Cognitive Analytics Market: By Component (Tools and Service) Deployment Type (On-Premise and On-Demand), Organizational Size (Small & Medium Enterprises and Large Enterprises), Industry Vertical (IT & Telecom, BFSI, Retail & Consumer Goods, Manufacturing, Energy & Utilities, Media & Entertainment, Government & Defense, Healthcare & Life Science, Travel & Hospitality, and Others): Global Opportunity Analysis and Industry Forecast, 2023-2030 Market

Cognitive Analytics Market Statistics: 2027

Cognitive analytics applies human-like intelligence to certain tasks, and brings together a number of intelligent technologies, including semantics, artificial intelligence algorithms, deep learning, and machine learning. Applying such techniques, a cognitive application can get smarter and more effective over time by learning from its interactions with data and humans. It is a combination of artificial intelligence and data analytics to enable analytic tools to think like humans.

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 .

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.

Top impacting factors: Market Scenario Analysis, Trends, Drivers, and Impact Analysis

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. 

Lengthy deployment cycle  

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.

Rise in adoption of IoT devices    

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.

Key benefits of the report:

• This study presents the analytical depiction of the global cognitive analytics market along with the current trends and future estimations to determine the imminent investment pockets.
• The report presents information related to key drivers, restraints, and opportunities along with detailed analysis of global cognitive analytics market share.
• The current cognitive analytics market is quantitatively analyzed to highlight the global cognitive analytics market growth scenario.
• Porter’s five forces analysis illustrates the potency of buyers & suppliers in the market. 
• The report provides detailed cognitive analytics market analysis based on competitive intensity and how the competition will take shape in coming years. 

 Cognitive Analytics Market: By Component Report Highlights