily misplaced and is time-consuming to sift through, and there’s a risk of damage to documents from water, wear and tear, and time.
Digital spreadsheets—You’ll be hard-pressed to find an organization that doesn’t use digital spreadsheets like Google Sheets or Microsoft Excel. Digital spreadsheets take less space than physical data storage, but they can still be siloed because employees haven’t enabled access permissions or because files are saved in an individual user’s Google Drive, Microsoft OneDrive, or local disk storage.
Digital databases—Data stored in databases that use Structured Query Language (SQL) is theoretically accessible to everyone. In reality, an SQL database is technically complex and requires technical knowledge—SQL skills—to access, siloing the data stored in it.
Software—One of the greatest complaints of teams that have to use many different tools for their work is that they need the cooperation of multiple team members just to log in and export basic data. This seriously slows down processes, and they are blocked from putting together essential reports or accessing data for regular tasks. Off-the-shelf software is often prohibitively expensive by seat, and tools are usually specialized for different functions. To keep subscription costs in check, not all employees or teams can access every software login. This can mean waiting for a coworker (or several) to share the data and then putting it together for what you need. The software may also be incompatible with other systems or software in your tech stack, even with native integrations or available APIs and webhook connections, restricting you from connecting it to other tools.
Benefits of data democratization and fixing data silos
Breaking down data silos and democratizing data are closely linked. When you make data accessible to everyone, you dismantle the existing barriers that keep information isolated. This open data access, in turn, prevents new silos from forming, as employees know exactly where to find the data they need and store the data they create.
Improved data quality—Removing data silos results in more complete, accurate data and knowledge since all the data is in one place for everyone to access.
Improves collaboration—With more—and more accurate—data readily available, employees can easily share and access information, leading to more opportunities for communication, collaboration, and innovation.
Improves efficiency—Consolidating data and giving your employees easy access means they spend less time searching for information and more time on productive tasks.
Reduces costs—Improved efficiency and streamlined data management reduce operational expenses. In fact, organizations with 1000 employees can save approximately USD 2.7 million from improved knowledge sharing.
Enables data-driven decisions—With all of your organization’s data at hand, you have a full picture of your progress toward goals, customer behavior and preferences, and budget allocations, among other things. This complete information can help you make data-driven business decisions to identify new revenue generation or savings opportunities and improve overall strategy.
How to democratize data and break down data silos in your organization
Giving employees access to data doesn’t mean simply providing a data dump of everything in your data warehouse. Achieving data democracy means equipping employees with the right data, the right tools—literal and figurative—to work with it, and the knowledge and skills to analyze and act on it.
1. Define data objectives and set metrics
What do you want to achieve by making data more accessible? Clearly outline your goals, which should align with your company’s overall objectives. This could include anything from better decision-making to strengthening quality control, improving customer experience, and optimizing pricing strategies.
Next, determine which metrics will help you measure progress toward these goals. This could include metrics like decision time taken, error rates reduced, customer satisfaction scores, or revenue growth.
You can better understand the actions you need to take to achieve your goals as data becomes more accessible.
2. Conduct a data audit
Create an inventory of all your organization’s data assets, and assess your data management practices. This includes evaluating how data is stored, accessed, and shared:
Data Storage—Is most of your data stored in the cloud or on on-premise sources such as local servers or computers? Is it physical data stored in a room in your office or a storage space? It could even be a combination of these. List your data sources and identify where different data types originate and are stored.
Data Access—Look at how your employees typically gain access to your data. Are they using SQL queries or logging in to cloud-based platforms or Business Intelligence tools? Do they have access to data warehouses where it may be stored, like Google BigQuery? The most crucial step here is to note who—or which team—has access to what data sources. Identify any common access barriers, such as outdated permissions and access controls.
Data Sharing—Look at how employees access data they haven’t created or share it with the rest of your organization. Are they regularly emailing each other or sending messages in Slack asking coworkers to send them files or give them access to a document? If you’re using cloud-based software, list which employee can access each software your organization uses.
Your audit should help you determine which data silos are the bottlenecks preventing you from achieving your objectives so you can prioritize them when setting up new systems. Create a data catalog and add metadata to keep your inventoried data organized and set up self-service access for your employees.
3. Create data governance guidelines
Data democratization means empowering all employees with data access. However, you still need some guardrails and access controls to protect sensitive data such as trade secrets and employee social security details.
Establish clear guidelines that govern who will have access to sensitive data and how all the data your organization holds—especially customer data—can be used. This can help ensure you maintain data quality, privacy, and security. You should regularly review and update these guidelines to adapt to business changes, new data types you may create or collect, and regulatory requirements.
4. Select the right tools and technologies
Breaking down data silos doesn’t mean eliminating all your tools in favor of one—there’s no single, magical platform that fits every team’s needs for all use cases. Instead, invest in a tool that acts as a centralized interface where employees can store, access, visualize, and share data from wherever it lives with the rest of the organization.
No code app builder—Use a no code app builder like Glide to create an internal business app that draws data from your different sources together. A custom interface with data visualization features can help stakeholders access, easily interpret, and act on data in real time, creating a single source of truth and eliminating data silos. Data sources can include everything from a data warehouse like BigQuery to a spreadsheet like Google Sheets. App interfaces allow teams to see and act on data insights without having full access. Adding forms can give them an easy way to submit shared data, and you can integrate tools like DocsAutomator to easily generate PDF reports for leadership.
SQL GUI—Tools like an SQL Graphical User Interface (SQL GUI) give non-technical users an intuitive, visual interface to interact with data stored in SQL databases. Employees can use an SQL GUI to query data, manage databases, and perform self-service analytics without writing SQL syntax. Commercial SQL GUI software options include DBeaver, MariaDB, Beekeeper Studio, and DbGate. You can also use no code tools like Glide to build a custom SQL GUI.
APIs—APIs allow different software to communicate with each other. This enables data integration from these different platforms, making data accessible in one interface without requiring manual data transfers. You can use Glide’s API to fetch data from other software and add it to your internal app.
Some important features to look for when choosing a centralized tool for your data are a user-friendly interface for non-technical users, data visualization to make complex data easier to understand, scalability so it can grow with your organization, accessibility across devices so employees can add to and find data when they need it, and taxonomy and categorization to make data searchable.
5. Promote data literacy
Your employees dive into data every day, so they need to really understand it to use it effectively. You may not have the help of data scientists, analysts, or engineers at your disposal, but with basic data literacy programs, you can equip your team with the knowledge and skills to understand and use data effectively.
Offer access to training sessions and resources focused on data analysis, interpretation, and best practices to improve data literacy across the organization. You can tap into your learning or education stipend to encourage your team to take a course in data. The Data Literacy Project, DataCamp, and Codecademy have data literacy courses you can explore as recommendations for your data literacy programs.
The aim is to make sure that all your employees are trained on how to use new tools and understand the benefits of data democratization so that they don’t unknowingly reinforce data silos when creating new data.
6. Monitor and adjust your efforts
Data democratization is an ongoing process, and you need to continuously monitor how effective your efforts are against the goals you previously set. If you find that data remains siloed or employees aren’t able to find data or use it effectively, adjust your processes as needed so that the team continues to have data access and avoids slipping back into older workflows that created data silos in the first place.
In addition to tracking your progress through metrics, you can also gather employee feedback to learn how your data democratization efforts are going. Your employees are best positioned to tell you whether they can use the new centralized tool you’ve implemented and work with cohesive data. Use this feedback to address issues and refine your data accessibility tools and strategies.
Continue democratizing data and strengthen your business
Data democratization empowers employees at all levels to make informed decisions and reduces the delays and costs that go hand-in-hand with searching for and getting access to data. If you’re looking to democratize data and break down data silos, you could consider building a custom internal knowledge base. It serves as a collaborative platform for the organization where employees have easy access to all the data in one place and on any device. Combined with a strong data governance policy and data literacy efforts, an internal knowledge base can help break down data silos and promote data democratization across your organization.
