Operational model for WPB Sample Clauses

Operational model for WPB. The goal of this section is to describe the solution architecture for processing XXX data according to an operational way, that is describing where the most-used data are located (local, European or worldwide level) and how the services are autonomous, interoperable, replicated or shared between the NSIs. The figure above is a representation for the XXX operational model. The different blue colors deal with the state of the services (autonomous…) while the purple ones represents the data availability level. This figure shows the implementation version which has been achieved within the work package B. Looking in the future, a target should be that the services linked to “Acquisition and recording”, “Data wrangling” and “Data representation” will be shared through the NSIs. The most peculiar thing about these three business functions is their autonomy regarding the aim of the process. Whatever the data you want to work on, data acquisition and recording are the same. The data needed could change the parameters used for scraping or website retrieving, but technical background is the same. You can have the same logic about data wrangling. Data filtering, language detection, standardization… are technical phases, which are independent from the aim of the statistical process and could be shared and used for other purposes. Looking at data representation this can be less evident - although creating indicators or classifying data are both quite the same whatever the goal of the statistical process, provided that the parameters can be well adjusted. This point of view resounds with the Eurostat grant call for the development of web intelligence network. It could give the availability to share services hosted on Eurostat web intelligence hub, provided NSIs can help in testing and developing these services, giving their own experience. Having an effective operational model relies also on some organizational aspects. The big data lifecycle needs to be implemented in a way that takes collaboration for heterogeneous teams and technologies into account. In addition, using ML (machine learning) in an effective way implies that ML models are reusable and interoperable.
Sample 1
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Related to Operational model for WPB

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  • Project Implementation Manual The Recipient, through the PCU, shall: (i) take all action required to carry out Parts 1.1, 1.3, 1.4, 2, 3.1(b), 3.2, 3.3 and 4 (ii) of the Project in accordance with the provisions and requirements set forth or referred to in the Project Implementation Manual; (ii) submit recommendations to the Association for its consideration for changes and updates of the Project Implementation Manual as they may become necessary or advisable during Project implementation in order to achieve the objective of Parts 1.1, 1.3, 1.4, 2, 3.1(b), 3.2, 3.3 and 4(ii) of the Project; and (iii) not assign, amend, abrogate or waive the Project Implementation Manual or any of its provisions without the Association’s prior agreement. Notwithstanding the foregoing, if any of the provisions of the Project Implementation Manual is inconsistent with the provisions of this Agreement, the provisions of this Agreement shall prevail and govern.

  • Implementation Program 1. The Borrower shall:

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