Our team works with our partners throughout several stages of development, like focusing on data pipelines and implementing interoperable data standards to improve data automation and quality. We take pride in our ability to create common analytics frameworks, data standards, and custom guidance that create more efficient processes to better support each partner’s unique needs.

We explore these types of challenges:

How can a state education agency effectively, privately, and securely support district use of data?

At EA, we believe there is an appropriate owner for every piece of data and that all stakeholders—from students and parents to districts to states—should have full control over the data they own. But there are currently very few mechanisms for those owners to exercise their control over their data, especially for students and parents. As state education agencies (SEAs) move away from strict compliance and accountability and towards acting as a service provider to their districts, SEAs need a way to access data for the purposes of supporting LEAs (such as through collective buying of services that reduces costs for districts) without jeopardizing local control and ownership of those data. Although some use cases may call for a singular data system at the state level with complex governance structures, EA aims to support SEAs wherever possible in building data pipelines that retain ownership of data at all points, and allow data owners to push their data at the right level for a particular use case. These pipelines leverage open data standards for data transmission that reduce costs and burden on the districts. Although this is difficult from a technical and implementation perspective, we believe it is the right strategy to support data stakeholders at all levels of the educational system, and to open up opportunities for widespread data use without widespread dilution of privacy and security.

How can we reduce the cost of data collection for districts, collaboratives, and local education agencies?

When different districts have different data systems in place, this induces high costs and barriers to entry for cross-district collaboration. For instance, trying to calculate a chronic absenteeism rate for a single student who attends schools across multiple districts involves navigating multiple data systems and reconciling many different ways that data are stored and defined. Although we could ask districts to change their data into a shared format to facilitate this type of calculation, this is a manually intensive effort that costs money (usually borne by the organization aiming to foster collaboration and cross-LEA learning). EA uses standards-based data collection approaches and interoperability technology to collaborate around a joint file specification, automate the inhalation of data meeting those specs, and store those data in a unified data system for joint collaborative analytics. By using algorithms to automate the identification of thousands of files, we free up our analytics talent to be deployed for deeper, more meaningful data analytics and visualization—which has broader recruitment and retention benefits for the analytics field at large.

What does it look like to bring open-source tech to the K-12 space to improve student outcomes?

EA embraces open-source technology as a key strategy for increasing ease of access to data while retaining data ownership, privacy, and security. We incorporate open-source tech into our work in two key ways. First, we are deeply involved in open-source technologies specifically built for education, such as Ed-Fi data standards. EA specializes in bridging the gap between data technology and data use, by helping IT and backend administrators understand the value of analytics and research, while helping our policy and practitioner partners understand the value of strong data governance. Second, EA leverages open-source technologies created by commercial industries to help radically lower the cost to develop tools and platforms for educators. By using tools like AirFlow (created by Airbnb) or Amazon Web Services as a cloud technology, EA remains deeply committed to leveraging technology created in any open-source space to help improve education and serve our education partners.

Data Collection & Systems topics:

Data Automation

Our team collaborates as a thought partner to build data systems that automate the sourcing and processing of data to enable timely delivery of analytics. We use the best new open-source technology available to construct data pipelines, with a focus on proactively anticipating data quality issues and making business rule decisions transparent. We also build upon our experiences with other education agencies we have worked with across the country to create common analytics frameworks. This allows us to build faster and more efficiently, while allowing us to tailor our architectural guidance to each partner’s specific needs.


We are proponents and supporters of open-source data standards such as Ed-Fi that enable better, faster, more detailed, and more powerful data analysis. We support education agencies in implementing interoperable data standards and leveraging those standards for data extraction and transfer wherever possible.

Equity is a buzzword unless it is accompanied by action. Working with EA as a trusted partner allows SCDE to provide an element of data equity with an Ed-Fi ODS across every district in South Carolina.

Director, Office of Research & Data Analysis, South Carolina Department of Education (SCDE)

Meet some of our team

Product Specialist
Staff Data Engineer
Data Engineer II

Interested in Learning More About EA?

We want to empower you to be informed and discerning data consumers. We get excited about the work we do and are enthusiastic about the changes it can bring to education.