数据准备
在接入数据后，为了将数据通过可视化的方式展示出来，需要对分散、异构的原始业务数据进行清晰、整合、加工，从而形成可以用于数据分析和展示的数据模型(或数据集)。
基于不同的用户使用场景，提供多种数据建模方式，包括：
直连模型
抽取模型
直连数据集
缓存数据集
原生查询数据集
流式数据集
推送数据集
接下来详细介绍每种数据建模方式并给出初步的选型建议。
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在接入数据后，为了将数据通过可视化的方式展示出来，需要对分散、异构的原始业务数据进行清晰、整合、加工，从而形成可以用于数据分析和展示的数据模型(或数据集)。
基于不同的用户使用场景，提供多种数据建模方式，包括：
直连模型
抽取模型
直连数据集
缓存数据集
原生查询数据集
流式数据集
推送数据集
接下来详细介绍每种数据建模方式并给出初步的选型建议。