Tabla de Contenidos: “…chapter 1. Little big data : mastering existing information as a foundation for big data / Donald A. …”

Tabla de Contenidos: “…; Chapter 20: Coping in a Big Data Environment : Analytics and Alignment with Organizational Change and Learning…”

Materias:

Tabla de Contenidos: “…-- Running Deep Learning models on H2O -- Summary -- Chapter 9: The Future of R - Big, Fast, and Smart Data -- The current state of Big Data analytics with R -- Out-of-memory data on a single machine -- Faster data processing with R -- Hadoop with R -- Spark with R -- R with databases -- Machine learning with R -- The future of R -- Big Data -- Fast data -- Smart data -- Where to go next -- Summary -- Index…”

Materias:

Materias:

Tabla de Contenidos: “…Chapter 1: Next-Generation Big Data -- Chapter 2: Introduction to Kudu -- Chapter 3: Introduction to Impala -- Chapter 4: High Performance Data Analysis with Impala and Kudu -- Chapter 5: Introduction to Spark -- Chapter 6: High-Performance Data Processing with Spark and Kudu -- Chapter 7: Batch and Real-Time Data Ingestion and Processing -- Chapter 8: Big Data Warehousing -- Chapter 9: Big Data Visualization and Data Wrangling -- Chapter 10: Distributed In-Memory Big Data Computing -- Chapter 11: Big Data Governance and Management -- Chapter 12: Big Data in the Cloud -- Chapter 13: Big Data Case Studies…”

Tabla de Contenidos: “…Machine generated contents note: Preface Acknowledgments PART ONE May You Live in Interesting Times CHAPTER 1 Lead or Get Out of the Way The Future is Now The Secret is Leadership Notes CHAPTER 2 Disruption as a Way of Life The Age of Uncertainty The Emergence of Big Data Rise of the Ronin The Knowledge Rush Systematized Chaos Notes PART TWO Understanding Culture and Capability CHAPTER 3 The Cultural Imperative Level 1: Dazed and Confused Level 2: Activities and Algorithms Level 3: Value and Outcomes Level 4: Functional Innovation Level 5: Revolutionary Disruptor Notes CHAPTER 4 The Intelligent Enterprise Level 1: Unstructured Chaos Level 2: Structured Chaos Levels 3 - 5: The Intelligent Enterprise Notes PART THREE Making It Real CHAPTER 5 Organizational Design What Should It Look Like? …”

“…The ultimate goal is extracting Big Information from the Big Data. As a Big Data Consultant, Mikhail Gilula combines academic background with 20 years of industry experience in the database and data warehousing technologies working as a Sr. …”

Tabla de Contenidos: “…So Secure It's Lost; Safe Access in Secure Big Data Systems; Chapter 2. The Challenge: Sharing Data Safely; Surprising Outcomes with Anonymity; The Netflix Prize; Unexpected Results from the Netflix Contest; Implications of Breaking Anonymity; Be Alert to the Possibility of Cross-Reference Datasets; New York Taxicabs: Threats to Privacy; Sharing Data Safely; Chapter 3. …”

Tabla de Contenidos: “…Title Page; Copyright Page; Table of Contents; Introduction; About This Book; Foolish Assumptions; Icons Used in This Book; Beyond the Book; Where to Go From Here; Part I Introducing Big Data Statistics; Chapter 1 What Is Big Data and What Do You Do with It?…”

“…Get Started Scaling Your Database Infrastructure for High-Volume Big Data Applications “Understanding Big Data Scalability presents the fundamentals of scaling databases from a single node to large clusters. …”

Tabla de Contenidos: “…; ""The Potentials and Difficulties of Big Data""; ""Requirements for a Big Data System""; ""How Hadoop Tools Can Help""; ""My Approach""; ""Overview of the Big Data System""; ""Big Data Flow and Storage""; ""Benefits of Big Data Systems""; ""Whatâ€?…”

Tabla de Contenidos: “…Chapter 1: Big Data Technology Landscape -- Chapter 2: Programming in Scala -- Chapter 3: Spark Core -- Chapter 4: Interactive Data Analysis with Spark Shell -- Chapter 5: Writing a Spark Application -- Chapter 6: Spark Streaming -- Chapter 7: Spark SQL -- Chapter 8: Machine Learning with Spark -- Chapter 9: Graph Processing with Spark -- Chapter 10: Cluster Managers -- Chapter 11: Monitoring…”

Tabla de Contenidos: “…Contents at a Glance; Introduction; Chapter 1: Big Data Solutions and the Internet of Things; From Punched Cards to Decision Support; The Data Warehouse ; Independent vs. …”

Tabla de Contenidos: “…The goal here is to lay down the foundation of a heterogeneous architecture that will be described in the following chapters.1- Identifying Big Data symptoms2- Understanding the Big Data projects ecosystem3- Creating the foundation of a long term Big Data architectureChapter 2: Early Big Data with No-SQL (30 pages)Chapter Goal: This chapter aims to describe how a No-SQL database can be a starting point for your Big Data project, how it can deal with large amounts of data, what are the limits of this model and how it can be scaled to a full-fledged Big Data project.1- Choosing the right No-SQL database2- Introduction to Couchbase3- Introduction to Elasticsearch4- Using No-SQL cache in a SQL based architectureChapter 3: Big Data processing jobs topology (30 pages)Chapter Goal: The more data you get, the more important it is to split the processing into different jobs depending on the topology of the processing.1- Big Data Job processing strategy2- Smart data extraction from No-SQL database3- Short term processing jobs.4- Long term processing jobs.Chapter 4: Big Data Streaming Pattern (30 pages)Chapter Goal: This chapter helps the readers to understand what are their options when it comes to dealing with streaming high data throughput.1- Identifying streaming data sources2- Streaming with Big Data projects (Flume) versus Enterprise Service Bus3- Processing architecture for stream dataChapter 5: Querying and Analysing Patterns (30 pages)Chapter Goal: In this chapter, the readers will understand how to leverage the processing work through long term & real time data querying.1- "Process then Query" strategy versus real-time querying2- Process, store and query data in Elasticsearch3- Real-Time querying using SparkChapter 6: How About Learning from your Data? …”

Materias:

Materias:

Tabla de Contenidos: “…Cover -- Title Page -- Copyright and Credits -- Packt Upsell -- Contributors -- Table of Contents -- Preface -- Chapter 1: Why Big Data? -- What is big data? -- Characteristics of big data -- Volume -- Velocity -- Variety -- Veracity -- Variability -- Value -- Solution-based approach for data -- Data - the most valuable asset -- Traditional approaches to data storage -- Clustered computing -- High availability -- Resource pooling -- Easy scalability -- Big data - how does it make a difference? …”