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TopIntroduction To Importance Of Big Data
Big data are usually difficult to analyze big data to discover facts that can assist organizations in developing effective business choices, like hidden patterns, correlations, market trends, and customer preferentiality (Elia et al., 2020). Recently, there has been a lot of discussion about the role that big data analytics may play in helping organizations make better decisions. To gain a competitive advantage, an increasing number of companies are expediting the deployment of their big data analytics programs. Technologies and data analytics provide companies with analyzing data sources and collecting additional knowledge. Business intelligence (BI) analytics answers basic business and performance inquiries (Nguyen et al., 2016). Big data analytics is an advanced type of analysis involving complicated applications with predictive modelling, regression methods, and analytics-based analysis (Zheng et al., 2020).
With new technologies and data analytics, businesses may better understand their data sources and gather new information. Fundamental business and performance questions are addressed by BI analytics. Analysts use predictive modelling, regression procedures, and analytic approaches to analyze large amounts of data.
Organizations can make data-driven decisions that improve business results through big data analytics technologies and applications (Nguyen et al., 2018). The advantages may include better marketing, new income chances, personalization of customers, and increased operating efficiency (Manogaran et al., 2018). These factors offer a higher advantage over its competitors with an effective strategy (Nguyen et al., 2017). Even though academics and business leaders alike have hailed big data analytics as a game-changing innovation, the question of whether and under what circumstances these tools might boost a company's competitiveness persists.
Increasing volumes of structured data and other kinds of data, not usable by traditional BI and analytical programs, data analysts, data scientists, security analysts, statisticians, and other analytics specialists collect, process, purify and analyze all kinds of business data using Smart Technologies for E-Business and Commerce (Manogaran et al., 2018).
Collection Of Data
Data specialists from various sources gather information often a mixture of structured and unstructured material (Wang et al., 2013). While each company uses different data streams, some popular sources include (Nguyen et al., 2018),
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Data internet streaming
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Server logs in web
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Applications in cloud
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Applications using mobile
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Social media content
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Recording mobile phone data
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Capturing mobile data (Abd El-Latif et al., 2013).