stručni rad
In analyzing large volumes of data (commonly referred to as Big Data), particular attention
should be given to the flow of these vast datasets and their impact on systems, computing
infrastructures, and networks. Modern data ecosystems must handle unprecedented levels of
throughput and complexity, demanding innovative approaches to data storage and retrieval.
Consequently, both traditional relational database management systems (SQL) and nonrelational (NoSQL) databases have emerged as critical tools. While SQL databases excel at
handling structured data with well-defined schemas, NoSQL solutions are better suited for
large-scale, unstructured, or semi-structured datasets that require high scalability and flexible
schemas. The Web environment plays a central role in driving this continual influx of
information, generating data at a global scale from an ever-increasing number of sources. Web
applications, social media platforms, and interconnected devices contribute to the creation of
complex data streams, which, when properly collected and analyzed, can inform strategic
decision-making. As these flows of Big Data continue to evolve, organizations need robust,
scalable architectures and interdisciplinary expertise to fully harness the potential of these
data-rich environments for innovation and growth
Big Data; data analytics; data storage; decision-making; large volumes of data; NoSQL; scalability; unstructured data
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