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Big Data Analytics (Database Management Systems)

. It elucidates the handling and storing of data through database management systems. It examines the challenges involved in big data analysis;

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Data Management Technologies and Applications

management, big data, knowledge management, ontology engineering, digital libraries, mobile databases, object-oriented database systems, and data;

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Handbook of Big Data Analytics: Applications in ICT, security and business analytics

Big Data analytics is the complex process of examining big data to uncover information such as correlations, hidden patterns, trends and;

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Handbook of Big Data Analytics: Methodologies

Big Data analytics is the complex process of examining big data to uncover information such as correlations, hidden patterns, trends and;

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Database and Expert Systems Applications

carefully reviewed and selected from 157 submissions. The papers are organized in the following topical sections: Part I: Big data;

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Database and Expert Systems Applications

were carefully reviewed and selected from 157 submissions. The papers are organized in the following topical sections: Part I: Big data;

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Human Capital Systems, Analytics, and Data Mining

tutorials for Human Capital Management Systems (HCMS) database modeling, analytics, interactive dashboards, and data mining that is independent;

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Human Capital Systems, Analytics, and Data Mining

tutorials for Human Capital Management Systems (HCMS) database modeling, analytics, interactive dashboards, and data mining that is independent;

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Analytics for Insurance

strategy, management, marketing, and more Big Data and analytics is changing business but how? The majority of Big Data guides discuss data;

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Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications

are organized into the following topical headings: big data analytics and distributed systems; security and privacy engineering; industry 4.0;

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Database Systems for Advanced Applications

management; indexing and distributed systems; network embedding; trajectory and time series data processing; data mining; query processing and;

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Database Systems for Advanced Applications

; spatial databases; real time data processing; big data; social networks and graphs.;

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Data Science

, Machine Learning, and Big Data - That You Don't Data Science for Business: Predictive Modeling, Data Mining, Data Analytics, Data Warehousing;

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Getting Started with Greenplum for Big Data Analytics

Standard tutorial-based approach. Getting Started with Greenplum for Big Data Analytics is great for data scientists and data analysts with;

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Database Systems for Advanced Applications

submissions to the four following workshops: the 4th International Workshop on Big Data Management and Service, BDMS 2017; the Second International;

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Database Systems for Advanced Applications

submissions. The papers cover the following topics: big data management, indexing and query processing, graph data management, spatio-temporal data;

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Big Data Analytics for Internet of Things

BIG DATA ANALYTICS FOR INTERNET OF THINGS Discover the latest developments in IoT Big Data with a new resource from established and;

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Database and Expert Systems Applications: 29th International Conference, Dexa 2018, Regensburg, Germany, September 3-6, 2018, Proceedings, Part I

including: Big data analytics; data integrity and privacy; decision support systems; data semantics; cloud data processing; time series data; social;

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Azure Storage, Streaming, and Batch Analytics

all the building blocks for scalable big data analysis systems including ingestion, processing, querying, and migration. * Azure;

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Web Age Information Management

from 164 submissions. The focus of the conference is on following topics: advanced database and web applications, big data analytics big data;

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Healthcare Data Analytics and Management

, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding;

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Recent Developments in Data Science and Business Analytics

, descriptive analytics, predictive analytics, prescriptive analytics, uncertainty modeling, big data, data warehousing, data compression, computer;

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Databases in Networked Information Systems

. The papers are organized in topical section such as big data and cloud computing; astronomical data management; business data analytics and;

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Big Data

book is organized into five main sections: Big Data Management-considers the research issues related to the management of Big;

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Big Data

book is organized into five main sections: Big Data Management-considers the research issues related to the management of Big Data;

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Database Systems for Advanced Applications: DASFAA 2019 International Workshops

to the three following workshops: the 6th International Workshop on Big Data Management and Service, BDMS 2019; the 4th International;

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Principles of Distributed Database Systems

The fourth edition of this classic textbook provides major updates. This edition has completely new chapters on Big Data Platforms;

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