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A guide for data managers and analyzers shares guidelines for identifying patterns, predicting future outcomes, and presenting findings to others; drawing on current research in cognitive science and learning theory while covering such additional topics as assessing data quality, handling ambiguous information, and organizing data within market groups. Original.
Do you use Excel for simple lists, but get confused and frustrated when it comes to actually doing something useful with all that data? Stop tearing your hair out: Head First Excel helps you painlessly move from spreadsheet dabbler to savvy user. Whether you're completely new to Excel or an experienced user looking to make the program work better for you, this book will help you incorporate Excel into every aspect of your workflow, from a scratch pad for data-based brainstorming to exploratory analysis with PivotTables, optimizing outcomes with Goal Seek, and presenting your conclusions with sophisticated data visualizations. Organize and clearly present information in a spreadsheet Make calculations across a number of worksheets Change your point of view with sorting, zooming, and filtering Manipulate numerical data to extract and use just what you need Leverage Excel as a grid-based layout program Write formulas for optimal functionality Nest formulas for more complex operations Create sophisticated data visualizations with charts and graphs Use Goal Seek to optimize possible outcomes based on different assumptions Create summaries from large data sets for exploratory data analysis with PivotTables We think your time is too valuable to waste struggling with new concepts. Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, Head First Excel uses a visually rich format designed for the way your brain works, rather than a text-heavy approach that will put you to sleep.
Want to learn the Python language without slogging your way through how-to manuals? With Head First Python, you’ll quickly grasp Python’s fundamentals, working with the built-in data structures and functions. Then you’ll move on to building your very own webapp, exploring database management, exception handling, and data wrangling. If you’re intrigued by what you can do with context managers, decorators, comprehensions, and generators, it’s all here. This second edition is a complete learning experience that will help you become a bonafide Python programmer in no time. Why does this book look so different? Based on the latest research in cognitive science and learning theory, Head First Pythonuses a visually rich format to engage your mind, rather than a text-heavy approach that puts you to sleep. Why waste your time struggling with new concepts? This multi-sensory learning experience is designed for the way your brain really works.
"Head First Statistics" brings a typically difficult subject to life, teaching readers everything they want and need to know about statistics through engaging, interactive, and thought-provoking material, full of puzzles, stories, quizzes, visual aids, and real-world examples.
The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics.
A dream come true for those looking to improve their datafluency Analytical data is a powerful tool for growing companies, butwhat good is it if it hides in the shadows? Bring your data to theforefront with effective visualization and communicationapproaches, and let Data Fluency: Empowering YourOrganization with Effective Communication show you thebest tools and strategies for getting the job done right. Learn thebest practices of data presentation and the ways that reporting anddashboards can help organizations effectively gauge performance,identify areas for improvement, and communicate results. Topics covered in the book include data reporting andcommunication, audience and user needs, data presentation tools,layout and styling, and common design failures. Those responsiblefor analytics, reporting, or BI implementation will find arefreshing take on data and visualization in this resource, as willreport, data visualization, and dashboard designers. Conquer the challenge of making valuable data approachable andeasy to understand Develop unique skills required to shape data to the needs ofdifferent audiences Full color book links to bonus content atjuiceanalytics.com Written by well-known and highly esteemed authors in the datapresentation community Data Fluency: Empowering Your Organization with EffectiveCommunication focuses on user experience, making reportsapproachable, and presenting data in a compelling, inspiring way.The book helps to dissolve the disconnect between your data andthose who might use it and can help make an impact on the peoplewho are most affected by data. Use Data Fluency today todevelop the skills necessary to turn data into effective displaysfor decision-making.
With the advent of the Web along with the unprecedented amount of information available in electronic format, conceptual data analysis is more useful and practical than ever, because this technology addresses important limitations of the systems that currently support users in their quest for information. Concept Data Analysis: Theory & Applications is the first book that provides a comprehensive treatment of the full range of algorithms available for conceptual data analysis, spanning creation, maintenance, display and manipulation of concept lattices. The accompanying website allows you to gain a greater understanding of the principles covered in the book through actively working on the topics discussed. The three main areas explored are interactive mining of documents or collections of documents (including Web documents), automatic text ranking, and rule mining from structured data. The potentials of conceptual data analysis in the application areas being considered are further illustrated by two detailed case studies. Concept Data Analysis: Theory & Applications is essential for researchers active in information processing and management and industry practitioners who are interested in creating a commercial product for conceptual data analysis or developing content management applications.

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