Abstract

Technological advancements enable new applications and interactions with devices, leading to an exponential increase in data production. Efficient methods for handling this data, from its origin to visualization and analysis, are crucial. Selecting the appropriate Big Data architecture is a complex task due to varying requirements for data volume, velocity, variety, and value. To address this, the Big Data Helper prototype is proposed, designed to assist in selecting the most suitable architecture for each specific scenario. Test results demonstrate the prototype's effectiveness and user-friendliness.

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