Using big data in decision-making

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Using big data


Modern companies use big data to extract valuable information, thanks to sophisticated analytical tools and data processing algorithms. This process includes not only analyzing customer purchasing behavior and preferences, but also predicting future market trends, identifying inefficient operations and optimizing supply chains. Special attention is paid to the analysis of consumer data, because understanding customer interactions with products or services allows businesses to adapt their marketing and sales strategies to meet the specific needs of their target audience.

Big data analytics also helps optimize internal business processes. Companies can identify bottlenecks in their operational processes, improve inventory management, and increase logistics efficiency. This not only reduces costs cambodia rcs data but also improves the overall quality of customer service.

Basic Big Data technologies
Big Data involves the use of various technologies to efficiently store, process, and analyze large amounts of information. Some of the most popular technologies in this area include Hadoop, Spark, and NoSQL databases. Let's consider the role and functionality of these technologies in big data processing processes.

Hadoop is open source software specifically designed to store and process large data sets on clusters consisting of cost-effective servers.
Spark is another open source project designed for efficient real-time data processing and analysis.
NoSQL databases are a category of systems that differ from traditional relational databases in their flexibility and scalability. They allow you to store and process large amounts of both structured and unstructured data, providing convenience in working with a variety of information formats.
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