Introduction:
We were discussing full-service options for NLP programming for any organization. I used an example to discuss points in favor of such a service: http://shrink-text.westus2.cloudapp.azure.com:8668/add. Here we try to illustrate that a file uploader for instance is an improvement over raw text processing.
There are several reasons that full service is more appealing than some out of box capabilities. For example, the connectors to data sources will need to be authored. Automation and scheduling of jobs and intakes are going to be necessary for continuous processing. Error handling, reports and notifications will be required for administration purposes anyways.
Full Service options also involve compute and storage handling for all the near and long term needs surrounding the processes for the NLP task involved. Artifacts produced as a result of the processing may need to be archived. Aged artifacts many need to be tiered. Retrieval systems can be built on top of collections made so far. At any time, a full service solution at the very least provides answers to questions that generally take a lot of effort with the boxed solutions.
Moreover, it is not just the effort involved with out of box features, it is the complete ownership of associated activities and the convenience brought into the picture. And the availability of queuing services and asynchronous processing for all backlogs adds more value to the full service. Reports and dashboards become more meaningful with full service solutions. The impact and the feedback from audience is improved with full service solution. A full service solution goes a long way to improve customer satisfaction.
There are several reasons that full service is more appealing than some out of box capabilities. For example, the connectors to data sources will need to be authored. Automation and scheduling of jobs and intakes are going to be necessary for continuous processing. Error handling, reports and notifications will be required for administration purposes anyways.
Full Service options also involve compute and storage handling for all the near and long term needs surrounding the processes for the NLP task involved. Artifacts produced as a result of the processing may need to be archived. Aged artifacts many need to be tiered. Retrieval systems can be built on top of collections made so far. At any time, a full service solution at the very least provides answers to questions that generally take a lot of effort with the boxed solutions.
Moreover, it is not just the effort involved with out of box features, it is the complete ownership of associated activities and the convenience brought into the picture. And the availability of queuing services and asynchronous processing for all backlogs adds more value to the full service. Reports and dashboards become more meaningful with full service solutions. The impact and the feedback from audience is improved with full service solution. A full service solution goes a long way to improve customer satisfaction.
#codingexercise
Tests for https://ideone.com/6ms4Vz
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