Educators globally are continually encouraged to use data to inform instructional improvement in schools, yet while there have been many recent innovations in data visualization and data science, educators are rarely included in dashboard co-design. On December 5 and 6, 2019, the Education Data Analytics Collaborative Workshop was held at Teachers College, Columbia University in New York City with approximately 80 participants. This workshop was part of the final phase of the collaborative National Science Foundation funded research project (#1560720) "Building Community and Capacity for Data-Intensive Evidence-Based Decision Making in Schools and Districts", a research practice partnership (RPP) on data use and evidence-based improvement cycles in collaboration with Nassau County Long Island BOCES (Board of Cooperative Education Services) and their 56 school districts in Nassau County Long Island, New York, USA. This edited book details the results from the workshop through 28 chapters from authors who were attendees, including educators, data scientists, and researchers. We aimed to achieve three goals through a collaborative workshop: (a) to bring educators together with data scientists in collaborative co-design to build conversation, workflows, visualizations, and pilot code; (b) to train educators and data scientists around data use in schools using the current data systems available and focusing on educator problems of practice; and (c) to publish open-access code as well as educator perceptions of this intersection of data use, visualization, and education data science to inform evidence-based improvement cycles for instructional improvement in schools. This book contains three sections: Section 1, Education Data Analytics Collaborative Workshop Organization and Studying the Event Itself, contains: (1) Introduction: Dashboards, Data Use, and Decision-making: A Data Collaborative Workshop Bringing Together Educators and Data Scientists (Alex J. Bowers); (2) Planning, Organizing, and Orchestrating the Education Data Collaborative Workshop (Alex J. Bowers); (3) NSF Education Data Analytics Collaborative Workshop: How Educators and Data Scientists Meet and Create Data Visualizations (Seulgi Kang and Alex J. Bowers); (4) Expanding the Design Space of Data and Action in Education: What Co-designing with Educators Reveal about Current Possibilities and Limitations (Ha Nguyen, Fabio Campos, and June Ahn); (5) Challenges and Successes in Education Leadership Data Analytics Collaboration: A Text Analysis of Participant Perspectives (Karin Gegenheimer); (6) Understanding Workshop Participant Movement Through a Temporal Cluster Analysis (Chad Coleman, Lauren Lutz-Coleman, Joshua Coleman, and Alex J. Bowers); and (7) Data Driven Instructional Systems: 2030 (Richard Halverson). Section 2, Data Collaborative Workshop Participant Datasprint Team Chapters, contains: (8) Look Who's Talking - Facilitating Data Conversations that Match Data Visualizations with Educators' Needs (Meador Pratt); (9) A Meeting of Three Interconnected Worlds: Reimaging Data for Practitioners (Wanda Toledo); (10) Building on Each Other's Strengths: Reflections from an Education Data Scientist on Designing Actionable Data Tools at the 2019 NSF Data Collaborative (Nicolas D'Amico); (11) Using Data to Pair Students and Teachers for Enhanced Collaborative Growth (Mohammed Omar Rasheed Khan); (12) Team Arrow's Path to Trust and Value: Getting the Right Data for the Right Task to the Right Person at the Right Time (Aaron Hawn); (13) Educational Data Workshop: What Does Success Look Like and How to Realize It (Burcu Pekcan); (14) Data Science in Schools -- Where, How, and What (Sunmin Lee); (15) Direct Data Dashboard (Melissa O'Geary and Laura Smith); (16) Pedagogy-driven Data: Aligning Data Collection, Analysis, and Use with Learning We Value (Louisa Rosenheck); (17) Collaborative Data Visualization: A Process for Improving Data Use in Schools (Elizabeth Adams, Amy Trojanowski, Jeffery Davis, Fernando Agramonte, Leslie Hazle Bussey, AnneMarie Giarrizzo, and Andrew Krumm); (18) An Open-Ended Data Collaborative (Imagined) (Fred Cohen); (19) Let Data Work (Yi Chen); (20) When in Rome (Kerry Dunne); (21) Responding Positively to Creative Packaging of Information (Robert Feihel); (22) Say Farewell to Dusty Data! (Josh McPherson); (23) Linking Data to Empower Meaningful Action (Leslie Duffy and Anthony Mignella); (24) The Components of a Successful Transdisciplinary Workshop: Rapport, Focus, and Impact (Elizabeth C. Monroe); (25) Moving the Conversation Forward for the Way Educators Would Like to View and Interpret Educational Data (Byron Ramirez). Section 3, Tools and Research for Data Analysis in Schooling Organizations, contains: (26) Data Viz in R with ggplot2: From Practical to Beautiful Visualizations (Tara Chiatovich); (27) Predicting High School Students' Performance with Early Warning Systems: A Theoretical Framework (Tommaso Agasisti and Marta Cannistrà); and (28) A Complex Systems Network Approach to Assessing Classroom/Teacher-Level Baseline Outcome Dependence and Peer Effects in Clustered Randomized Control Trials (Manuel S. González Canché).