Cognitive analytics tool continuously learns from data and human machine interactions to become smarter, having a goal to blend traditional analytics technique with AI and ML features for advanced analytics outcome. Improved customer engagement, high productivity efficiency, and high business growth are some of the expected benefits of the cognitive analytics market.
One of the greatest challenges of cognitive analytics is the time invested on development of scenario-based applications via cognitive computing. As development cycle of cognitive analytics is very lengthy and it cannot be implemented across multiple industry segments as it requires powerful development teams and a considerable amount of time to develop a solution, thus restrains growth of the cognitive analytics market.
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COVID-19 scenario Analysis:
➢ The emergence of COVID-19 pandemic has severely affected almost all industries across the world. Further, lockdown enforcements and restrictions on movements of non-essential goods as well as resources in various countries has disrupted supply chain of electronic components & networking equipment. Thus, this has led to delay in supply of electronic components required in manufacturing of network equipment.
➢ Adoption of big data and artificial intelligence (AI) are set to increase, though global IT spending is expected to drop 3 to 4% this year, with a severe impact on hardware and slowdown in software and services business.
➢ Data science teams are being called into action to crunch petabytes of data and build best business models on trusted data for decision makers to quickly prepare contingency plans. This is where enterprises use AI, machine learning, and natural language processing to mine data and build predictive or prescriptive models.
➢ The COVID-19 crisis is an opportunity for IT vendors to build and improve their capabilities on AI and big data. Relatively smaller companies are also launching dedicated AI-based apps to assist people in the crisis and are adopting different analytical strategies, which is expected to impact the market positively.
➢ However, it is expected that the COVID-19 pandemic has resulted in growing use of big data, machine learning, automated reasoning, and natural language processing as tools to limit spread of the contagion, which increases demand for cognitive systems spending.
➢ In addition, these trends have an impact on government, finance, insurance, and investment services, which could potentially generate improved revenue flow in the cognitive systems spending market, which is opportunistic for the market.
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Factors such as rise in adoption of cognitive computing technology, introduction of advanced analytics techniques, growth in penetration of IoT devices, and continuously generation massive volume of unstructured data, are expected to drive growth of the cognitive analytics market. However, complex adoption and lengthy development cycle hinders growth of the market. Furthermore, increase in adoption of cloud technology among small and medium enterprises create numerous opportunities for the global cognitive analytics market.
Adoption of internet of things (IoT) devices is continuously increasing and number of sensors integrated in these devices are expected to generate massive amount of data over the period. Organizations are able to predict future data obtained by sensors that it has capacity to transfer large amount of data over network. The huge volume of data produced and transmitted from sensing devices can provide a lot of information but is often considered next big data challenge for businesses. To deal with that challenge, sensor data analytics is a growing field of endeavor and is expected to increase adoption of cognitive analytical tools in the upcoming years.
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Leading Market Players:
➢ Cisco System, Inc
➢ IBM Corporation
➢ Tata Consultancy Services Limited
➢ Nuance Corporation
➢ Intel Corporation
➢ Amazon Web Service Inc.
➢ SAP SE
➢ Microsoft Corporation
➢ Google LLC
➢ Oracle Corporation
These players have adopted various strategies to increase their market penetration and strengthen their position in the industry. Current and future Data Warehouse as a Service market trends are outlined to determine the overall attractiveness of the market.
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