Cloud-Digital-Leader Exam Dumps - Google Cloud Certified Questions and Answers

The correct answer is B. Switch from batch processing to stream processing. Here's why:

Context of the Question: The organization processes sales data at the end of every month and wants to make near real-time decisions to improve accuracy and agility.

Google Cloud Product Relevance:

Stream processing allows data to be processed as it arrives, enabling real-time analytics and faster decision-making. This would allow the organization to analyze sales trends continuously rather than waiting for monthly batch jobs to complete.

Google Cloud services like Dataflow support both batch and stream processing, allowing for the transformation and analysis of data in real-time.

Why Not Other Options:

A. Filter the data so reports are generated faster: Filtering data may speed up reporting slightly but does not enable near real-time decision-making.

C. Process batch reports weekly instead of monthly: Processing weekly instead of monthly still doesn't provide the near real-time insights the organization needs.

D. Change from a relational database to a NoSQL database: This change might improve scalability or flexibility but does not directly address the need for real-time data processing.

Google Cloud Digital Leader References:

Refer to Google Cloud Dataflow documentation to learn about stream processing capabilities.

Completeness refers to the degree to which all necessary data is present and accounted for. In the context of machine learning, if a model is trained without including all relevant dimensions (such as demographic information in this case), it might lead to poor performance because it lacks important data needed to make accurate predictions.

Option D: Completeness is correct because the lack of demographic information represents incomplete data. The absence of this data dimension could prevent the model from learning patterns that are influenced by demographic factors, thereby impacting its overall effectiveness.

References:

Google Cloud Documentation: Data Quality in Machine Learning

Google Cloud AI Platform: Best Practices for Training Data Preparation