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More accurate decision-making: in a NewVantage Partners survey, 36.2% of respondents said that better decision-making was their primary goal of big data's analytical work. In addition, 84.1% of respondents said they had begun to work towards this goal, and 59.0% of respondents said they had achieved some measurable success, with an overall success rate of 69.0%. Big data analysis can provide business decision makers with the data-driven insight they need to help enterprises compete and develop their business.

Improve productivity: another survey from supplier Syncsort found that 59.9% of respondents used big data tools such as Hadoop and Spark to improve business productivity. Modern big data tools enable analysts to analyze more data faster, thereby improving personal productivity. In addition, the insights gained from these analyses often enable organizations to increase productivity more widely throughout the company.

Cost reduction: surveys by Syncsort and NewVantage have found that big data's analysis is helping companies reduce costs. Nearly 3/5 (59.4%) of respondents said that Syncsort's big data tool had helped them improve operational efficiency and reduce costs, and about 2/3 (66.7%) of respondents in the NewVantage survey said they had started to use big data to reduce costs. Interestingly, however, only 13.0% of the respondents chose cost reduction as the main goal of big data's analysis, indicating that for many people, this is just a very popular side benefit.

Improving customer service: among the respondents surveyed by NewVantage, improving customer service was the second most common major goal of big data's analysis project, and 53.4% of the respondents said they had some success in this regard. Social media, customer relationship management (CRM) systems, and other customers provide today's businesses with a great deal of information about their customers, and it is natural for them to use this data to better serve them.

Fraud detection: another common use of big data's analysis is fraud detection, especially in the financial services industry. One of the advantages of big data analysis systems, which rely on machine learning, is that they are excellent at detecting patterns and anomalies. These capabilities allow banks and credit card companies to detect stolen credit cards or fraudulent purchases, usually before cardholders know there is a problem.

Increase revenue: when organizations use big data to improve decision-making and customer service, increasing revenue is usually a natural result. In the Syncsort survey, more than half of the respondents (54.7%) said they were using big data tools to increase revenue and accelerate growth based on better insight.

Improve flexibility: similarly, from the Syncsort survey, 41.7% of respondents said that one of big data's benefits is the ability to improve business / IT agility. Many organizations are using their big data to better adjust their IT and business efforts, and they are using their analytics to support faster and more frequent changes to their business strategies and policies.

Better innovation: innovation is another common interest of big data, and a survey by NewVantage found that 11.6% of executives are investing in analysis, mainly as a means of innovation and market subversion. They believe that if they can collect insights that competitors do not have, they can stay ahead of other companies with new products and services.

Time-to-market speed: in these areas, many companies say they will use big data to speed up their products to market. Only 8.8% of the respondents said this was big data's primary goal, but 53.6% of the respondents had begun to work towards this goal, of which 54.1% said they had achieved some success. Big data's advantage may also bring additional benefits, such as faster growth and higher income.

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