Analytics as a service (AaaS) has been developed from the integration of cloud computing and analytics solutions. It ingests data and information from different sources and integrates it into a fully-managed data center. Analytics as a service provides services based on the subscription model. It includes cloud-based business intelligence solutions and software as a service-based (SaaS) social media analytics-as-a-service solution. Cloud-based business intelligence solutions efficiently provide business analytics solutions to consumers at a lower cost. On the other hand, SaaS-based social media analytics-as-a-service solution involves remote positioning of a variety of tools that help in analyzing visitors’ behavior and trends; collecting the data; and finding advanced techniques to serve clients in a better manner.
Analytics as a service helps in implementing and managing analytics infrastructure on-premises. It is also employed to cut preventable losses; enhance operational efficiency; and create new opportunities for customers. Furthermore, analytics as a service aids individuals by providing them with personalized access to centrally managed information data groups. This, in turn, eliminates several delays faced by business analysts, data scientists, and other information users. It allows them to discover information data sets more interactively and explore richer insights more quickly.
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The global analytics-as-a-service market is expanding at a higher pace, owing to factors such as rising adoption of social media applications and constantly rising demand for advanced technologies to process high workload through cloud. This is primarily due to continuous increase in the volume of structured and unstructured data from multiple social media platforms. Apart from this, lower cost of ownership is also key factor which is expected to propel the demand for analytics as a service across the world during the forecast period. However, availability of complex analytical workflow and data and security concerns are major factors anticipated to hinder the global analytics-as-a-service market in the near future.
Surge in the volume of data across different end-use industries and increase in usage of machine-generated data are key factors which are anticipated to offer immense growth opportunities to the analytics-as-a-service market in the next few years.
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The global analytics-as-a-service market can be segmented based on component, analytics type, enterprise size, deployment type, and end-use industries. Based on component, the market has been divided into solutions and services. Based on analytics type, the global analytics-as-a-service market has been segmented into prescriptive analytics, predictive analytics, diagnostic analytics, and descriptive analytics. In terms of enterprise size, the market has been categorized into small- and medium-sized enterprises (SMEs) and large enterprises. Based on deployment type, the global analytics-as-a-service market has been classified into private cloud, public cloud, and hybrid. Furthermore, in terms of end-use industries, the analytics-as-a-service market has been segregated into transportation & logistics, BFSI, IT & telecom, health care, government, retail, manufacturing, energy & utilities, travel & hospitality, and others.
Geographically, the global analytics-as-a-service market can be segmented into Europe, North America, South America, Middle East & Africa, and Asia Pacific. The analytics-as-a-service market in North America is expected to expand at a high growth rate during the forecast period. This primarily due to presence of a large number of technical experts and large enterprises and rise in the demand for analytics-as-a-service solutions and services across the region. However, Asia Pacific is projected to provide lucrative growth opportunities to the analytics-as-a-service market in the near future. Surge in the volume of data through different channels such as mobile computing, social media, and Internet of Things (IoT) is the primary driving factor for the market in Asia Pacific.
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