Analytics as a Service Market Driven by the Growing Demand for Machine Learning

Market Research Future has published a Half-Cooked Research Report on the Global Analytics as a Service Market.

Market Synopsis

In the research report, Market Research Future (MRFR), emphasizes that the global Analytics as a Service Market 2020 is slated to grow exponentially, securing a substantial market valuation of USD 40.1 Billion, and a healthy 27.82% CAGR over the review period 2023-2030.

Drivers and Restraints

Analytical operations are designed using an expandable set of resources using an analytical algorithm that is focused mostly on concepts of deep learning and machine learning. The driving factors for the development of analytical services include the rising understanding among business enterprises of internet of things (IoT) and the increasing adoption of social media use. Nevertheless, it is anticipated that a massive demand for a large amount of data that needs to be processed and effective processing will gain considerable popularity over the forecast era. In addition, Analytics as a service provides multiple benefits, such as experiential forecasts and the ability to classify the patterns which are expected to develop a huge demand for the market over the next few years. Analytics as a service market's main growth driver includes rising analytics mobile app industry, increasing organizations' investment in analytics as a service to keep focusing on business data processing, and increasing adoption of cloud-based services among others.

On the flipside, advanced computational methods such as machine learning are challenging and require a broad set of skills. Therefore, in the coming years, the lack of domain-specific knowledge is expected to be one of the hindrances for the analytics as a service industry. Information security risks and complex workflow processes are therefore some of the factors that impede the growth of Analytics as a service market

Segmental Analysis

The Analytics as a Service market is analyzed into the organization size, component, analytics type, deployment, and end-user.

By Component, the market is bifurcated as solutions and services. The solution segment is segmented into financial analytics, risk analytics, marketing analytics, customer analytics, sales analytics, web and social analytics, network analytics, supply chain analytics, and others

By service, the segment is further is segmented into consulting, managed service, and support & maintenance. The Analytics type is segregated into prescriptive, predictive, diagnostics, and descriptive. The deployment segment is divided into private, public, and hybrid. On the basis of organization size, the Analytics as a Service market is divided as large enterprises and small and medium enterprises (SMEs).

Lastly, the Analytics as a Service market is sub-segmented into end user which BFSI, government, healthcare & life sciences, manufacturing, retail & E-commerce, IT & telecom, energy and utility, travel & hospitality, media & entertainment, transportation and logistics, and others.

Regional Analysis

The geographical analysis of the global Analytics as a Service market has been conducted in four significant regions, including the Asia Pacific, North America, Europe, and the rest of the world.

The presumed growth of North America as a service market in Analytics is important. This is due to the existence of a growing number of providers of solutions, and the rising demand for big data. Over the forecast era, Asia Pacific is also projected to be the fastest-growing area on Analytics as a service market. As a service sector, India, South Korea, Japan, and China are the leading analytics countries. It is due to the rising demand for large data storage volumes such as big data and cloud computing. India is also considered to be the fastest-growing economy due to huge investments by developed economies in building IT infrastructure in the country.

Competitive Overview

The major market players operating in the global market as acknowledged by MRFR are IBM Corporation (U.S.), Hewlett-Packard Enterprise (U.S.), Oracle Corporation (U.S.), 1010 Data Inc. (U.S.), Google Inc. (U.S.), EMC Corporation (U.S.), Amazon (U.S.), Hitachi, Ltd. (Japan), Good data Corporation (U.S.), SAS Institute (U.S.), and Cloudera, Inc. (U.S.)