In the mission-driven world of nonprofits, success is often measured by impact. Questions arise about the number of people served, communities empowered, and the causes advanced. Private and community Foundations feel this acutely, as they are being expected to fill larger and larger voids left by shifts in government funding ranging from critical healthcare research to community reinvestment programs.
Underpinning all is a critically important asset: data. Specifically, clean, trustworthy, and actionable data.
Many organizations, however, are held back by fragmented information, outdated systems, or a lack of trust in their own data. This not only creates stress for teams but also depresses innovation and hinders the ability to make evidence-based decisions.
The challenge is twofold. First, how do you improve the day-to-day discipline of managing data? And second, what is the right technological infrastructure to support this effort? How do you move from data silos to data strategy?
The answer lies not just in a new solution or a quick data cleanup, but in a strategic, holistic approach that addresses both process and platform.
The Problem with Untrustworthy Data: A Case Study in Opportunity
Consider a mature, mid-sized nonprofit with a loyal base of subscribers and hundreds of thousands of household donors. Their fundraising efforts were stuck in a cycle of seasonal, stressful campaigns. The root cause: Despite efforts to make their CRM “clean”, they knew that their CRM was only part of the picture of how constituents engaged. They volunteered. They were funders. They engaged with email content. But, the organization had no way to fully understand the constituent picture. This meant they were operating on intuition rather than evidence, and their relationships with constituents, and communities suffered.
This meant breaking down internal silos so that marketing, development, programs, and finance/operations could share in the richness of
A new technology solution alone was not the answer. The real work was aligning technology, process, and people – moving from isolated and non-functioning data silos to a comprehensive data strategy. This data strategy identified that, while they could theoretically string together disparate systems through APIs or ETLs, there was a likely a better approach. This approach would create a data platform that key systems would connect to enabling staff to answer questions that improved constituent experiences, evaluate their impact, and better forecast revenue
This experience highlights a crucial truth: data management is not a one-time project but an ongoing discipline. It requires continuous monitoring and updates. Yet, for an organization to truly embrace this discipline, it needs a technology platform that can handle the complexity of its data—and this is where the conversation turns to data warehouses, data lakes, and data platforms.
Building the Foundation: Choosing the Right Data Infrastructure
With the value of clean data firmly established, the next logical question for a nonprofit is: where should all this data live? Without a strategy, data silos will keep your organization from reaching your goals.
As organizations capture more information from various sources, donor records, marketing analytics, program outcomes, financial data, the traditional approach of trying integrate data becomes challenging and, in many cases, unsustainable. The modern solution is a more sophisticated data infrastructure, with three primary options emerging: data warehouses, data lakes, and data platforms. Each has its own features, benefits, and tradeoffs, and the right choice to move from data silos to data strategy depends on your organization’s unique needs and capacity.
What is a Data Warehouse?
A data warehouse is a highly structured repository designed to store and manage data that is already cleaned and organized. It’s optimized for fast querying and reporting, making it ideal for operational business intelligence and trend analysis. For a nonprofit, a data warehouse is a perfect fit for an organization that tends to have large, and complex, volumes of data. Imagine an organization that needs to perform complex calculations, conduct extensive trend analysis on well-defined transactional data. The key benefit is improved data quality and consistency, but it may require ongoing investment to scale.
What is a Data Lake?
In contrast, a data lake is a repository that often stores raw, unprocessed data in its native format. This can include unstructured data like documents, program evaluation forms, narrative descriptions, etc. This is where you ingest everything from spreadsheets and CSV files to documents, images, and other unstructured data. A data lake is excellent for organizations dealing with a variety of data types, especially if they are not yet sure how they will use the data. It’s compatible with advanced analytics and machine learning as well as reporting tools like Tableau and PowerBI.
What is a Data Platform?
A data platform is an all-in-one solution that integrates storage, processing, integration, and analytics into a single ecosystem. It is a comprehensive tool for managing data from end to end. Platforms like Snowflake and Google BigQuery offer a scalable, unified environment. They provide the flexibility of a data lake with the structure and usability of a data warehouse, making them a powerful choice for organizations looking for a complete solution.
Making the Right Decision for Your Nonprofit
Choosing the right solution isn’t about jumping on a buzzword like “data warehouse.” It’s a strategic decision that requires careful consideration of five key factors:
- Data Volume and Variety: Assess the amount and types of data your nonprofit handles. Do you primarily have structured donor records, or are you also collecting large volumes of unstructured data like program reports, videos, or survey responses?
- Data Accessibility and Usability: Who needs to access this data? The solution should be usable by a range of people, from a data analyst to a department head. A tool that is too complex will not be adopted, no matter how powerful it is.
- Cost and Budget Constraints: Go beyond the sticker price of the tool. Consider the long-term costs of ownership, including staffing, ongoing storage, and training.
- Scalability and Future Growth: Does the solution have the capacity to grow with your organization? Data lakes and platforms are generally designed for greater scalability than traditional data warehouses.
- Team Expertise: Do you have the internal skills to manage and maintain the solution? If not, will you need to hire new staff or bring in external consultants for support?
Ultimately, the best approach is to ground the decision in a data strategy that is informed by your organization’s broader mission and goals. Don’t choose a solution based on a single team’s preference. Instead, conduct a requirements-based analysis that addresses the realities of your current operations and your future strategic vision.
The Path Forward: Data Silos to Data Strategy
Combining the power of a disciplined data management process with the right technological infrastructure can transform a nonprofit’s ability to maximize its impact. By investing in trustworthy, accessible, and complete data, your organization can move into a world of proactive, evidence-based strategy. The time and effort spent in this process will create greater trust in your strategies, empower staff to focus on high-value activities, and, most importantly, allow your organization to build stronger, more meaningful connections between data and your mission.
