Data Analytics Using Open Source Tools

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Data Analysis with Open Source Tools

Author : Philipp K. Janert
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 9781449396657
Total Pages : 540 pages
Book Rating : 4.3/5 (966 download)

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Book Synopsis Data Analysis with Open Source Tools by : Philipp K. Janert

Download or read book Data Analysis with Open Source Tools written by Philipp K. Janert and published by "O'Reilly Media, Inc.". This book was released on 2010-11-11 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: Collecting data is relatively easy, but turning raw information into something useful requires that you know how to extract precisely what you need. With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications. Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you. Use graphics to describe data with one, two, or dozens of variables Develop conceptual models using back-of-the-envelope calculations, as well asscaling and probability arguments Mine data with computationally intensive methods such as simulation and clustering Make your conclusions understandable through reports, dashboards, and other metrics programs Understand financial calculations, including the time-value of money Use dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situations Become familiar with different open source programming environments for data analysis "Finally, a concise reference for understanding how to conquer piles of data."--Austin King, Senior Web Developer, Mozilla "An indispensable text for aspiring data scientists."--Michael E. Driscoll, CEO/Founder, Dataspora

Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities

Author : Segall, Richard S.
Publisher : IGI Global
ISBN 13 : 1799827704
Total Pages : 237 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities by : Segall, Richard S.

Download or read book Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities written by Segall, Richard S. and published by IGI Global. This book was released on 2020-02-21 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the development of computing technologies in today’s modernized world, software packages have become easily accessible. Open source software, specifically, is a popular method for solving certain issues in the field of computer science. One key challenge is analyzing big data due to the high amounts that organizations are processing. Researchers and professionals need research on the foundations of open source software programs and how they can successfully analyze statistical data. Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. Featuring coverage on a broad range of topics such as cluster analysis, time series forecasting, and machine learning, this book is ideally designed for researchers, developers, practitioners, engineers, academicians, scholars, and students who want to more fully understand in a brief and concise format the realm and technologies of open source software for big data and how it has been used to solve large-scale research problems in a multitude of disciplines.

Practical Data Analysis

Author : Dhiraj Bhuyan
Publisher : Dhiraj Bhuyan
ISBN 13 :
Total Pages : 323 pages
Book Rating : 4./5 ( download)

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Book Synopsis Practical Data Analysis by : Dhiraj Bhuyan

Download or read book Practical Data Analysis written by Dhiraj Bhuyan and published by Dhiraj Bhuyan. This book was released on 2019-11-30 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Practical Data Analysis – Using Python & Open Source Technology” uses a case-study based approach to explore some of the real-world applications of open source data analysis tools and techniques. Specifically, the following topics are covered in this book: 1. Open Source Data Analysis Tools and Techniques. 2. A Beginner’s Guide to “Python” for Data Analysis. 3. Implementing Custom Search Engines On The Fly. 4. Visualising Missing Data. 5. Sentiment Analysis and Named Entity Recognition. 6. Automatic Document Classification, Clustering and Summarisation. 7. Fraud Detection Using Machine Learning Techniques. 8. Forecasting - Using Data to Map the Future. 9. Continuous Monitoring and Real-Time Analytics. 10. Creating a Robot for Interacting with Web Applications. Free samples of the book is available at - http://timesofdatascience.com

Data Analytics Using Open-Source Tools

Author : Jeffrey Strickland
Publisher : Lulu.com
ISBN 13 : 1365213846
Total Pages : 708 pages
Book Rating : 4.3/5 (652 download)

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Book Synopsis Data Analytics Using Open-Source Tools by : Jeffrey Strickland

Download or read book Data Analytics Using Open-Source Tools written by Jeffrey Strickland and published by Lulu.com. This book was released on 2016-07 with total page 708 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about using open-source tools in data analytics. The book covers several subjects, including descriptive and predictive modeling, gradient boosting, cluster modeling, logistic regression, and artificial neural networks, among other topics.

Foundations for Architecting Data Solutions

Author : Ted Malaska
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492038695
Total Pages : 190 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Foundations for Architecting Data Solutions by : Ted Malaska

Download or read book Foundations for Architecting Data Solutions written by Ted Malaska and published by "O'Reilly Media, Inc.". This book was released on 2018-08-29 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: While many companies ponder implementation details such as distributed processing engines and algorithms for data analysis, this practical book takes a much wider view of big data development, starting with initial planning and moving diligently toward execution. Authors Ted Malaska and Jonathan Seidman guide you through the major components necessary to start, architect, and develop successful big data projects. Everyone from CIOs and COOs to lead architects and developers will explore a variety of big data architectures and applications, from massive data pipelines to web-scale applications. Each chapter addresses a piece of the software development life cycle and identifies patterns to maximize long-term success throughout the life of your project. Start the planning process by considering the key data project types Use guidelines to evaluate and select data management solutions Reduce risk related to technology, your team, and vague requirements Explore system interface design using APIs, REST, and pub/sub systems Choose the right distributed storage system for your big data system Plan and implement metadata collections for your data architecture Use data pipelines to ensure data integrity from source to final storage Evaluate the attributes of various engines for processing the data you collect

Guidelines for Preparing Patent Landscape Reports

Author : World Intellectual Property Organization
Publisher : WIPO
ISBN 13 : 9280525298
Total Pages : 131 pages
Book Rating : 4.2/5 (85 download)

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Book Synopsis Guidelines for Preparing Patent Landscape Reports by : World Intellectual Property Organization

Download or read book Guidelines for Preparing Patent Landscape Reports written by World Intellectual Property Organization and published by WIPO. This book was released on 2015-08-24 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: These Guidelines are designed both for general users of patent information, as well as for those involved in producing Patent Landscape Reports (PLRs). They provide step-by-step instructions on how to prepare a PLR, as well as background information such as objectives, patent analytics, concepts and frameworks.

Building Open Source Network Security Tools

Author : Mike Schiffman
Publisher : John Wiley & Sons
ISBN 13 : 0471445452
Total Pages : 450 pages
Book Rating : 4.4/5 (714 download)

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Book Synopsis Building Open Source Network Security Tools by : Mike Schiffman

Download or read book Building Open Source Network Security Tools written by Mike Schiffman and published by John Wiley & Sons. This book was released on 2002-12-03 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to protect your network with this guide to building complete and fully functional network security tools Although open source network security tools come in all shapes and sizes, a company will eventually discover that these tools are lacking in some area—whether it's additional functionality, a specific feature, or a narrower scope. Written by security expert Mike Schiffman, this comprehensive book will show you how to build your own network security tools that meet the needs of your company. To accomplish this, you'll first learn about the Network Security Tool Paradigm in addition to currently available components including libpcap, libnet, libnids, libsf, libdnet, and OpenSSL. Schiffman offers a detailed discussion of these components, helping you gain a better understanding of the native datatypes and exported functions. Next, you'll find several key techniques that are built from the components as well as easy-to-parse programming examples. The book then ties the model, code, and concepts together, explaining how you can use this information to craft intricate and robust security programs. Schiffman provides you with cost-effective, time-saving guidance on how to build customized network security tools using existing components. He explores: A multilayered model for describing network security tools The ins and outs of several specific security-related components How to combine these components into several useful network security techniques Four different classifications for network security tools: passive reconnaissance, active reconnaissance, attack and penetration, and defensive How to combine techniques to build customized network security tools The companion Web site contains all of the code from the book.

Open Source Software in Life Science Research

Author : Lee Harland
Publisher : Elsevier
ISBN 13 : 1908818247
Total Pages : 583 pages
Book Rating : 4.9/5 (88 download)

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Book Synopsis Open Source Software in Life Science Research by : Lee Harland

Download or read book Open Source Software in Life Science Research written by Lee Harland and published by Elsevier. This book was released on 2012-10-31 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: The free/open source approach has grown from a minor activity to become a significant producer of robust, task-orientated software for a wide variety of situations and applications. To life science informatics groups, these systems present an appealing proposition - high quality software at a very attractive price. Open source software in life science research considers how industry and applied research groups have embraced these resources, discussing practical implementations that address real-world business problems. The book is divided into four parts. Part one looks at laboratory data management and chemical informatics, covering software such as Bioclipse, OpenTox, ImageJ and KNIME. In part two, the focus turns to genomics and bioinformatics tools, with chapters examining GenomicsTools and EBI Atlas software, as well as the practicalities of setting up an ‘omics’ platform and managing large volumes of data. Chapters in part three examine information and knowledge management, covering a range of topics including software for web-based collaboration, open source search and visualisation technologies for scientific business applications, and specific software such as DesignTracker and Utopia Documents. Part four looks at semantic technologies such as Semantic MediaWiki, TripleMap and Chem2Bio2RDF, before part five examines clinical analytics, and validation and regulatory compliance of free/open source software. Finally, the book concludes by looking at future perspectives and the economics and free/open source software in industry. Discusses a broad range of applications from a variety of sectors Provides a unique perspective on work normally performed behind closed doors Highlights the criteria used to compare and assess different approaches to solving problems

Open Source Data Warehousing and Business Intelligence

Author : Lakshman Bulusu
Publisher : CRC Press
ISBN 13 : 1466578769
Total Pages : 430 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Open Source Data Warehousing and Business Intelligence by : Lakshman Bulusu

Download or read book Open Source Data Warehousing and Business Intelligence written by Lakshman Bulusu and published by CRC Press. This book was released on 2012-08-06 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Open Source Data Warehousing and Business Intelligence is an all-in-one reference for developing open source based data warehousing (DW) and business intelligence (BI) solutions that are business-centric, cross-customer viable, cross-functional, cross-technology based, and enterprise-wide. Considering the entire lifecycle of an open source DW &

Practical Data Analysis

Author : Hector Cuesta
Publisher : Packt Publishing Ltd
ISBN 13 : 1785286668
Total Pages : 338 pages
Book Rating : 4.7/5 (852 download)

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Book Synopsis Practical Data Analysis by : Hector Cuesta

Download or read book Practical Data Analysis written by Hector Cuesta and published by Packt Publishing Ltd. This book was released on 2016-09-30 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache Spark About This Book Learn to use various data analysis tools and algorithms to classify, cluster, visualize, simulate, and forecast your data Apply Machine Learning algorithms to different kinds of data such as social networks, time series, and images A hands-on guide to understanding the nature of data and how to turn it into insight Who This Book Is For This book is for developers who want to implement data analysis and data-driven algorithms in a practical way. It is also suitable for those without a background in data analysis or data processing. Basic knowledge of Python programming, statistics, and linear algebra is assumed. What You Will Learn Acquire, format, and visualize your data Build an image-similarity search engine Generate meaningful visualizations anyone can understand Get started with analyzing social network graphs Find out how to implement sentiment text analysis Install data analysis tools such as Pandas, MongoDB, and Apache Spark Get to grips with Apache Spark Implement machine learning algorithms such as classification or forecasting In Detail Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you'll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark. Style and approach This is a hands-on guide to data analysis and data processing. The concrete examples are explained with simple code and accessible data.

Data Analytics in Marketing, Entrepreneurship, and Innovation

Author : Mounir Kehal
Publisher : CRC Press
ISBN 13 : 0429591683
Total Pages : 193 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Data Analytics in Marketing, Entrepreneurship, and Innovation by : Mounir Kehal

Download or read book Data Analytics in Marketing, Entrepreneurship, and Innovation written by Mounir Kehal and published by CRC Press. This book was released on 2021-01-12 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Innovation based in data analytics is a contemporary approach to developing empirically supported advances that encourage entrepreneurial activity inspired by novel marketing inferences. Data Analytics in Marketing, Entrepreneurship, and Innovation covers techniques, processes, models, tools, and practices for creating business opportunities through data analytics. It features case studies that provide realistic examples of applications. This multifaceted examination of data analytics looks at: Business analytics Applying predictive analytics Using discrete choice analysis for decision-making Marketing and customer analytics Developing new products Technopreneurship Disruptive versus incremental innovation The book gives researchers and practitioners insight into how data analytics is used in the areas of innovation, entrepreneurship, and marketing. Innovation analytics helps identify opportunities to develop new products and services, and improve existing methods of product manufacturing and service delivery. Entrepreneurial analytics facilitates the transformation of innovative ideas into strategy and helps entrepreneurs make critical decisions based on data-driven techniques. Marketing analytics is used in collecting, managing, assessing, and analyzing marketing data to predict trends, investigate customer preferences, and launch campaigns.

IoT Data Analytics using Python

Author : M S Hariharan
Publisher : BPB Publications
ISBN 13 : 9355515758
Total Pages : 303 pages
Book Rating : 4.3/5 (555 download)

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Book Synopsis IoT Data Analytics using Python by : M S Hariharan

Download or read book IoT Data Analytics using Python written by M S Hariharan and published by BPB Publications. This book was released on 2023-10-23 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: Harness the power of Python to analyze your IoT data KEY FEATURES ● Learn how to build an IoT Data Analytics infrastructure. ● Explore advanced techniques for IoT Data Analysis with Python. ● Gain hands-on experience applying IoT Data Analytics to real-world situations. DESCRIPTION Python is a popular programming language for data analytics, and it is also well-suited for IoT Data Analytics. By leveraging Python's versatility and its rich ecosystem of libraries and tools, Data Analytics for IoT can unlock valuable insights, enable predictive capabilities, and optimize decision-making in various IoT applications and domains. The book begins with a foundation in IoT fundamentals, its role in digital transformation, and why Python is the preferred language for IoT Data Analytics. It then covers essential data analytics concepts, how to establish an IoT Data Analytics environment, and how to design and manage real-time IoT data flows. Next, the book discusses how to implement Descriptive Analytics with Pandas, Time Series Forecasting with Python libraries, and Monitoring, Preventive Maintenance, Optimization, Text Mining, and Automation strategies. It also introduces Edge Computing and Analytics, discusses Continuous and Adaptive Learning concepts, and explores data flow and use cases for Edge Analytics. Finally, the book concludes with a chapter on IoT Data Analytics for self-driving cars, using the CRISP-DM framework for data collection, modeling, and deployment. By the end of the book, you will be equipped with the skills and knowledge needed to extract valuable insights from IoT data and build real-world applications. WHAT YOU WILL LEARN ● Explore the essentials of IoT Data Analytics and the Industry 4.0 revolution. ● Learn how to set up the IoT Data Analytics environment. ● Equip Python developers with data analysis foundations. ● Learn to build data lakes for real-time IoT data streaming. ● Learn to deploy machine learning models on edge devices. ● Understand Edge Computing with MicroPython for efficient IoT Data Analytics. WHO THIS BOOK IS FOR If you are an experienced Python developer who wants to master IoT Data Analytics, or a newcomer who wants to learn Python and its applications in IoT, this book will give you a thorough understanding of IoT Data Analytics and practical skills for real-world use cases. TABLE OF CONTENTS 1. Necessity of Analytics Across IoT 2. Up and Running with Data Analytics Fundamentals 3. Setting Up IoT Analytics Environment 4. Managing Data Pipeline and Cleaning 5. Designing Data Lake and Executing Data Transformation 6. Implementing Descriptive Analytics Using Pandas 7. Time Series Forecasting and Predictions 8. Monitoring and Preventive Maintenance 9. Model Deployment on Edge Devices 10. Understanding Edge Computing with MicroPython 11. IoT Analytics for Self-driving Vehicles

Data Science Applications using R

Author : Jeffrey Strickland
Publisher : Lulu.com
ISBN 13 : 035981042X
Total Pages : 434 pages
Book Rating : 4.3/5 (598 download)

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Book Synopsis Data Science Applications using R by : Jeffrey Strickland

Download or read book Data Science Applications using R written by Jeffrey Strickland and published by Lulu.com. This book was released on 2019-11-13 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: To write a single book about data science, at least as I view the discipline, would result in several volumes. I have come to view Data Science as a multidisciplinary field. People who engage in data science may be statisticians, economists, mathematicians, operations research analysts, and a myriad of other scientific professionals. Most would agree that data scientist have advance degrees in one or more of these disciplines. All practitioners would agree that Data is at center stage. This book is intended to demonstrate the multidisciplinary application of data science, using R-programming with R Studio.

Big Data Analytics

Author : Arun K. Somani
Publisher : CRC Press
ISBN 13 : 1315391244
Total Pages : 484 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Big Data Analytics by : Arun K. Somani

Download or read book Big Data Analytics written by Arun K. Somani and published by CRC Press. This book was released on 2017-10-30 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proposed book will discuss various aspects of big data Analytics. It will deliberate upon the tools, technology, applications, use cases and research directions in the field. Chapters would be contributed by researchers, scientist and practitioners from various reputed universities and organizations for the benefit of readers.

R for Data Science

Author : Hadley Wickham
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491910364
Total Pages : 521 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis R for Data Science by : Hadley Wickham

Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

Managerial Perspectives on Intelligent Big Data Analytics

Author : Sun, Zhaohao
Publisher : IGI Global
ISBN 13 : 1522572783
Total Pages : 335 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Managerial Perspectives on Intelligent Big Data Analytics by : Sun, Zhaohao

Download or read book Managerial Perspectives on Intelligent Big Data Analytics written by Sun, Zhaohao and published by IGI Global. This book was released on 2019-02-22 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data, analytics, and artificial intelligence are revolutionizing work, management, and lifestyles and are becoming disruptive technologies for healthcare, e-commerce, and web services. However, many fundamental, technological, and managerial issues for developing and applying intelligent big data analytics in these fields have yet to be addressed. Managerial Perspectives on Intelligent Big Data Analytics is a collection of innovative research that discusses the integration and application of artificial intelligence, business intelligence, digital transformation, and intelligent big data analytics from a perspective of computing, service, and management. While highlighting topics including e-commerce, machine learning, and fuzzy logic, this book is ideally designed for students, government officials, data scientists, managers, consultants, analysts, IT specialists, academicians, researchers, and industry professionals in fields that include big data, artificial intelligence, computing, and commerce.

Agile Business Architecture for Digital Transformation

Author : Dr Mehmet Yildiz
Publisher : Digitalmehmet
ISBN 13 :
Total Pages : 178 pages
Book Rating : 4./5 ( download)

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Book Synopsis Agile Business Architecture for Digital Transformation by : Dr Mehmet Yildiz

Download or read book Agile Business Architecture for Digital Transformation written by Dr Mehmet Yildiz and published by Digitalmehmet. This book was released on 2021-05-01 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are in a frenetic and a convoluted digital age. Every organisation strives to transform its business to stay competitive in this exponentially growing digital world. Digital transformation became pervasive and ubiquitous in all business ventures. This new norm of constant transformation requires architecting our business and underlying technology stacks rapidly. Establishing agile business architecture frameworks are fundamental requirements to achieve successful digital transformation outcomes. In this book, I attempt to share my knowledge and experience using a rigorous yet agile architectural method. My aim is to add accelerated value to the broader business architecture and digital transformation communities by focusing on the practical aspect with minimal emphasis on the theoretical aspect. The content in this book is based on my architectural thought leadership experience gained in multiple large business and enterprise architecture initiatives, focusing on business capabilities, digital transformation initiatives, and enterprise modernisation engagements, reflecting hard lessons learned in these applied settings. In this book I attempt to redefine the role of business architects as primary leaders for digital transformation programs. The content reflects my experience and observations from the field. As a caveat, this book is not based on theories in the traditional business architecture textbooks which may conflict with my experience. My beta readers found this as a unique guide reflecting reality from the field. Hope it adds new insights for your role in the business digital transformation initiatives.