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Google Exam Professional Data Engineer Topic 2 Question 81 Discussion

Actual exam question for Google's Professional Data Engineer exam
Question #: 81
Topic #: 2
[All Professional Data Engineer Questions]

You are implementing a chatbot to help an online retailer streamline their customer service. The chatbot must be able to respond to both text and voice inquiries. You are looking for a low-code or no-code option, and you want to be able to easily train the chatbot to provide answers to keywords. What should you do?

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Suggested Answer: D

Dialogflow is a conversational AI platform that allows for easy implementation of chatbots without needing to code. It has built-in integration for both text and voice input via APIs like Cloud Speech-to-Text. Defining intents and entity types allows you to map common queries and keywords to responses. This would provide a low/no-code way to quickly build and iteratively improve the chatbot capabilities.

https://cloud.google.com/dialogflow/docs Dialogflow is a natural language understanding platform that makes it easy to design and integrate a conversational user interface into your mobile app, web application, device, bot, interactive voice response system, and so on. Using Dialogflow, you can provide new and engaging ways for users to interact with your product. Dialogflow can analyze multiple types of input from your customers, including text or audio inputs (like from a phone or voice recording). It can also respond to your customers in a couple of ways, either through text or with synthetic speech.


Contribute your Thoughts:

Gaston
6 months ago
Eve: I think we should consider how easy it is to implement each option and how it aligns with our overall goals.
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Marshall
6 months ago
David: I'm not sure which option to choose. They all seem to have their pros and cons.
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Kendra
6 months ago
That makes sense too, It's important to have a chatbot that is easy to train and scalable.
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Jonelle
6 months ago
I would rather go with option D, using Dialogflow to define intents based on common queries. It seems more efficient.
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Kristofer
7 months ago
I agree with It's a good approach to balance simplicity and complexity in the chatbot's responses.
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Karina
7 months ago
I think we should go with option C, using Dialogflow for simple queries and Speech-to-Text API for complex ones.
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Glory
8 months ago
That could work. We can combine Dialogflow for simple queries and the API for complex ones.
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Mona
8 months ago
Should we also use the Speech-to-Text API for complex queries?
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Merissa
8 months ago
That sounds like a good idea. We can define intents based on common queries.
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Glory
8 months ago
I think we should use Dialogflow to implement the chatbot.
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Nguyet
7 months ago
Great, let's go ahead with using Dialogflow for our chatbot implementation.
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Eulah
7 months ago
With Dialogflow, you can integrate the Speech-to-Text API for handling voice inquiries.
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Rikki
8 months ago
That sounds like a good option for our needs. What about handling voice inquiries?
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Malinda
8 months ago
Yes, with Dialogflow you can define specific intents and responses based on keywords.
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Nell
8 months ago
Can we easily train the chatbot to provide answers to keywords?
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Melissa
8 months ago
C) Use Dialogflow for simple queries and the Speech-to-Text API for complex queries.
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Marnie
8 months ago
D) Use Dialogflow to implement the chatbot, defining the intents based on the most common queries collected.
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