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Big data - Statistics & Facts

"Big data" refers to data sets that are too large or too complex for traditional data processing applications. The term is often used to refer to predictive analytics or other methods of extracting value from data. In order to harness big data, businesses rely on storage and processing power as well as strong analytics capabilities and skills. By 2025, annual revenue from the global big data analytics market is expected to reach 68.09 billion U.S. dollars. Some of the total revenue comes from the advanced and predictive analytics software segment, which assists in making business outcomes predictable through data mining and uses predictive modeling to analyze various historical data.

Data volume

While not every piece of data finds its way into the big data ecosystem, a number of figures already highlight the challenge of making good use of data amongst the rest. In 2021, it was projected that the overall amount of data created worldwide would reach 79 zettabytes, and would more than double by 2025 with no end in sight. However, 90 percent of the data in the global datasphere is replicated data, while only 10 percent is unique data. What also contributes to the rapid growth of data traffic is the internet of things (IoT), which is already connecting the digital and physical worlds through a network of sensors. The data volume created by global IoT connections already reached 13.6 zettabytes in 2019 and is forecast to amount to over 79 zettabytes by 2025.

Consumption of big data

The need for digital transformation and innovation are among the key drivers for investing in artificial intelligence (AI) and big data technologies. As of 2021, the state of big data and AI among surveyed U.S. organizations was an overall focus towards driving innovation with data, with almost a third indicating active transformational business outcomes within their companies. As of 2020, the United States, Germany, and the United Kingdom lead the world in data-driven decision-making in organizations, with popular sectors such as banking, insurance, and telecom.

Major players in big data

The major providers of big data and analytics software include global names such as Oracle, Microsoft, SAP, and IBM. They each offer specialized software tools and applications for advanced and predictive analytics, data mining, forecasting, and also data optimization. Even though these processes are all separate, they are still highly integrated functions of big data analytics that come together to assist their clients with data-focused business decisions for the future of their company. Other noteworthy companies that specialize in more specific functions of big data analytics include SAS, who leads the advanced and predictive analytics software segment, as well as Informatica, who leads the analytic data integration and integrity software segment.

Cloud computing

Given the high value of data volume used for big data analytics, companies have turned to cloud computing, which remotely takes the data in and performs various operations on the data from a set of powerful remote servers, or the “cloud”. Cloud computing offers on-demand storage and computing capacity and can view and query large data sets efficiently. Enterprise spending for cloud computing and data centers has seen rapid growth in recent years. In 2020, 129.5 billion U.S. dollars of enterprise spending was for cloud infrastructure services alone, while 89 billion U.S. dollars was spent on data center hardware and software, which houses the cloud.

Cloud strategies & providers

Global enterprises’ most utilized cloud strategy was hybrid cloud, which includes a mix of private and public cloud services. Private cloud is either managed by the company themselves or by a third-party, while public cloud is essentially renting a fraction of a service providers’ data center infrastructure, such as with AWS or Microsoft Azure. By combining these types of clouds, companies are able to utilize both and see the benefits of each. When organizations were asked to rank their cloud business intelligence (BI) provider preferences, Microsoft Azure, Amazon Web Services (AWS), and Google Cloud were the top three. Other choices for providers include Oracle Cloud, Alibaba, and IBM Cloud. It is worth noting that given the overwhelming popularity of hybrid cloud, a companies’ choice for a cloud provider heavily relies on the providers’ multicloud and hybrid cloud support.

Key figures

The most important key figures provide you with a compact summary of the topic of "Big data" and take you straight to the corresponding statistics.

Segments

Companies

Cloud computing

Data centers

Interesting statistics

In the following 5 chapters, you will quickly find the 37 most important statistics relating to "Big data".

Big data

Dossier on the topic

All important statistics are prepared by our experts – available for direct download as PPT & PDF!
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Big data - Statistics & Facts

"Big data" refers to data sets that are too large or too complex for traditional data processing applications. The term is often used to refer to predictive analytics or other methods of extracting value from data. In order to harness big data, businesses rely on storage and processing power as well as strong analytics capabilities and skills. By 2025, annual revenue from the global big data analytics market is expected to reach 68.09 billion U.S. dollars. Some of the total revenue comes from the advanced and predictive analytics software segment, which assists in making business outcomes predictable through data mining and uses predictive modeling to analyze various historical data.

Data volume

While not every piece of data finds its way into the big data ecosystem, a number of figures already highlight the challenge of making good use of data amongst the rest. In 2021, it was projected that the overall amount of data created worldwide would reach 79 zettabytes, and would more than double by 2025 with no end in sight. However, 90 percent of the data in the global datasphere is replicated data, while only 10 percent is unique data. What also contributes to the rapid growth of data traffic is the internet of things (IoT), which is already connecting the digital and physical worlds through a network of sensors. The data volume created by global IoT connections already reached 13.6 zettabytes in 2019 and is forecast to amount to over 79 zettabytes by 2025.

Consumption of big data

The need for digital transformation and innovation are among the key drivers for investing in artificial intelligence (AI) and big data technologies. As of 2021, the state of big data and AI among surveyed U.S. organizations was an overall focus towards driving innovation with data, with almost a third indicating active transformational business outcomes within their companies. As of 2020, the United States, Germany, and the United Kingdom lead the world in data-driven decision-making in organizations, with popular sectors such as banking, insurance, and telecom.

Major players in big data

The major providers of big data and analytics software include global names such as Oracle, Microsoft, SAP, and IBM. They each offer specialized software tools and applications for advanced and predictive analytics, data mining, forecasting, and also data optimization. Even though these processes are all separate, they are still highly integrated functions of big data analytics that come together to assist their clients with data-focused business decisions for the future of their company. Other noteworthy companies that specialize in more specific functions of big data analytics include SAS, who leads the advanced and predictive analytics software segment, as well as Informatica, who leads the analytic data integration and integrity software segment.

Cloud computing

Given the high value of data volume used for big data analytics, companies have turned to cloud computing, which remotely takes the data in and performs various operations on the data from a set of powerful remote servers, or the “cloud”. Cloud computing offers on-demand storage and computing capacity and can view and query large data sets efficiently. Enterprise spending for cloud computing and data centers has seen rapid growth in recent years. In 2020, 129.5 billion U.S. dollars of enterprise spending was for cloud infrastructure services alone, while 89 billion U.S. dollars was spent on data center hardware and software, which houses the cloud.

Cloud strategies & providers

Global enterprises’ most utilized cloud strategy was hybrid cloud, which includes a mix of private and public cloud services. Private cloud is either managed by the company themselves or by a third-party, while public cloud is essentially renting a fraction of a service providers’ data center infrastructure, such as with AWS or Microsoft Azure. By combining these types of clouds, companies are able to utilize both and see the benefits of each. When organizations were asked to rank their cloud business intelligence (BI) provider preferences, Microsoft Azure, Amazon Web Services (AWS), and Google Cloud were the top three. Other choices for providers include Oracle Cloud, Alibaba, and IBM Cloud. It is worth noting that given the overwhelming popularity of hybrid cloud, a companies’ choice for a cloud provider heavily relies on the providers’ multicloud and hybrid cloud support.

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