TOP 10 Data Analysis Best Practices Results at 10Bestify.com
Apache Spark is amazing when everything clicks. But if you haven’t seen the performance improvements you expected, or still don’t feel confident enough to use Spark in production, this practical book is for you. Authors Holden Karau and Rachel Warren demonstrate performance optimizations to help your Spark queries run faster and handle larger data sizes, while using fewer resources.Ideal for software engineers, data engineers, developers, and system administrators working with large-scale data applications, this book describes techniques that can reduce data infrastructure costs and developer hours. Not only will you gain a more comprehensive understanding of Spark, you’ll also learn how to make it sing.With this book, you’ll explore:How Spark SQL’s new interfaces improve perform... [Read More] Data Analysis Best Practices
This work provides in-depth analysis of the origins of landscape ecology and its close alignment with the understanding of scale, the causes of landscape pattern, and the interactions of spatial pattern with a variety of ecological processes. The text covers the quantitative approaches that are applied widely in landscape studies, with emphasis on their appropriate use and interpretation.The field of landscape ecology has grown rapidly during this period, its concepts and methods have matured, and the published literature has increased exponentially. Landscape research has enhanced understanding of the causes and consequences of spatial heterogeneity and how these vary with scale, and they have influenced the management of natural and human-dominated landscapes. Landscape ecology is now co... [Read More] Data Analysis Best Practices
Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process.Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.Use the IPython shell and Jupyter notebook for exploratory computingLearn basic and advanced features in NumPy (Nu... [Read More] Data Analysis Best Practices
Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'... [Read More] Data Analysis Best Practices
Many researchers jump from data collection directly into testing hypothesis without realizing these tests can go profoundly wrong without clean data. This book provides a clear, accessible, step-by-step process of important best practices in preparing for Data Analysis Best Practices
Jason W. Osborne’s Best Practices in Logistic Regression provides students with an accessible, applied approach that communicates logistic regression in clear and concise terms. The book effectively leverages readers’ basic intuitive understanding of simple and multiple regression to guide them into a sophisticated mastery of logistic regression. Osborne’s applied approach offers students and instructors a clear perspective, elucidated through practical and engaging tools that encourage student comprehension. Data Analysis Best Practices
Transform your organization's data into actionable insights with Tableau Tableau is designed specifically to provide fast and easy visual analytics. The intuitive drag-and-drop interface helps you create interactive reports, dashboards, and visualizations, all without any special or advanced training. This all new edition of Tableau Your Data! is your Tableau companion, helping you get the most out of this invaluable business toolset.Tableau Your Data! shows you how to build dynamic, best of breed visualizations using the Tableau Software toolset. This comprehensive guide covers the core feature set for data analytics, and provides clear step-by-step guidance toward best practices and advanced techniques that go way beyond the user manual. You'll learn how Tableau is different from traditi... [Read More] Data Analysis Best Practices
Learn How to Properly Analyze Categorical DataAnalysis of Categorical Data with R presents a modern account of categorical data analysis using the popular R software. It covers recent techniques of model building and assessment for binary, multicategory, and count response variables and discusses fundamentals, such as odds ratio and probability estimation. The authors give detailed advice and guidelines on which procedures to use and why to use them. The Use of R as Both a Data Analysis Method and a Learning ToolRequiring no prior experience with R, the text offers an introduction to the essential features and functions of R. It incorporates numerous examples from medicine, psychology, sports, ecology, and other areas, along with extensive R code and output. The authors use data simulation... [Read More] Data Analysis Best Practices
Summary R in Action, Second Edition presents both the R language and the examples that make it so useful for business developers. Focusing on practical solutions, the book offers a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on time series analysis, cluster analysis, and classification methodologies, including decision trees, random forests, and support vector machines. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the TechnologyBusiness pros and researchers thr... [Read More] Data Analysis Best Practices
Modeling and Analysis of Compositional Data presents a practical and comprehensive introduction to the analysis of compositional data along with numerous examples to illustrate both theory and application of each method. Based upon short courses delivered by the authors, it provides a complete and current compendium of fundamental to advanced methodologies along with exercises at the end of each chapter to improve understanding, as well as data and a solutions manual which is available on an accompanying website. Complementing Pawlowsky-Glahn’s earlier collective text that provides an overview of the state-of-the-art in this field, Modeling and Analysis of Compositional Data fills a gap in the literature for a much-needed manual for teaching, self learning or consulting. Data Analysis Best Practices
This book is designed to help the managers and researchers in solving statistical problems using SPSS and to help them understand how they can use various statistical tools for their own research problems. SPSS is a very powerful and user friendly computer package for data analyses. It can take data from most other file-types and generate tables, charts, plots, and descriptive statistics, and conduct complex statistical analyses. This book will help students, business managers, academics as well as practicing researchers to solve statistical problems using the latest version of SPSS (16.0). After providing a brief overview of SPSS and basic Data Analysis Best Practices Books : STATISTICAL METHODS FOR PRACTICE & RESEA
Compositional Data Analysis in Practice is a user-oriented practical guide to the analysis of data with the property of a constant sum, for example percentages adding up to 100%. Compositional data can give misleading results if regular statistical methods are applied, and are best analysed by first transforming them to logarithms of ratios. This book explains how this transformation affects the analysis, results and interpretation of this very special type of data. All aspects of compositional data analysis are considered: visualization, modelling, dimension-reduction, clustering and variable selection, with many examples in the fields of food science, archaeology, sociology and biochemistry, Data Analysis Best Practices Compositional Data Analysis in Practice - eBook
This unique and informative paper was produced by the National Intelligence University / National Defense Intelligence College. Topics and subjects include: CIA analysis, internet and electronic media, analytical tradecraft, process management, U.S. Coast Guard, DIA, DODIIS, COLISEUM, JWICS, SIPRNET, OSIS, DITDS, HUGIN expert, ESRI, induction, deduction, and abduction.The title chosen for this book carries two meanings. The more straightforward interpretation of "Bringing Intelligence About,'' and the principal one, refers to the book's coverage of wide-ranging sources and methods employed to add value to national security-related information—to create "intelligence.'' A second meaning, not unrelated to the first, refers to the responsible Data Analysis Best Practices National Defense Intelligence College Paper: Bringing Intelligence About - Practitioners Reflect on Best Practices - CIA Analysis, Analytical Tradecraft, Process Management -
The definitive guide on the roles and responsibilities of the business analyst Business Analysis offers a complete description of the process of business analysis in solving business problems. Filled with tips, tricks, techniques, and guerilla tactics to help execute the process in the face of sometimes overwhelming political or social obstacles, this guide is also filled with real world stories from the author's more than thirty years of experience working as a business analyst. Provides techniques and tips to execute the at-times tricky job of business analyst Written by an industry expert with over thirty years of experience Straightforward and Data Analysis Best Practices The definitive guide on the roles and responsibilities of the business analyst Business Analysis offers a complete description of the process of business analysis in solving business problems. Filled with tips, tricks, techniques, and guerilla tactics to help execute the process in the face of sometimes overwhelming political or social obstacles, this guide is also filled with real world stories from the author's more than thirty years of experience working as a business analyst.Provides techniques and tips to execute the at-times tricky job of business analystWritten by an industry expert with over thirty years of experienceStraightforward and insightful, Business Analysis
Do you work with large and quickly-changing data sets, multiple data sources, a wide range of report/spreadsheet customers, and do you need to respond with increasing agility? In this advanced sess... Ignite2018,Be a data ninja: Best practices for analytics using Microsoft Excel - THR3017,Modern W...
The pandas library is a powerful tool for multiple phases of the data science workflow, including data cleaning, visualization, and exploratory data analysis. However, the size and complexity of th... python,pandas,data science,data analysis,tutorial
Join us to improve your Excel skills and make your spreadsheets more powerful! We cover formulas, data wrangling in the grid and with Power Query, visualizations, and more. mbas19,mbas2019,Microsoft Excel: Best practices for spreadsheet modeling data shaping and data - ...
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