Practical Data Handling

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Practical Data Analysis in Chemistry

Author : Marcel Maeder
Publisher : Elsevier
ISBN 13 : 0080548830
Total Pages : 341 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Practical Data Analysis in Chemistry by : Marcel Maeder

Download or read book Practical Data Analysis in Chemistry written by Marcel Maeder and published by Elsevier. This book was released on 2007-08-10 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: The majority of modern instruments are computerised and provide incredible amounts of data. Methods that take advantage of the flood of data are now available; importantly they do not emulate 'graph paper analyses' on the computer. Modern computational methods are able to give us insights into data, but analysis or data fitting in chemistry requires the quantitative understanding of chemical processes. The results of this analysis allows the modelling and prediction of processes under new conditions, therefore saving on extensive experimentation. Practical Data Analysis in Chemistry exemplifies every aspect of theory applicable to data analysis using a short program in a Matlab or Excel spreadsheet, enabling the reader to study the programs, play with them and observe what happens. Suitable data are generated for each example in short routines, this ensuring a clear understanding of the data structure. Chapter 2 includes a brief introduction to matrix algebra and its implementation in Matlab and Excel while Chapter 3 covers the theory required for the modelling of chemical processes. This is followed by an introduction to linear and non-linear least-squares fitting, each demonstrated with typical applications. Finally Chapter 5 comprises a collection of several methods for model-free data analyses.* Includes a solid introduction to the simulation of equilibrium processes and the simulation of complex kinetic processes.* Provides examples of routines that are easily adapted to the processes investigated by the reader* 'Model-based' analysis (linear and non-linear regression) and 'model-free' analysis are covered

Principles of Statistical Data Handling

Author : Fred Davidson
Publisher : SAGE Publications, Incorporated
ISBN 13 :
Total Pages : 344 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Principles of Statistical Data Handling by : Fred Davidson

Download or read book Principles of Statistical Data Handling written by Fred Davidson and published by SAGE Publications, Incorporated. This book was released on 1996-04-09 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Principles of Statistical Data Handling is designed to help readers understand the principles of data handling so that they can make better use of computer data in research or study.

Handling Qualitative Data

Author : Lyn Richards
Publisher : SAGE
ISBN 13 : 1446242900
Total Pages : 233 pages
Book Rating : 4.4/5 (462 download)

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Book Synopsis Handling Qualitative Data by : Lyn Richards

Download or read book Handling Qualitative Data written by Lyn Richards and published by SAGE. This book was released on 2009-11-18 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lecturers, click here to request an e-inspection copy of this text This new edition of Lyn Richards' best-selling book provides an accessible introduction to qualitative research for students and practitioners. Recognizing that for many new researchers dealing with data is the main point of departure, this book helps them to acquire a progressive understanding of the skills and methodological issues that are central to qualitative research. Lyn Richards provides clear and pragmatic guidance on how to handle, reflect on and get results from small amounts of data, while at the same time showing how a consideration of methods and their philosophical underpinnings informs how we should best handle our data. This book also covers all the processes of making, meeting, sorting, coding, documenting and exploring qualitative data, smoothly integrating software use and the discussion of the main challenges that readers are likely to encounter. It guides novice researchers to achieve valid and useful outcomes from qualitative analysis, and to ensure they do justice to their data. This second edition features: - Increased coverage of issues about the researcher's relation to their data and ethical implications - An expanded section on preparing for data collection and reflecting on the nature of data. There is also a brand new website, offering: - Live, detailed case studies of qualitative methods in practice, linking to publications and illustrative material. Researchers tell the stories of projects, from design, through what was actually done with the data, to how analysis was achieved and reported; - A software guide with links to information and tutorials in several products.

Fundamentals and Analytical Applications of Multiway Calibration

Author :
Publisher : Elsevier
ISBN 13 : 0444635378
Total Pages : 612 pages
Book Rating : 4.4/5 (446 download)

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Book Synopsis Fundamentals and Analytical Applications of Multiway Calibration by :

Download or read book Fundamentals and Analytical Applications of Multiway Calibration written by and published by Elsevier. This book was released on 2015-08-10 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamentals and Analytical Applications of Multi-Way Calibration presents researchers with a set of effective tools they can use to obtain the maximum information from instrumental data. It includes the most advanced techniques, methods, and algorithms related to multi-way calibration and the ways they can be applied to solve actual analytical problems. This book provides a comprehensive coverage of the main aspects of multi-way analysis, including fundamentals and selected applications of chemometrics that can resolve complex analytical chemistry problems through the use of multi-way calibration. Includes the most advanced techniques, methods, and algorithms related to multi-way calibration and the ways they can be applied to solve actual analytical problems Presents researchers with a set of effective tools they can use to obtain the maximum information from instrumental data Provides comprehensive coverage of the main aspects of multi-way analysis, including fundamentals and selected applications of chemometrics

Data Handling and Analysis

Author : Andrew D. Blann
Publisher : Oxford University Press, USA
ISBN 13 : 0199667918
Total Pages : 205 pages
Book Rating : 4.1/5 (996 download)

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Book Synopsis Data Handling and Analysis by : Andrew D. Blann

Download or read book Data Handling and Analysis written by Andrew D. Blann and published by Oxford University Press, USA. This book was released on 2015 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Handling and Analysis provides a broad review of the quantitative skills needed to be an effective biomedical scientist.

Practical Data Analysis Cookbook

Author : Tomasz Drabas
Publisher : Packt Publishing Ltd
ISBN 13 : 1783558512
Total Pages : 384 pages
Book Rating : 4.7/5 (835 download)

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Book Synopsis Practical Data Analysis Cookbook by : Tomasz Drabas

Download or read book Practical Data Analysis Cookbook written by Tomasz Drabas and published by Packt Publishing Ltd. This book was released on 2016-04-29 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 60 practical recipes on data exploration and analysis About This Book Clean dirty data, extract accurate information, and explore the relationships between variables Forecast the output of an electric plant and the water flow of American rivers using pandas, NumPy, Statsmodels, and scikit-learn Find and extract the most important features from your dataset using the most efficient Python libraries Who This Book Is For If you are a beginner or intermediate-level professional who is looking to solve your day-to-day, analytical problems with Python, this book is for you. Even with no prior programming and data analytics experience, you will be able to finish each recipe and learn while doing so. What You Will Learn Read, clean, transform, and store your data usng Pandas and OpenRefine Understand your data and explore the relationships between variables using Pandas and D3.js Explore a variety of techniques to classify and cluster outbound marketing campaign calls data of a bank using Pandas, mlpy, NumPy, and Statsmodels Reduce the dimensionality of your dataset and extract the most important features with pandas, NumPy, and mlpy Predict the output of a power plant with regression models and forecast water flow of American rivers with time series methods using pandas, NumPy, Statsmodels, and scikit-learn Explore social interactions and identify fraudulent activities with graph theory concepts using NetworkX and Gephi Scrape Internet web pages using urlib and BeautifulSoup and get to know natural language processing techniques to classify movies ratings using NLTK Study simulation techniques in an example of a gas station with agent-based modeling In Detail Data analysis is the process of systematically applying statistical and logical techniques to describe and illustrate, condense and recap, and evaluate data. Its importance has been most visible in the sector of information and communication technologies. It is an employee asset in almost all economy sectors. This book provides a rich set of independent recipes that dive into the world of data analytics and modeling using a variety of approaches, tools, and algorithms. You will learn the basics of data handling and modeling, and will build your skills gradually toward more advanced topics such as simulations, raw text processing, social interactions analysis, and more. First, you will learn some easy-to-follow practical techniques on how to read, write, clean, reformat, explore, and understand your data—arguably the most time-consuming (and the most important) tasks for any data scientist. In the second section, different independent recipes delve into intermediate topics such as classification, clustering, predicting, and more. With the help of these easy-to-follow recipes, you will also learn techniques that can easily be expanded to solve other real-life problems such as building recommendation engines or predictive models. In the third section, you will explore more advanced topics: from the field of graph theory through natural language processing, discrete choice modeling to simulations. You will also get to expand your knowledge on identifying fraud origin with the help of a graph, scrape Internet websites, and classify movies based on their reviews. By the end of this book, you will be able to efficiently use the vast array of tools that the Python environment has to offer. Style and approach This hands-on recipe guide is divided into three sections that tackle and overcome real-world data modeling problems faced by data analysts/scientist in their everyday work. Each independent recipe is written in an easy-to-follow and step-by-step fashion.

Data-Handling in Biomedical Science

Author : Peter White
Publisher : Cambridge University Press
ISBN 13 : 1139488201
Total Pages : pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Data-Handling in Biomedical Science by : Peter White

Download or read book Data-Handling in Biomedical Science written by Peter White and published by Cambridge University Press. This book was released on 2010-05-06 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Packed with worked examples and problems, this book will help the reader improve their confidence and skill in data-handling. The mathematical methods needed for problem-solving are described in the first part of the book, with chapters covering topics such as indices, graphs and logarithms. The following eight chapters explore data-handling in different areas of microbiology and biochemistry including microbial growth, enzymes and radioactivity. Each chapter is fully illustrated with worked examples that provide a step-by-step guide to the solution of the most common problems. Over 30 exercises, ranging in difficulty and length, allow you to practise your skills and are accompanied by a full set of hints and solutions.

Practical Statistics for Nursing Using SPSS

Author : Herschel Knapp
Publisher : SAGE Publications
ISBN 13 : 1506325696
Total Pages : 387 pages
Book Rating : 4.5/5 (63 download)

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Book Synopsis Practical Statistics for Nursing Using SPSS by : Herschel Knapp

Download or read book Practical Statistics for Nursing Using SPSS written by Herschel Knapp and published by SAGE Publications. This book was released on 2016-03-24 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: A friendly and approachable guide to real-world statistics, Practical Statistics for Nursing Using SPSS® covers the most common statistical functions in nursing science using plain language. Students learn by doing, and an emphasis on this practical approach is seen throughout the book with each chapter structured to answer key questions: What statistical test should I use for this situation? How do I set up the data? How do I run the test? How do I interpret and document the results? Practice exercises include a vignette, codebook, and data sets ready for processing, enabling students to achieve mastery by carrying out actual statistical analyses. Online resources for students are available and include data sets for examples and exercises, fully developed solutions to all odd-numbered exercises, and thorough tutorial videos providing an overview of each statistical method, step-by-step guidance on SPSS® processing, and interpretation of results. Online resources for instructors include Microsoft® PowerPoint® slides for each chapter and solutions to all exercises.

Practical Real-time Data Processing and Analytics

Author : Shilpi Saxena
Publisher : Packt Publishing Ltd
ISBN 13 : 1787289869
Total Pages : 354 pages
Book Rating : 4.7/5 (872 download)

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Book Synopsis Practical Real-time Data Processing and Analytics by : Shilpi Saxena

Download or read book Practical Real-time Data Processing and Analytics written by Shilpi Saxena and published by Packt Publishing Ltd. This book was released on 2017-09-28 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to help you tackle different real-time data processing and analytics problems using the best tools for each scenario About This Book Learn about the various challenges in real-time data processing and use the right tools to overcome them This book covers popular tools and frameworks such as Spark, Flink, and Apache Storm to solve all your distributed processing problems A practical guide filled with examples, tips, and tricks to help you perform efficient Big Data processing in real-time Who This Book Is For If you are a Java developer who would like to be equipped with all the tools required to devise an end-to-end practical solution on real-time data streaming, then this book is for you. Basic knowledge of real-time processing would be helpful, and knowing the fundamentals of Maven, Shell, and Eclipse would be great. What You Will Learn Get an introduction to the established real-time stack Understand the key integration of all the components Get a thorough understanding of the basic building blocks for real-time solution designing Garnish the search and visualization aspects for your real-time solution Get conceptually and practically acquainted with real-time analytics Be well equipped to apply the knowledge and create your own solutions In Detail With the rise of Big Data, there is an increasing need to process large amounts of data continuously, with a shorter turnaround time. Real-time data processing involves continuous input, processing and output of data, with the condition that the time required for processing is as short as possible. This book covers the majority of the existing and evolving open source technology stack for real-time processing and analytics. You will get to know about all the real-time solution aspects, from the source to the presentation to persistence. Through this practical book, you'll be equipped with a clear understanding of how to solve challenges on your own. We'll cover topics such as how to set up components, basic executions, integrations, advanced use cases, alerts, and monitoring. You'll be exposed to the popular tools used in real-time processing today such as Apache Spark, Apache Flink, and Storm. Finally, you will put your knowledge to practical use by implementing all of the techniques in the form of a practical, real-world use case. By the end of this book, you will have a solid understanding of all the aspects of real-time data processing and analytics, and will know how to deploy the solutions in production environments in the best possible manner. Style and Approach In this practical guide to real-time analytics, each chapter begins with a basic high-level concept of the topic, followed by a practical, hands-on implementation of each concept, where you can see the working and execution of it. The book is written in a DIY style, with plenty of practical use cases, well-explained code examples, and relevant screenshots and diagrams.

A Practical Guide to Transforming Primary Mathematics

Author : Mike Askew
Publisher : Routledge
ISBN 13 : 131781326X
Total Pages : 185 pages
Book Rating : 4.3/5 (178 download)

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Book Synopsis A Practical Guide to Transforming Primary Mathematics by : Mike Askew

Download or read book A Practical Guide to Transforming Primary Mathematics written by Mike Askew and published by Routledge. This book was released on 2015-07-30 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Practical Guide to Transforming Primary Mathematics offers inspiration and ideas for all training and practising teachers committed to making mathematics enjoyable, inclusive, engaging and successful. The companion to Mike Askew’s bestselling book, Transforming Primary Mathematics, this practical guide focuses on showing you how to unlock the powerful potential of a small set of consistent principles and practices, known as the teaching tripod, to develop a coherent approach to teaching mathematics. Organised around the major strands of the curriculum - number, calculations, shape and space, measures, and data handling – it offers an accessible introduction to the teaching tripod, a careful choice of tasks, supported by a range of tools that extend our natural abilities and held together by careful attention to classroom talk. A range of classroom tasks, each including key learning outcomes, clear links to the framework, links to relevant research, and suggestions for making the tasks easier or harder, are offered for every topic, helping you plan units of work for meaningful learning. A Practical Guide to Transforming Primary Mathematics offers all teachers a vision, rationale and ideas for how teaching can support better learning of mathematics but also encourage learners to see themselves as being capable of learning mathematics, and wanting to learn it.

A Data Scientist's Guide to Acquiring, Cleaning, and Managing Data in R

Author : Samuel E. Buttrey
Publisher : John Wiley & Sons
ISBN 13 : 1119080029
Total Pages : 310 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis A Data Scientist's Guide to Acquiring, Cleaning, and Managing Data in R by : Samuel E. Buttrey

Download or read book A Data Scientist's Guide to Acquiring, Cleaning, and Managing Data in R written by Samuel E. Buttrey and published by John Wiley & Sons. This book was released on 2017-12-18 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: The only how-to guide offering a unified, systemic approach to acquiring, cleaning, and managing data in R Every experienced practitioner knows that preparing data for modeling is a painstaking, time-consuming process. Adding to the difficulty is that most modelers learn the steps involved in cleaning and managing data piecemeal, often on the fly, or they develop their own ad hoc methods. This book helps simplify their task by providing a unified, systematic approach to acquiring, modeling, manipulating, cleaning, and maintaining data in R. Starting with the very basics, data scientists Samuel E. Buttrey and Lyn R. Whitaker walk readers through the entire process. From what data looks like and what it should look like, they progress through all the steps involved in getting data ready for modeling. They describe best practices for acquiring data from numerous sources; explore key issues in data handling, including text/regular expressions, big data, parallel processing, merging, matching, and checking for duplicates; and outline highly efficient and reliable techniques for documenting data and recordkeeping, including audit trails, getting data back out of R, and more. The only single-source guide to R data and its preparation, it describes best practices for acquiring, manipulating, cleaning, and maintaining data Begins with the basics and walks readers through all the steps necessary to get data ready for the modeling process Provides expert guidance on how to document the processes described so that they are reproducible Written by seasoned professionals, it provides both introductory and advanced techniques Features case studies with supporting data and R code, hosted on a companion website A Data Scientist's Guide to Acquiring, Cleaning and Managing Data in R is a valuable working resource/bench manual for practitioners who collect and analyze data, lab scientists and research associates of all levels of experience, and graduate-level data mining students.

Data Analysis Methods in Physical Oceanography

Author : Richard E. Thomson
Publisher : Elsevier
ISBN 13 : 0080477003
Total Pages : 654 pages
Book Rating : 4.0/5 (84 download)

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Book Synopsis Data Analysis Methods in Physical Oceanography by : Richard E. Thomson

Download or read book Data Analysis Methods in Physical Oceanography written by Richard E. Thomson and published by Elsevier. This book was released on 2001-04-03 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analysis Methods in Physical Oceanography is a practical referenceguide to established and modern data analysis techniques in earth and oceansciences. This second and revised edition is even more comprehensive with numerous updates, and an additional appendix on 'Convolution and Fourier transforms'. Intended for both students and established scientists, the fivemajor chapters of the book cover data acquisition and recording, dataprocessing and presentation, statistical methods and error handling,analysis of spatial data fields, and time series analysis methods. Chapter 5on time series analysis is a book in itself, spanning a wide diversity oftopics from stochastic processes and stationarity, coherence functions,Fourier analysis, tidal harmonic analysis, spectral and cross-spectralanalysis, wavelet and other related methods for processing nonstationarydata series, digital filters, and fractals. The seven appendices includeunit conversions, approximation methods and nondimensional numbers used ingeophysical fluid dynamics, presentations on convolution, statisticalterminology, and distribution functions, and a number of importantstatistical tables. Twenty pages are devoted to references. Featuring:• An in-depth presentation of modern techniques for the analysis of temporal and spatial data sets collected in oceanography, geophysics, and other disciplines in earth and ocean sciences.• A detailed overview of oceanographic instrumentation and sensors - old and new - used to collect oceanographic data.• 7 appendices especially applicable to earth and ocean sciences ranging from conversion of units, through statistical tables, to terminology and non-dimensional parameters. In praise of the first edition: "(...)This is a very practical guide to the various statistical analysis methods used for obtaining information from geophysical data, with particular reference to oceanography(...)The book provides both a text for advanced students of the geophysical sciences and a useful reference volume for researchers." Aslib Book Guide Vol 63, No. 9, 1998 "(...)This is an excellent book that I recommend highly and will definitely use for my own research and teaching." EOS Transactions, D.A. Jay, 1999 "(...)In summary, this book is the most comprehensive and practical source of information on data analysis methods available to the physical oceanographer. The reader gets the benefit of extremely broad coverage and an excellent set of examples drawn from geographical observations." Oceanography, Vol. 12, No. 3, A. Plueddemann, 1999 "(...)Data Analysis Methods in Physical Oceanography is highly recommended for a wide range of readers, from the relative novice to the experienced researcher. It would be appropriate for academic and special libraries." E-Streams, Vol. 2, No. 8, P. Mofjelf, August 1999

Knowledge Graphs and Big Data Processing

Author : Valentina Janev
Publisher : Springer Nature
ISBN 13 : 3030531996
Total Pages : 212 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Knowledge Graphs and Big Data Processing by : Valentina Janev

Download or read book Knowledge Graphs and Big Data Processing written by Valentina Janev and published by Springer Nature. This book was released on 2020-07-15 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.

A Practical Guide to Transforming Primary Mathematics

Author : Mike Askew
Publisher : Routledge
ISBN 13 : 1317813251
Total Pages : 299 pages
Book Rating : 4.3/5 (178 download)

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Book Synopsis A Practical Guide to Transforming Primary Mathematics by : Mike Askew

Download or read book A Practical Guide to Transforming Primary Mathematics written by Mike Askew and published by Routledge. This book was released on 2015-07-30 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Practical Guide to Transforming Primary Mathematics offers inspiration and ideas for all training and practising teachers committed to making mathematics enjoyable, inclusive, engaging and successful. The companion to Mike Askew’s bestselling book, Transforming Primary Mathematics, this practical guide focuses on showing you how to unlock the powerful potential of a small set of consistent principles and practices, known as the teaching tripod, to develop a coherent approach to teaching mathematics. Organised around the major strands of the curriculum - number, calculations, shape and space, measures, and data handling – it offers an accessible introduction to the teaching tripod, a careful choice of tasks, supported by a range of tools that extend our natural abilities and held together by careful attention to classroom talk. A range of classroom tasks, each including key learning outcomes, clear links to the framework, links to relevant research, and suggestions for making the tasks easier or harder, are offered for every topic, helping you plan units of work for meaningful learning. A Practical Guide to Transforming Primary Mathematics offers all teachers a vision, rationale and ideas for how teaching can support better learning of mathematics but also encourage learners to see themselves as being capable of learning mathematics, and wanting to learn it.

Machine Learning with Python Cookbook

Author : Chris Albon
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491989335
Total Pages : 285 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Machine Learning with Python Cookbook by : Chris Albon

Download or read book Machine Learning with Python Cookbook written by Chris Albon and published by "O'Reilly Media, Inc.". This book was released on 2018-03-09 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or numerical data, model selection, and dimensionality reduction and many other topics. Each recipe includes code that you can copy and paste into a toy dataset to ensure that it actually works. From there, you can insert, combine, or adapt the code to help construct your application. Recipes also include a discussion that explains the solution and provides meaningful context. This cookbook takes you beyond theory and concepts by providing the nuts and bolts you need to construct working machine learning applications. You’ll find recipes for: Vectors, matrices, and arrays Handling numerical and categorical data, text, images, and dates and times Dimensionality reduction using feature extraction or feature selection Model evaluation and selection Linear and logical regression, trees and forests, and k-nearest neighbors Support vector machines (SVM), naïve Bayes, clustering, and neural networks Saving and loading trained models

Practical Enterprise Data Lake Insights

Author : Saurabh Gupta
Publisher : Apress
ISBN 13 : 1484235223
Total Pages : 335 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Practical Enterprise Data Lake Insights by : Saurabh Gupta

Download or read book Practical Enterprise Data Lake Insights written by Saurabh Gupta and published by Apress. This book was released on 2018-07-29 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use this practical guide to successfully handle the challenges encountered when designing an enterprise data lake and learn industry best practices to resolve issues. When designing an enterprise data lake you often hit a roadblock when you must leave the comfort of the relational world and learn the nuances of handling non-relational data. Starting from sourcing data into the Hadoop ecosystem, you will go through stages that can bring up tough questions such as data processing, data querying, and security. Concepts such as change data capture and data streaming are covered. The book takes an end-to-end solution approach in a data lake environment that includes data security, high availability, data processing, data streaming, and more. Each chapter includes application of a concept, code snippets, and use case demonstrations to provide you with a practical approach. You will learn the concept, scope, application, and starting point. What You'll Learn Get to know data lake architecture and design principles Implement data capture and streaming strategies Implement data processing strategies in Hadoop Understand the data lake security framework and availability model Who This Book Is For Big data architects and solution architects

Practical Handbook of Spatial Statistics

Author : Sandra Arlinghaus
Publisher : CRC Press
ISBN 13 : 1000144321
Total Pages : 328 pages
Book Rating : 4.0/5 (1 download)

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Book Synopsis Practical Handbook of Spatial Statistics by : Sandra Arlinghaus

Download or read book Practical Handbook of Spatial Statistics written by Sandra Arlinghaus and published by CRC Press. This book was released on 2020-08-27 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: The guidance and special techniques provided in this handbook will allow you to understand and use complex spatial statistical techniques. You will learn how to apply proper spatial analysis techniques and why they are generally different from conventional statistical analyses. Clear and concise information on weighting, aggregation effects, sampling, spatial statistics and GIS, and visualization of spatial dependence is provided. Discussions on specific applications using actual data sets fill obvious gaps in the literature, and coverage of critical research frontiers allows readers to explore current areas of active research.