Data Modeling
Data Modeling Master Class Steve Hoberman s Best Practices Approach to Developing a Competency in Data Modeling
... of data modeling, we introduce our first case study which illustrates four important gaps filled by data ...explain data modeling concepts and terminology, and provide you with a set of ...
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Dimensional Data Modeling
... in data warehousing is dimensional data ...some data analysis situations, it can meet an organization's requirements for organizing warehouse ...
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Data modeling applications in space science and astronomy
... Lambert demonstrated theoretical and practical examples of achieving super-resolved images by exploiting the anisoplanatic distortion to enable observation of spatial frequency content which would normally be lost beyond ...
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A DATA MODELING PROCESS FOR DECOMPOSING HEALTHCARE PATIENT DATA SETS
... the modeling process serves as a valuable means to understand and verify the user requirements, as well as to communicate the database design among ...any data model, in practice the relational model is ...
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Data Modeling and Data Analytics: A Survey from a Big Data Perspective
... unstructured data. Database Management Systems and Data Warehouses are no longer the only technologies used to store and analyze datasets, namely due to the volume and complex structure of nowadays ...
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Graph-based Data Modeling and Analysis for Data Fusion in Remote Sensing
... on data and feature fusion in remote sensing area using graph-based data modeling and learning ...sensing data fusion techniques to address new challenging applications is ...in data ...
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Agricultural Data Modeling and Yield Forecasting using Data Mining Techniques
... using data mining techniques. Data mining techniques extract hidden knowledge through data analysis, unlike statistical ...agronomic data for the paddy ...
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Generative Adversarial Networks for Data Modeling
... histograms. If you wanted the Jensen-Shannon divergence, you would need to square the answer returned. The function call implicitly normalizes the histogram arrays if you supply them otherwise. With regard to the role of ...
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Triple-Driven Data Modeling Methodology in Data Warehousing: A Case Study
... Notice: The “Map” process mentioned in this step is fit for “subject->entity” level in a medium-scale data warehouse. Refinement may be needed for “subject->sub-subject->entity” level in a large-scale ...
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Data Modeling for Product Data Using Cassandra and Mongodb
... In this module, we can eliminate stop words and stemming words[6]. In corpus linguistics, part-of-speech[6], also called grammatical tagging or words-category disambiguation, the process of word in a text as ...
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Graphical Diagnostic for Mortality Data Modeling
... for data transformed under a parametric null ...transformed data. If the model does fit the data then the hazard for the data transformed using the model should be constant, with no monotonic ...
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Data Modeling by Example a Tutorial
... the Data On the right-hand side, we show Species as a Tourist Attraction, whereas in fact, people say ‘Let’s go the Elephant Sanctuary’ so the entity that should be related to the Tourist Attraction is the ...
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Big Data Approaches to Modeling the Labor Market
... Those two simple steps lead to a dramatic reduction of the number of variables per observation – these now count 233, or a total of 77 million data points. Such a dataset can be usefully analyzed with relatively ...
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Simplified aerosol modeling for variational data assimilation
... Atmospheric Modeling System/Chemical Wheather Forecasting System 4-D varia- tional data assimilation system ...variational data assimilation on multiple aerosol ...
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An R package for analyzing and modeling ranking data
... ranking data are available (partially and indirectly) in some statistical software (for example, pro- cedure MDPREF in SAS), not to mention hypothesis testing and probability models for ranking ...ranking ...
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MODELING CITY PULSATION VIA MOBILE DATA
... these data could be done, since it is real time data, and came from real infrastructure of the ...these data in aggregated or disaggregated (individually/collectively), with different kinds analysis ...
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Modeling and Querying Data Series and Data Streams with Uncertainty
... Our evaluation reveals the effectiveness of the techniques that have been proposed in the literature under different scenarios. In the experiments, we stress-test the different techniques both in situations for which ...
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Modeling data communication with NS3 simulator
... device data structure: it represents a single hardware device and allows the upper layers to queue packets for transmission by the hardware and makes it possible for the hardware device to notify the upper layers ...
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NAME Modeling and Data Assimilation: a strategic overview
... observations near the mouth of and along the Gulf of California. The mix of observations gathered by the Mexican Navy Research Vessel Altair, the University of Mexico El Puma and the CICESE Research Vessel Ulloa (see the ...
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A data-driven framework for neural field modeling
... creating data-driven neural field models by developing a method for estimating intracortical connectivity and synaptic dynamics from electrophysiological ...real data is now ...
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