Building a Data Culture—Unorthodox Tidbits from a Former Practitioner and Current Data Strategy Consultant

In 2022, Sarah Singer, a former district data leader who now consults on data strategy, shared lessons on building a data culture. Below Singer’s article, an updated section compares Singer’s advice with federal guidance on school data use and adds points on privacy and software choices.

Data can transform educational practice. More than ever, especially in the face of the COVID-19 pandemic, data is needed to understand where students are in their learning.

But the effective use of data throughout an organization doesn’t just happen overnight. It takes building a culture of data, including belief systems, norms, practices, and routines. And culture building is not easy to do. If done well, however, strategic priorities and accompanying plans are infinitively more likely to succeed.

As Peter Drucker said, “Culture eats strategy for breakfast.”

I want to start by saying I formerly oversaw a division in a large public school system that housed Research, Accountability, Assessment, and Strategic Planning. When I first took that role, I was determined to build a data culture. I was young and excited, pushing to create a “data culture revolution.”

On the plus side, because people always appreciate passion, they fed off that energy. But, in reflection, my data culture initiative was sort of a middle-tier priority for the district, at best. Urgent needs and other strategic priorities initially received more time and attention.

I also realized that my passion alone was not enough to carry the day. Our systems were people-dependent, wrought with single points of failure. If any one key person left, the whole data culture was ready to crumble. Culture, which transcends the act of one or a few individuals, needs to permeate the masses. I made progress for sure but did not quite get there.

Fast forward several years later to the present. By having held various roles in education, I have now had the opportunity to work across the U.S. with many other districts on data strategy and data culture. Through this work, I have come to better understand some of the components that make up a data culture. Below, I have articulated just a few of these.

1. Building a data culture by itself will always be a mid-tier priority at best; the key is to attach data use to the highest priorities. At the end of day, improving graduation rates, or ensuring that graduating students are prepared for CCLR (College, Career, and Life Readiness), will take precedence. Urgent items like staffing shortages due to COVID will also always be a priority. I’ve learned that the key is that data is a means to an end. For example, reviewing and monitoring data helps to improve third grade reading scores and graduation rates. Embedding data practices within key strategic priorities should be the first step for any practitioner looking to build data culture.
2. Data’s primary role can’t be punitive. Accountability is important, but if the dominant use of data in your system is to hold educators “accountable” for their actions or lack thereof, they will develop a troubled relationship with data. Without exception, data should primarily be framed as one tool to support educators as they work to improve students’ lives.
3. Structured systems are necessary to build educator competence and confidence. If data culture is lacking, the best way to build momentum is to ensure that your district and school builds in the time and space for groups of educators to collaborate around problems of practice. Structures such as professional learning communities, freshman success teams, or school improvement planning teams are examples. These teams can then build into their meeting routines the use and monitoring of data. This, in turn, will build organizational competence and confidence with data. More importantly, it will ensure better student outcomes.
4. Optimize educators’ time. Educators should not be wasting time with outdated spreadsheets, or filters on spreadsheets. They should not be going to three or four platforms to review data (assessment platforms, attendance, or behavior, for example, which often all sit in different systems). My feeling is that it’s a colossal waste of time for educators to search for the data they need, to filter it to their liking, or to put in a data request and wait several weeks for a partial answer to their data questions. Time is the most precious resource in education. The good news is that technology can handle data analytics more efficiently—and better—than humans. Teachers should spend their time doing what they do best, which is to teach children. We should set up systems that remove any obstacle that prevents them from doing what they do best.
5. Invest in an up-to-date analytics platform. To make all the above happen, invest in the right data platform. The platform is “the engine” for a district’s data culture and the car will not run without a well-functioning engine. Too many districts are stuck with outdated modes, such as spreadsheets, shared drives, or even BI (Business Intelligence) tools. Your platform should bring together disparate data sources to create a one-stop data shop. This will help educators correlate data and make meaningful connections across domains. Your dashboards should be in real-time and give you the ability to drill down to the student level. Critically, there should be no “wait time” for the data educators need. PowerSchool Unified Insights is an example of this type of platform. Alone, it will not build your data culture for you. But having this tool sets you on the right path.
6. Lead with the assumption that educators are the smartest people on the planet. I’m serious. There’s hesitancy in some districts to provide educators access to data. My belief is that once educators are provided with the tools and the space to collaborate—and have the competence and confidence to use data—they will do amazing things. They’ll support students in ways that a central office administrator or policymaker never would have dreamed possible. Initially, educators will rely on the structured systems available to them, but eventually their confidence grows and they will find ways to impact students’ lives in their own time and in their own organic ways.

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Building a data culture in school districts: what the guidance says and what to decide in 2026

Building a data culture in school districts means making it normal for teachers and leaders to look at evidence, talk about it together and act on it. Sarah Singer’s article above gives five habits that fit that description: attach data to the district’s top priorities, avoid using data mainly to punish, create structures where educators meet around data, save educators’ time, and trust educators with access. This section places those habits beside the best-known federal guidance on the subject, notes where the evidence is thin, and adds a legal point that every district needs when it chooses a platform.

What the federal practice guide recommends

The U.S. Department of Education’s What Works Clearinghouse published Using Student Achievement Data to Support Instructional Decision Making in September 2009. A panel of researchers and practitioners wrote five recommendations: make data part of an ongoing cycle of instructional improvement, teach students to examine their own data and set learning goals, establish a clear vision for schoolwide data use, provide supports that foster a data-driven culture, and develop and maintain a districtwide data system.

The guide is more than fifteen years old, and the Clearinghouse labels the level of evidence for all five recommendations as minimal (the 2009 guide itself rated each one low). The full guide explains why. Rigorous experiments on some data practices are hard or impractical to run, because it is difficult to find a fair comparison for something like a districtwide data system, and the panel adds that its recommendations should not be read as meaning no further research is needed. A district leader should therefore treat the guide as careful professional judgment, not as proof.

Even so, the specific steps match Singer’s advice closely. For building a data-driven culture, the guide suggests designating a school-based facilitator who meets with teacher teams to discuss data, dedicating structured time for staff collaboration, and providing targeted professional development regularly. Singer makes the same point when Singer recommends professional learning communities and school improvement teams that build data into their regular routines. For schoolwide vision, the guide suggests a data team that sets the tone, a written plan with roles and responsibilities, and ongoing leadership from the principal. Singer’s warning that a data culture can depend on one or two people ties to the written plan: roles that are written down survive when a key person leaves.

Choosing a district data system

Singer argues that an up-to-date analytics platform saves educators’ time by bringing attendance, assessment and behavior data together. The federal guide supports the process side of that choice more than any particular product. For a districtwide system it suggests involving a variety of stakeholders in the selection, stating requirements in terms of what users need, deciding whether to build or buy, and planning and staging the rollout. Teachers and building leaders who will use the system daily belong in that conversation from the start, and a district can ask each vendor to show how long it takes a teacher to find one student’s attendance, assessment and behavior records.

A district should also check the legal basis for sharing student records with a vendor. The Student Privacy Policy Office explains on its FERPA page that a school can treat an outside contractor as a school official only if the contractor performs a function the school would otherwise do with its own employees, is under the school’s direct control for the use and maintenance of education records, and is subject to limits on passing the information on. Those conditions matter whether the tool is a dashboard, an assessment platform or a new feature that uses artificial intelligence. A district’s lawyer or privacy officer should read the contract before records move.

Keeping data supportive

Singer says data should not be used mainly to hold educators accountable. A practical test for a district is to look at the last three data meetings and ask what happened afterward. If the answer is a plan to teach something differently, a change to a schedule or a support for a student, the data is working as a tool. If the answer is a list of names and scores, the culture may be moving the wrong way. Linking data use to a concrete priority, as Singer advises, helps. Attendance is a good example, and the edCircuit chronic absenteeism guide shows how districts connect attendance data to action. For ideas on what to collect and how to read it, see the assessment guide.

Where state policy is heading

Data practice in schools sits inside state systems. The Data Quality Campaign, a nonprofit focused on education data policy, lists on its home page a review of 2026 state legislation on education and workforce data access and a toolkit arguing that cross-agency data governance is the foundation for making data work for people. District leaders may find it useful to follow those publications, because state rules often decide which data a district can see and share.

Questions for a district team

1. Which one or two district priorities will our data work serve this year?
2. Who is the facilitator for each school’s data meetings, and when do teachers meet?
3. How many separate systems does a teacher open to see one student’s picture?
4. Has our privacy officer reviewed every vendor that receives student records?
5. When did data last lead to a visible change for students?

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