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The ebook is always available in multiple formats, DRM-free, for “pay what you can” with a suggested price of $15.

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Volume 2

Excerpt: Introduction

Or welcome in the first place for those of you just joining us. Either way, welcome!

It’s been quite eventful since EDDR launched with Volume I’s Lessons from the Trenches of Applied Data Science. In that release we set out to write the field guide we wished we each had in our respective back pockets when we’d started out in the applied analytic environment. We also wanted to provide a gathering point for all the hardworking, ingenious, altruistic folks out there in the education data space who staff the schools, Local Education Agencies (LEAs), and State Education Agencies (SEAs). We wanted to give a proverbial talisman of sorts, so those folks could take heart, and know that they’re not alone (and neither are you!).

Over the last two years, we’ve heard from many of you, our comrades and our colleagues in data science for the public good. Thank you for your kind words, your incisive, spot-on feedback, and your sharing our excitement about giving this kind of work the attention we think it deserves.

We’re back in this volume to bring together some truly fantastic, careful, meaningful work that’s been happening across this field through the creativity, commitment to getting it right, and diligence of some really talented folks. Volume II adds three new voices to our returning authors from Volume I. Their contributions showcase some of the best work taking place across the nation.

It’s work that’s not coming from the hallowed halls of the academy, but from the quotidien cubicles (or remote work spaces set up rapidly in our homes after the pandemic hit) where we, any of us, report for duty each day. But before we get too far into what this volume will share, let’s recap why you should bother to read this book in the first place.

For those of you who’ve already read volume one and know why you want to keep reading, skip right ahead to the next section. For those of you who still need to be convinced, please do read on!

Why you should keep reading this book.

As you might have gathered from the opening few sections, this book series is different.

First, each volume is a living document – this is the 2021 edition of Volume II. On a regular basis, with experts in the field (maybe you?), we plan to add chapters and update the books. The field is changing rapidly, and we need a publishing approach that fits with those changes.

We set out to write something more substantial and crafted than a blog, but less stodgy and slow than a book series from an academic press. So, we’re using LeanPub – you pay what you want for the books and you get free updates as we add new content. If you want a printed version of any of the volumes, you can order print-on-demand versions as well.

This approach has two big advantages. First, you can be part of this series. See a typo? Let us know, we’ll fix it, and give you an acknowledgement. Have a resource to share that would fit well in one of the chapters? Send it in and if we include it, we’ll credit you.

We can update the books as frequently as we like between full releases or new editions – fixing typos, adding resources, and improving them as we go and as a community of practice.

The real value of this approach comes from when we hear from you. We are offering this series as a gathering point for conversation, as a way to spark interest, share knowledge, and as a means to find more people like us and get their great ideas heard so they can help others.

So, in short, we invite you to please contribute.

A second advantage of our approach is that you can use this series or any volume on its own however works best for you.

We believe in creating a resource that works for our colleagues across the country (and maybe world?) (besides, everyone knows there is no money in writing books these days).

What’s important to us is not the extra cup of coffee we might be able to buy someday (maybe - not likely) from the proceeds, but how the books can be used by you to help you in your important work. Take the books, give copies to everyone on your team, hold discussion sessions with them, print them out, and share them if you find them useful.

Use them however you like. All we ask is that you don’t redistribute them commercially and that if you use them and like them, please make sure to give us some attributions as authors and maybe drop us a note letting us know how you used them. That’s it!

So, Volume II. Anything Good in Here?

Yes (well, we think so anyways!). When we started this project, we envisioned it as a three volume series and this right here is volume two. In this release, we’re introducing some new voices with the hope that more are encouraged to share their work as a result. This text shares some great stuff that folks are doing for very average, public sector paychecks sweetened with the knowledge that their work is contributing to a pillar of our practice of self-governance, public education.

So yeah, this volume introduces you to some people we think are doing good things for the field of applied data science in education. They haven’t done this work for the money and they certainly haven’t done it for the fame. They’ve done it because harnessing sound, careful science in the name of public service is what makes these folks excited about their jobs.

That’s pretty exceptional, so is their work, and we think more people should know about it because what each one of us does to advance that field, we all benefit from. What each of us contributes can help another of us move forward in their efforts. We believe we’re in this together and we’re better that way, so that’s why we wrote this volume about them and their work.

Just like in volume one, each chapter has been reviewed by at least one expert whom we have asked to check the work - see the reviewer biographies to learn about the kick-ass people whose experience helped make this volume worth your taking the time to read about it.

To that end, this second volume has a few different contributors. They cover some of the most thoughtful stuff we’ve encountered and they showcase how folks, just like you and us, are bringing rigor into their work on a daily basis. From Justin Meyer’s (Wisconsin) piece on how documenting work is a critical component to continuity of operations (and not making people crazy), to LaCole Foots’ (Texas) discussion about the importance of self-reflection and awareness of how our identities shape our approach to our work, this volume brings together voices from across the nation.

Ellis Ott (Alaska) and DJ share a thoughtful conversation about transparency, reproducibility, and their place in our work, while Wendy and Jared provide a primer on how to navigate data governance work and the work it both necessitates and produces in an institution, offering some concrete steps you can take to get started. Jared outlines not just what an Early Warning System (EWS) is, but why it’s useful and how you can build your own at your organization.

Finally, we close this edition with some reflections on how the Pandemic has deeply underscored the very real, immediate, and ongoing need for careful data collection, management, and use. As Wendy recently wrote in a proposal for how to leverage a portion of stimulus funds to future-proof some of Vermont’s data infrastructure, Howard Yonas, MD says, “making decisions without data is called guessing” and guessing isn’t good enough when it comes to the work we need to do to stabilize our education system. We need good data practices, systems, and products to meet the needs of our students and families amidst the emergency, not to mention onwards into the recovery process.

So, with that, read on and welcome to the work! We’re there with you, right by your side.

Table of Contents


Organizing and Documenting Analysis Projects

The Answers Are Within

Transparency: Helping Others See What the Data Truly Reveal

Data Governance

Early Warning Systems: A Consumer's Guide

Reflections and Conclusions

Suggested Citation

Foots, LaCole; Ott, Ellis; Meyer, Justin; Geller, Wendy; Cratty, Dorothyjean; and Knowles, Jared. 2021. Education Data Done Right Volume 2: Building on Each Others’ Work. Victoria. Leanpub. Available online: www.eddatadoneright.com

Volume 1


This book came together after a series of conversations among the others (and others) about our frustrations with the lack of information available about how to do the real work behind education data analysis. In 2015, we were happy to be invited by the Brown Center Chalkboard at Brookings to discuss those ideas in a series of posts:

From these articles, and more conversation, we decided to put together a book that filled what we saw was a real gap in practical advice on how to do the work that needs to get done inside education agencies to turn those many data collections into information that can inform decisions and return value to educators, students, and the public.

Education Data Done Right: Lessons from the Trenches of Applied Data Science


Across the country hundreds of data scientists and analysts are working for thousands of education agencies trying to help schools, school leaders, and education systems as a whole function more effectively. The work they do is critical to everything from scheduling classes and evaluating programs, to managing enrollments, strategic planning, and making the laws that shape our public education system at large.

This book is for them. For their work.

Lots of pundits and researchers have ideas about how education data work should be done and who should do it. Many of their ideas are disseminated widely. But, there are far fewer places for education analysts themselves to share their ideas, to describe their challenges, to cover their efforts to do good science in the everyday.

We wanted to bring the voices and the work these folks do to to the forefront, so others among them could learn from the hard fought advances they’ve made and that benefit us all.

This book is by folks who’ve been agency analysts for folks who are agency analysts.

And we hope it is just the beginning.

Suggested Citation

Geller, Wendy, Cratty, Dorothyjean, and Knowles, Jared. 2019. Education Data Done Right: Lessons from the Trenches of Applied Data Science. Victoria. Leanpub. Available online: www.eddatadoneright.com

Table of Contents




Metadata and Business Rules


An Analyst’s Guide to IT


Data Requests: You Can Make Them Useful (we swear)


Politics and Data Driven Decision Making


Moments of Truth: Why Calculating Descriptive Statistics Is Actually Some of the Most Important Work You’ll Do


Applying Tools of the Trade: Descriptive Data Commands in Context