The Data Teams Experience

The Data Teams Experience PDF

Author: Angela B. Peery

Publisher: Lead and Learn Press

Published: 2011

Total Pages: 0

ISBN-13: 9781935588023

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An instructional Data Team is a small group based on grade, department, or course that examines student's test. These tests are focus on prioritized standards or learning goals that are aligned with Common Core State Standards. The student's work is analyzed to gain a picture of how the student is doing. Then the Data Team selects instructional strategies to address the student's learning challenges. This is a how-to for those meetings.

Building Analytics Teams

Building Analytics Teams PDF

Author: John K. Thompson

Publisher: Packt Publishing Ltd

Published: 2020-06-30

Total Pages: 395

ISBN-13: 180020518X

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Master the skills necessary to hire and manage a team of highly skilled individuals to design, build, and implement applications and systems based on advanced analytics and AI Key FeaturesLearn to create an operationally effective advanced analytics team in a corporate environmentSelect and undertake projects that have a high probability of success and deliver the improved top and bottom-line resultsUnderstand how to create relationships with executives, senior managers, peers, and subject matter experts that lead to team collaboration, increased funding, and long-term success for you and your teamBook Description In Building Analytics Teams, John K. Thompson, with his 30+ years of experience and expertise, illustrates the fundamental concepts of building and managing a high-performance analytics team, including what to do, who to hire, projects to undertake, and what to avoid in the journey of building an analytically sound team. The core processes in creating an effective analytics team and the importance of the business decision-making life cycle are explored to help achieve initial and sustainable success. The book demonstrates the various traits of a successful and high-performing analytics team and then delineates the path to achieve this with insights on the mindset, advanced analytics models, and predictions based on data analytics. It also emphasizes the significance of the macro and micro processes required to evolve in response to rapidly changing business needs. The book dives into the methods and practices of managing, developing, and leading an analytics team. Once you've brought the team up to speed, the book explains how to govern executive expectations and select winning projects. By the end of this book, you will have acquired the knowledge to create an effective business analytics team and develop a production environment that delivers ongoing operational improvements for your organization. What you will learnAvoid organizational and technological pitfalls of moving from a defined project to a production environmentEnable team members to focus on higher-value work and tasksBuild Advanced Analytics and Artificial Intelligence (AA&AI) functions in an organizationOutsource certain projects to competent and capable third partiesSupport the operational areas that intend to invest in business intelligence, descriptive statistics, and small-scale predictive analyticsAnalyze the operational area, the processes, the data, and the organizational resistanceWho this book is for This book is for senior executives, senior and junior managers, and those who are working as part of a team that is accountable for designing, building, delivering and ensuring business success through advanced analytics and artificial intelligence systems and applications. At least 5 to 10 years of experience in driving your organization to a higher level of efficiency will be helpful.

Building Data Science Teams

Building Data Science Teams PDF

Author: DJ Patil

Publisher: "O'Reilly Media, Inc."

Published: 2011-09-15

Total Pages: 14

ISBN-13: 1449316778

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As data science evolves to become a business necessity, the importance of assembling a strong and innovative data teams grows. In this in-depth report, data scientist DJ Patil explains the skills, perspectives, tools and processes that position data science teams for success. Topics include: What it means to be "data driven." The unique roles of data scientists. The four essential qualities of data scientists. Patil's first-hand experience building the LinkedIn data science team.

The Data Coach's Guide to Improving Learning for All Students

The Data Coach's Guide to Improving Learning for All Students PDF

Author: Nancy Love

Publisher: Corwin Press

Published: 2008-02-27

Total Pages: 409

ISBN-13: 1412950015

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Use data as an effective tool for school change and improvement! This resource helps data team facilitators move schools away from unproductive data practices and toward examining data for systematic and continuous improvement in instruction and learning. The book, which includes a CD-ROM with slides and reproducibles, illustrates how the authors' model has proven successful in: Narrowing achievement gaps in all content areas and grade levels Achieving strong, continuous gains in local and state assessments in mathematics, science, and reading Initiating powerful conversations about race/ethnicity, class, educational status, gender, and language differences Developing a vision for a high-performing, data-informed school culture

Designing with Data

Designing with Data PDF

Author: Rochelle King

Publisher: "O'Reilly Media, Inc."

Published: 2017-03-29

Total Pages: 370

ISBN-13: 1449334954

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On the surface, design practices and data science may not seem like obvious partners. But these disciplines actually work toward the same goal, helping designers and product managers understand users so they can craft elegant digital experiences. While data can enhance design, design can bring deeper meaning to data. This practical guide shows you how to conduct data-driven A/B testing for making design decisions on everything from small tweaks to large-scale UX concepts. Complete with real-world examples, this book shows you how to make data-driven design part of your product design workflow. Understand the relationship between data, business, and design Get a firm grounding in data, data types, and components of A/B testing Use an experimentation framework to define opportunities, formulate hypotheses, and test different options Create hypotheses that connect to key metrics and business goals Design proposed solutions for hypotheses that are most promising Interpret the results of an A/B test and determine your next move

Data Smart

Data Smart PDF

Author: John W. Foreman

Publisher: John Wiley & Sons

Published: 2013-10-31

Total Pages: 432

ISBN-13: 1118839862

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Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.

Designing Distributed Systems

Designing Distributed Systems PDF

Author: Brendan Burns

Publisher: "O'Reilly Media, Inc."

Published: 2018-02-20

Total Pages: 164

ISBN-13: 1491983612

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Without established design patterns to guide them, developers have had to build distributed systems from scratch, and most of these systems are very unique indeed. Today, the increasing use of containers has paved the way for core distributed system patterns and reusable containerized components. This practical guide presents a collection of repeatable, generic patterns to help make the development of reliable distributed systems far more approachable and efficient. Author Brendan Burns—Director of Engineering at Microsoft Azure—demonstrates how you can adapt existing software design patterns for designing and building reliable distributed applications. Systems engineers and application developers will learn how these long-established patterns provide a common language and framework for dramatically increasing the quality of your system. Understand how patterns and reusable components enable the rapid development of reliable distributed systems Use the side-car, adapter, and ambassador patterns to split your application into a group of containers on a single machine Explore loosely coupled multi-node distributed patterns for replication, scaling, and communication between the components Learn distributed system patterns for large-scale batch data processing covering work-queues, event-based processing, and coordinated workflows

Visual Teams

Visual Teams PDF

Author: David Sibbet

Publisher: John Wiley & Sons

Published: 2011-09-23

Total Pages: 320

ISBN-13: 1118158598

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Graphic tools and visual solutions for team building and development Visual Teams uses visual tools and methods to help teams—both face-to-face and virtual—reach high performance in today's work environment. As teams become more and more global and distributed, visualization provides an important channel of communication—one that opens up the group's mind to improving work systems and processes by understanding relationships, interconnections, and big picture contexts. Visual Teams shares best practices and uses visualization as a power tool for process improvement by providing teams with a common language for high performance. The book: Explores how any kind of team can draw on the principles and practices of creative design teams in the software, architectural, engineering, and information design professions Introduces the Drexler/Sibbet Team PerformanceTM Model and related tools—a system used throughout companies such as Nike, Genentech, Becton Dickinson, Chevron, and others Visual Teams presents a comprehensive framework, best practices, and unique visual tools for becoming an innovative, high-performance team.