一家数字设备公司想要预测内存硬件的客户需求。该公司没有编码经验，也不了解机器学习算法，但需要开发一个数据驱动的预测模型。该公司需要对内部数据和外部数据进行分析。哪种解决方案能满足这些要求呢？
A. 将数据存储在亚马逊 S3 中。使用来自亚马逊 S3 的数据，通过亚马逊 SageMaker 内置算法创建机器学习模型并进行需求预测。
B. 将数据导入亚马逊 SageMaker Data Wrangler。使用 SageMaker 内置算法创建机器学习模型并进行需求预测。
C. 将数据导入亚马逊 SageMaker Data Wrangler。使用亚马逊 Personalize 的 Trending - Now 配方构建机器学习模型并进行需求预测。
D. 将数据导入亚马逊 SageMaker Canvas。通过在 SageMaker Canvas 中选择数据值来构建机器学习模型并进行需求预测。
A digital devices company wants to predict customer demand for memory hardware. The company does not have coding experience or knowledge of ML algorithms and needs to develop a data-driven predictive model. The company needs to perform analysis on internal data and external data.
Which solution will meet these requirements?
A. Store the data in Amazon S3. Create ML models and demand foredcast predictions by using Amazon SageMaker built-in algorithms that use the data from Amazon S3.
B. Import the data into Amazon SageMaker Data Wrangler. Create MLmodels and demand forecast predictions by using SageMaker built-in algorithms.
C. Import the data into Amazon SageMaker Data Wrangler. Build ML nnodels and demand forecast predictions by using an Amazon Personalize Trending-Now recipe.
D. Import the data into Amazon SageMaker Canvas. Build ML modelsand demand forecast predictions by selecting the values in the data from SageMaker Canvas.
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