Materias:

Materias: “…Big data Periodicals…”

Tabla de Contenidos: “…Thomas Hoeren, Big Data and Data Quality -- Christian Döpke, The Importance of Big Data for Jurisprudence and Legal Practice -- Nicolai Culik and Christian Döpke, About Forgetting and Being Forgotten -- Nicolai Culik, Brussels Calling: Big Data and Privacy -- Andreas Börding, Safe Harbor: The Decision of the European Court of Justice -- Tim Jülicher, Education 2.0: Learning Analytics, Educational Data Mining and Co. -- Max v. …”

Materias: “…Big Data…”

Materias: “…Big data Periodicals…”

Materias: “…Big data Periodicals…”

Materias: “…Big data Social aspects Periodicals…”

“…Big Data Demystified…”

“…Even with tools like Hadoop, extracting usable insight is difficult—often, because it’s so difficult to integrate new and legacy data sources. In Beyond Big Data , five of IBM’s leading data management experts introduce powerful new ways to integrate social, mobile, location, and traditional data. …”

“…"Big Data Simplified blends technology with strategy and delves into applications of big data in specialized areas, such as recommendation engines, data science and Internet of Things (IoT) and enables a practitioner to make the right technology choice. …”

Tabla de Contenidos: “…Big-n versus Big-p in Big Data; II. Data-Centric, Exploratory Methods; 3. …”

Tabla de Contenidos: “…Cover; Contents; Preface; Editors; Contributors; I: Introduction of Big Data; Chapter 1: Orchestrating Science DMZs for Big Data Acceleration: Challenges and Approaches; Chapter 2: A Survey of Virtual Machine Placement in Cloud Computing for Big Data; Chapter 3: Big Data Management Challenges, Approaches, Tools, and Their Limitations; Chapter 4: Big Data Distributed Systems Management; II: Networking Theory and Design for Big Data; Chapter 5: Moving Big Data to the Cloud: Online Cost-Minimizing Algorithms; Chapter 6: Data Process and Analysis Technologies of Big Data…”

Tabla de Contenidos: “…Intro -- Foreword -- Introduction -- Glossary -- Contents -- Part I Technological Foundation: Big Data Technologies for BioIndustries -- 1 Big Data Technologies in DataBio -- 1.1 Basic Concepts of Big Data -- 1.2 Pipelines and the BDV Reference Model -- 1.3 Open, Closed and FAIR Data -- 1.4 The DataBio Platform -- 1.5 Introduction to the Technology Chapters -- Literature -- 2 Standards and EO Data Platforms -- 2.1 Introduction -- 2.2 Standardization Organizations and Initiatives -- 2.2.1 The Role of Location in Bioeconomy -- 2.2.2 The Role of Semantics in Bioeconomy…”

Tabla de Contenidos: “…Cover -- Copyright -- Credits -- About the Author -- Acknowledgement -- About the Reviewers -- www.PacktPub.com -- Preface -- Chapter 1: Big Data Analytics at a 10,000-Foot View -- Big Data analytics and the role of Hadoop and Spark -- A typical Big Data analytics project life cycle -- Identifying the problem and outcomes -- Identifying the necessary data -- Data collection -- Preprocessing data and ETL -- Performing analytics -- Visualizing data -- The role of Hadoop and Spark -- Big Data science and the role of Hadoop and Spark -- A fundamental shift from data analytics to data science -- Data scientists versus software engineers -- Data scientists versus data analysts -- Data scientists versus business analysts -- A typical data science project life cycle -- Hypothesis and modeling -- Measuring the effectiveness -- Making improvements -- Communicating the results -- The role of Hadoop and Spark -- Tools and techniques -- Real-life use cases -- Summary -- Chapter 2: Getting Started with Apache Hadoop and Apache Spark -- Introducing Apache Hadoop -- Hadoop Distributed File System -- Features of HDFS -- MapReduce -- MapReduce features -- MapReduce v1 versus MapReduce v2 -- MapReduce v1 challenges -- YARN -- Storage options on Hadoop -- File formats -- Compression formats -- Introducing Apache Spark -- Spark history -- What is Apache Spark? …”

Tabla de Contenidos: “…Cover -- Copyright -- Credits -- About the Author -- About the Reviewer -- www.PacktPub.com -- Customer Feedback -- Table of Contents -- Preface -- Chapter 1: Introduction to Big Data Visualization -- An explanation of data visualization -- Conventional data visualization concepts -- Training options -- Challenges of big data visualization -- Big data -- Using Excel to gauge your data -- Pushing big data higher -- The 3Vs -- Volume -- Velocity -- Variety -- Categorization -- Such are the 3Vs -- Data quality -- Dealing with outliers -- Meaningful displays -- Adding a fourth V -- Visualization philosophies -- More on variety -- Velocity -- Volume -- All is not lost -- Approaches to big data visualization -- Access, speed, and storage -- Entering Hadoop -- Context -- Quality -- Displaying results -- Not a new concept -- Instant gratifications -- Data-driven documents -- Dashboards -- Outliers -- Investigation and adjudication -- Operational intelligence -- Summary -- Chapter 2: Access, Speed, and Storage with Hadoop -- About Hadoop -- What else but Hadoop? …”

Materias: “…Big data…”

Materias: “…Big data…”

“…You’ll gain a practical, actionable view of big data by working with real data and real problems. …”

Tabla de Contenidos: “…Title Page; Copyright Page; About the Authors; Contents; Prologue; Berkeley, 1930's; Pattern Recognition; Nelson Peltz; Committing to One Percent; The Big Data Revolution; Introduction; Storytelling; Objective; Outline; Part I "The Revolution Starts Now: 9 Industries Transforming with Data"; Part II "Learning from Patterns in Big Data"; Part III "Leading the Revolution"; Storytelling (Continued); Part I: The Revolution Starts Now: 9 Industries Transforming With Data; Chapter 1: Transforming Farms with Data; California, 2013; Brief History of Farming; The Data Era; Potato Farming…”