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Security and Privacy Trends in Cloud Computing and Big Data

big data integration.;

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Big Data Integration

integration (BDI) challenge is critical to realizing the promise of big data. BDI differs from traditional data integration along the dimensions;

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Systems Analytics and Integration of Big Omics Data

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Building Big Data Applications

Building Big Data Applications helps data managers and their organizations make the most of unstructured data with an existing data;

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Big Data Analytics for Smart and Connected Cities

bring them into the future. The integration of big data and interconnected technology, along with the increasing population, will lead to the;

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Big Data Analysis for Bioinformatics and Biomedical Discoveries

Demystifies Biomedical and Biological Big Data Analyses Big Data Analysis for Bioinformatics and Biomedical Discoveries provides a;

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Big Data Analysis for Bioinformatics and Biomedical Discoveries

Demystifies Biomedical and Biological Big Data Analyses Big Data Analysis for Bioinformatics and Biomedical Discoveries provides a;

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Principles of Big Data

a set of laws, regulations and ethical standards that apply to the acquisition, distribution and integration of Big Data resources;

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Managerial Perspectives on Intelligent Big Data Analytics

Big data, analytics, and artificial intelligence are revolutionizing work, management, and lifestyles and are becoming disruptive;

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Big Data Analytics and Knowledge Discovery

This volume LNCS 12925 constitutes the papers of the 23rd International Conference on Big Data Analytics and Knowledge Discovery, held;

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Emerging Perspectives in Big Data Warehousing

The concept of a big data warehouse appeared in order to store moving data objects and temporal data information. Moving objects are;

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Medical Big Data and Internet of Medical Things

research on integration of big data analytics with respect to clinical practice and clinical utility, architectures and clustering techniques for;

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Advances in Mobile Cloud Computing and Big Data in the 5G Era

paradigms, the Mobile Cloud computing (MCC) and Big Data, as the pillars and their association with the emerging 5G mobile networks. The book;

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Data Warehousing in the Age of Big Data

, and new architecture options, workloads, and integration techniques for Big Data and the data warehouse. Part 3 deals with data governance;

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Biomedical Data Management and Graph Online Querying

This book constitutes the refereed proceedings of the two International Workshops on Big-Graphs Online Querying, Big-O(Q) 2015, and Data;

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Emerging Trends in IoT and Integration With Data Science

in IoT and Integration With Data Science is a critical reference source that provides theoretical frameworks and research findings on IoT and big;

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Big Data for Regional Science

wide array of disciplinary backgrounds. The content is organized along four themes: sources of big data; integration, processing and management;

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Integration Challenges for Analytics, Business Intelligence, and Data Mining

information that is crucial for the success of the company. Without the integration of data (both structured and unstructured) mining in business;

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Structured Search for Big Data

The WWW era made billions of people dramatically dependent on the progress of data technologies, out of which Internet search and Big;

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Understanding Azure Data Factory

advanced analytics and big data pipelines. What You'll Learn Understand data integration on Azure cloud Build and operationalize an ADF pipeline;

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Big Data Visualization

integration of visual big data with BI using Cognos BI. Style and approach With the help of insightful real-world use cases, we'll tackle data;

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Handbook of Data Science Approaches for Biomedical Engineering

management, such as predictive analytics and forecasting, big data integration for medical data, algorithms and techniques to speed up the analysis;

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Handbook of Big Data Technologies

engines and big stream processing systems. Part Two focuses on the semantic aspects of Big Data management including data integration and;

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Handbook of Big Data Technologies

engines and big stream processing systems. Part Two focuses on the semantic aspects of Big Data management including data integration and;

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Demystifying Big Data and Machine Learning for Healthcare

value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this;

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Demystifying Big Data and Machine Learning for Healthcare

value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this;

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Data Management

modelling and SQL. It includes a new chapter on future directions, including e-commerce. It contains new material on data integration, data quality;

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