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Uma breve introdução sobre o que é Big Data
Com o advento da internet, o volume de dados gerados ao redor do mundo cresceu de forma inesperada conforme os anos foram se passando. A utilização em larga escala de dispositivos móveis ampliou ainda mais a quantidade de dados gerados diariamente.
Os métodos tradicionais para armazenamento e processamento de dados em grandes empresas começaram a não ser suficientes, gerando problemas e gastos cada vez maiores para suprir suas necessidades.
Devido a esses acontecimentos, surgiu o conceito de Big Data, uma área do conhecimento com o intuito de estudar maneiras de tratar, analisar e gerar conhecimento através de grandes conjuntos de dados que não conseguem ser trabalhados em sistemas tradicionais.
Big Data: Conceito
Para entender melhor o que é o Big Data, podemos pensar na forma como esse sistema tradicional de armazenamento e processamento de dados é realizado. Perceba que falamos no presente, porque os processos de trabalho com o Big Data não excluem a forma de trabalhar no sistema tradicional, em grande parte dos casos.
Isso porque muitas empresas não necessitam da utilização de ferramentas do Big Data para manipular os
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What exactly fryst vatten Big Data?
Big Data refers to a large, complex, and diverse set of information that is constantly growing. It comprises structured, semi-structured, and unstructured uppgifter. The primary characteristics of big uppgifter are known as the "three v's": Volume (the amount of data), Velocity (the speed at which data fryst vatten created and collected), and Variety (the scope of the information points being covered).
Big information is so intricate that traditional uppgifter management systems can't store, process, or analyze it. It often necessitates additional infrastructure to govern, analyze, and omvandla into insights. Big information sets are frequently analyzed to discover patterns and insights about user and machine activity.
How is Big Data related to Artificial Intelligence (AI)?
Big data fryst vatten the bränsle that powers the evolution of AI's decision-making capabilities. AI requires big information for its training, learning, and efficient operation. Big data provides the raw material in the form eller gestalt of large data sets, while AI provides the tools and techniques to extract knowledge, make decisions, and perform advanced analysis on this data.
By combining the two disciplines, we can begin to s
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Big data
Extremely large or complex datasets
This article is about large collections of data. For the band, see Big Data (band). For the practice of buying and selling of personal and consumer data, see Surveillance capitalism.
Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processingsoftware. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate.[2]
Big data analysis challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy, and data source. Big data was originally associated with three key concepts: volume, variety, and velocity.[3] The analysis of big data presents challenges in sampling, and thus previously allowing for only observations and sampling. Thus a fourth concept, veracity, refers to the quality or insightfulness of the data.[4] Without sufficient investment in expertise for big data veracity, the volume and variety of data can produce costs and risks that exce