A data scientist at an industrial equipment manufacturing company needs to build a regression model to predict power consumption in the company's plants using sensor data (tens of millions of records daily). Daily model training is required using all available data.
The suggested answer is B: Develop a regression model using BigQuery ML. This is likely the best option due to BigQuery's scalability and ability to handle large datasets directly, minimizing development effort.
You are a data scientist at an industrial equipment manufacturing company. You are developing a regression model to estimate the power consumption in the company’s manufacturing plants based on sensor data collected from all of the plants. The sensors collect tens of millions of records every day. You need to schedule daily training runs for your model that use all the data collected up to the current date. You want your model to scale smoothly and require minimal development work. What should you do?
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