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 534 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

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.

Download or read book Data Analytics Using Open Source Tools written by Jeffrey Strickland and published by Lulu.com. This book was released on 2016-07-20 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.

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

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.

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.

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

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.

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.

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

Download or read book Open Source Software for Statistical Analysis of Big Data written by Richard Segall and published by Engineering Science Reference. This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book explores topics in the field of open source software for big data"--

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 357 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.

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.

Download or read book Network Data Analytics written by K. G. Srinivasa and published by Springer. This book was released on 2018-04-26 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: In order to carry out data analytics, we need powerful and flexible computing software. However the software available for data analytics is often proprietary and can be expensive. This book reviews Apache tools, which are open source and easy to use. After providing an overview of the background of data analytics, covering the different types of analysis and the basics of using Hadoop as a tool, it focuses on different Hadoop ecosystem tools, like Apache Flume, Apache Spark, Apache Storm, Apache Hive, R, and Python, which can be used for different types of analysis. It then examines the different machine learning techniques that are useful for data analytics, and how to visualize data with different graphs and charts. Presenting data analytics from a practice-oriented viewpoint, the book discusses useful tools and approaches for data analytics, supported by concrete code examples. The book is a valuable reference resource for graduate students and professionals in related fields, and is also of interest to general readers with an understanding of data analytics.

Download or read book Systems Engineering Using the DEJI Systems Model written by Adedeji B. Badiru and published by CRC Press. This book was released on 2022-08-29 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: While we need to work more with a systems approach, there are few books that provide systems engineering theory and applications. This book presents a comprehensive collection of systems engineering models. Each of the models is fully covered with guidelines of how and why to use them, along with case studies. Systems Engineering Using the DEJI Systems Model®: Evaluation, Justification, and Integration with Case Studies and Applications provides systems integration as a unifying platform for systems of systems and presents a structured model for systems applications and explicit treatment of human-in-the-loop systems. It discusses systems design in detail and covers the justification methodologies along with examples. Systems evaluation tools and techniques are also included with a discussion on how engineering education is playing a major role for systems advancement. Practicing professionals, as well as educational institutions, governments, businesses, and industries, will find this book of interest.

Download or read book Practical Business Analytics Using SAS written by Shailendra Kadre and published by Apress. This book was released on 2015-02-07 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Business Analytics Using SAS: A Hands-on Guide shows SAS users and businesspeople how to analyze data effectively in real-life business scenarios. The book begins with an introduction to analytics, analytical tools, and SAS programming. The authors—both SAS, statistics, analytics, and big data experts—first show how SAS is used in business, and then how to get started programming in SAS by importing data and learning how to manipulate it. Besides illustrating SAS basic functions, you will see how each function can be used to get the information you need to improve business performance. Each chapter offers hands-on exercises drawn from real business situations. The book then provides an overview of statistics, as well as instruction on exploring data, preparing it for analysis, and testing hypotheses. You will learn how to use SAS to perform analytics and model using both basic and advanced techniques like multiple regression, logistic regression, and time series analysis, among other topics. The book concludes with a chapter on analyzing big data. Illustrations from banking and other industries make the principles and methods come to life. Readers will find just enough theory to understand the practical examples and case studies, which cover all industries. Written for a corporate IT and programming audience that wants to upgrade skills or enter the analytics field, this book includes: More than 200 examples and exercises, including code and datasets for practice. Relevant examples for all industries. Case studies that show how to use SAS analytics to identify opportunities, solve complicated problems, and chart a course. Practical Business Analytics Using SAS: A Hands-on Guide gives you the tools you need to gain insight into the data at your fingertips, predict business conditions for better planning, and make excellent decisions. Whether you are in retail, finance, healthcare, manufacturing, government, or any other industry, this book will help your organization increase revenue, drive down costs, improve marketing, and satisfy customers better than ever before.

Download or read book Wiley CIA Exam Review 2021 Part 1 written by S. Rao Vallabhaneni and published by John Wiley & Sons. This book was released on 2021-01-13 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get effective and efficient instruction on all CIA internal auditing exam competencies in 2021 Updated for 2021, the Wiley CIA Exam Review 2021, Part 1 Essentials of Internal Auditing offers readers a comprehensive overview of the internal auditing process as set out by the Institute of Internal Auditors. The Exam Review covers the six domains tested by the Certified Internal Auditor exam, including: The foundations of internal auditing Independence and objectivity Proficiency and due professional care Quality assurance and improvement programs Governance, risk management, and control Fraud risks The Wiley CIA Exam Review 2021, Part 1 Essentials of Internal Auditing is a perfect resource for candidates preparing for the CIA exam. It provides an accessible and efficient learning experience for students regardless of their current level of proficiency.