Data Architecture Solutions - Platform Data Architecture Strategies Analytics | Modern Platform's

Описание: In this video, we discuss about Why platform and architecture matter in data science? There are two types of concept here. The 1st one is that if we want to design or built a platform and architecture for data science, then we keep in mind that there are some steps that we follow to build an effective and efficient platform. Our platform must me manage the data and store it, it process the data according to user requirement’s, platform must me scalable and compatible with different tools and libraries. It provide data integration and must me cost effective. Our platform must be provide the security to the user and it provide deployment facility.
The 2nd one is that if we are dada scientist and want to build a system or working on project, we select a platform and architecture for building a project, then we preliminary judgment some basic needs to select a platform. The platform that we choose for our project, it must be manage our data according to our needs and store it for further use it in future. If we used large amount of data for our project, then selected platform provide scalability facility to us for working on our project. When we are working on data science, we choose different type of machine learning libraries and tools to use some built in model or methods to build a effective project. It must be cost effective that will be managed with our budget.

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