Sentence examples for data architecture for from inspiring English sources

Exact(6)

We will consider the architecture of such systems in more detail in 'Big data architecture for adaptive learning systems' section.

This chapter introduces design principles, framework, and data architecture for structured search systems based on the key-object model.

Finally, 'Big data architecture for adaptive learning systems' section describes a scalable, cloud-based learning analytics platform which runs generalized adaptive and analytical models on educational data in parallel.

We conclude with some remarks about the need to develop a data architecture for the Grid that will allow federated access to relational databases as well as flat files.

The paper presents the process adopted to produce the ontology and the big data architecture for the knowledge base feeding on the basis of open and private data, and the mechanisms adopted for the data verification, reconciliation and validation.

In 'Big data architecture for adaptive learning systems' section we will see how these two analytics capabilities, of providing just-in-time insights and embedding ongoing data collection and experimentation to improve the quality of adaptive models, can be supported with an open, modular architecture.

Similar(54)

This chapter delineates a framework based on statistical and mathematical approaches to measure and manage this risk, and highlights the requirements for the data architecture of the model.

Ms. Shifrin, 42, a data architecture manager for LexisNexis, comes from a line of movie enthusiasts.

The process involves a complex data architecture that accounts for heterogeneous information that is collected by a variety of institutions across different scales.

The basic architecture of a data warehouse can also be recognized from the right half of Fig. 9, yet the figure also indicates how to extend a traditional data warehouse architecture for big data.

It is argued that elements of software, infrastructure, and data architecture are necessary prerequisites for the successful delivery of complex agile system development projects.

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