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Global Cognitive Analytics Market to reach USD 40.88 billion by the end of 2030

Global Cognitive Analytics Market Size study & Forecast, by Deployment (On-Premise, On-Demand), by Component (Tools, Services), by Technology Type (Natural Language Processing (NLP), Machine Learning, Automated Reasoning), by End User (BFSI, Manufacturing, IT & telecommunication, Aerospace and Defense, Healthcare, Retail and Consumer Goods and Other End-user Industries) and Regional Analysis, 2023-2030

Product Code: ICTNGT-58409375
Publish Date: 27-06-2023
Page: 200

Global Cognitive Analytics Market is valued at approximately USD 2.77 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 40% over the forecast period 2023-2030. Cognitive analytics refers to the use of advanced technologies, such as artificial intelligence (AI), machine learning, natural language processing, and data mining, to analyze and interpret complex sets of data and provide insights and actionable intelligence. It combines the fields of cognitive computing and data analytics to gain a deeper understanding of data and enable decision-making. The Cognitive Analytics Market is expanding because of factors such as the increasing adoption of big data and cloud computing and the increasing volume of unstructured data.

The rising volume of unstructured data across the globe is fostering market growth. International Data Corporation predicts that by 2025, there would be 175 zettabytes of data worldwide (that’s 175 with 21 zeros), with 80% of that data being unstructured, up from 2.6 ZB in 2018. In addition, the increasing adoption of cognitive computing technology and increasing adoption of AI based business applications is creating lucrative growth in the market. However, the high cost of cognitive analytics and complex analytical process stifles market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Cognitive Analytics Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to the dominance of key market players, a rising amount of data generation, and rising technological advancement in the region. Asia Pacific is expected to grow significantly during the forecast period, owing to factors such as rising demand from end use industries, and rising volume of data generated in the market space.

Major market player included in this report are:
Amazon Web Services, Inc.
Google LLC
Oracle Corporation
SAS Institute
International Business Machines Corporation
Intel Corporation
Microsoft Corporation
Cisco Systems Inc.
Narrative Science
Nuance Communications, Inc.

Recent Developments in the Market:
Ø In March 2023, Tata Consultancy Services (TCS) has announced the release of TCS Cognitive Plant Operations Adviser for the Microsoft Azure Private Mobile Edge Computing (PMEC) platform, a 5G-enabled solution. This will help businesses in industries including manufacturing, oil and gas, consumer packaged products, and pharmaceuticals as they restructure their output. This approach employs AI and machine learning to improve the intelligence, adaptability, and resilience of production.

Global Cognitive Analytics Market Report Scope:
ü Historical Data – 2020 – 2021
ü Base Year for Estimation – 2022
ü Forecast period – 2023-2030
ü Report Coverage – Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
ü Segments Covered – Deployment, Component, Technology Type, End User, Region
ü Regional Scope – North America; Europe; Asia Pacific; Latin America; Middle East & Africa
ü Customization Scope – Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and Componentofferings of key players. The detailed segments and sub-segment of the market are explained below:

By Deployment:

By Component:

By Technology Type:
Natural Language Processing (NLP)
Machine Learning
Automated Reasoning

By End User:
IT & telecommunication
Aerospace and Defense
Retail and Consumer Goods
Other End-user Industries

By Region:

North America


Asia Pacific
South Korea

Latin America

Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
1.2.1. Cognitive Analytics Market, by Region, 2020-2030 (USD Billion)
1.2.2. Cognitive Analytics Market, by Deployment, 2020-2030 (USD Billion)
1.2.3. Cognitive Analytics Market, by Component, 2020-2030 (USD Billion)
1.2.4. Cognitive Analytics Market, by Technology Type, 2020-2030 (USD Billion)
1.2.5. Cognitive Analytics Market, by End User, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Cognitive Analytics Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Cognitive Analytics Market Dynamics
3.1. Cognitive Analytics Market Impact Analysis (2020-2030)
3.1.1. Market Drivers Increasing adoption of big data and cloud computing Increasing Volume of Unstructured Data
3.1.2. Market Challenges High Cost of Cognitive Analytics Complex Analytical Process
3.1.3. Market Opportunities Increasing Adoption of Cognitive Computing Technology Increasing adoption of AI based business applications
Chapter 4. Global Cognitive Analytics Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Porter’s 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global Cognitive Analytics Market, by Deployment
5.1. Market Snapshot
5.2. Global Cognitive Analytics Market by Deployment, Performance – Potential Analysis
5.3. Global Cognitive Analytics Market Estimates & Forecasts by Deployment 2020-2030 (USD Billion)
5.4. Cognitive Analytics Market, Sub Segment Analysis
5.4.1. On-Premise
5.4.2. On-Demand
Chapter 6. Global Cognitive Analytics Market, by Component
6.1. Market Snapshot
6.2. Global Cognitive Analytics Market by Component, Performance – Potential Analysis
6.3. Global Cognitive Analytics Market Estimates & Forecasts by Component 2020-2030 (USD Billion)
6.4. Cognitive Analytics Market, Sub Segment Analysis
6.4.1. Tools
6.4.2. Services
Chapter 7. Global Cognitive Analytics Market, by Technology Type
7.1. Market Snapshot
7.2. Global Cognitive Analytics Market by Technology Type, Performance – Potential Analysis
7.3. Global Cognitive Analytics Market Estimates & Forecasts by Technology Type 2020-2030 (USD Billion)
7.4. Cognitive Analytics Market, Sub Segment Analysis
7.4.1. Natural Language Processing (NLP)
7.4.2. Machine Learning
7.4.3. Automated Reasoning
Chapter 8. Global Cognitive Analytics Market, by End User
8.1. Market Snapshot
8.2. Global Cognitive Analytics Market by End User, Performance – Potential Analysis
8.3. Global Cognitive Analytics Market Estimates & Forecasts by End User 2020-2030 (USD Billion)
8.4. Cognitive Analytics Market, Sub Segment Analysis
8.4.1. BFSI
8.4.2. Manufacturing
8.4.3. IT & telecommunication
8.4.4. Aerospace and Defense
8.4.5. Healthcare
8.4.6. Retail and Consumer Goods
8.4.7. Other End-user Industries
Chapter 9. Global Cognitive Analytics Market, Regional Analysis
9.1. Top Leading Countries
9.2. Top Emerging Countries
9.3. Cognitive Analytics Market, Regional Market Snapshot
9.4. North America Cognitive Analytics Market
9.4.1. U.S. Cognitive Analytics Market Deployment breakdown estimates & forecasts, 2020-2030 Component breakdown estimates & forecasts, 2020-2030 Technology Type breakdown estimates & forecasts, 2020-2030 End User breakdown estimates & forecasts, 2020-2030
9.4.2. Canada Cognitive Analytics Market
9.5. Europe Cognitive Analytics Market Snapshot
9.5.1. U.K. Cognitive Analytics Market
9.5.2. Germany Cognitive Analytics Market
9.5.3. France Cognitive Analytics Market
9.5.4. Spain Cognitive Analytics Market
9.5.5. Italy Cognitive Analytics Market
9.5.6. Rest of Europe Cognitive Analytics Market
9.6. Asia-Pacific Cognitive Analytics Market Snapshot
9.6.1. China Cognitive Analytics Market
9.6.2. India Cognitive Analytics Market
9.6.3. Japan Cognitive Analytics Market
9.6.4. Australia Cognitive Analytics Market
9.6.5. South Korea Cognitive Analytics Market
9.6.6. Rest of Asia Pacific Cognitive Analytics Market
9.7. Latin America Cognitive Analytics Market Snapshot
9.7.1. Brazil Cognitive Analytics Market
9.7.2. Mexico Cognitive Analytics Market
9.8. Middle East & Africa Cognitive Analytics Market
9.8.1. Saudi Arabia Cognitive Analytics Market
9.8.2. South Africa Cognitive Analytics Market
9.8.3. Rest of Middle East & Africa Cognitive Analytics Market

Chapter 10. Competitive Intelligence
10.1. Key Company SWOT Analysis
10.1.1. Company 1
10.1.2. Company 2
10.1.3. Company 3
10.2. Top Market Strategies
10.3. Company Profiles
10.3.1. Amazon Web Services, Inc. Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
10.3.2. Google LLC
10.3.3. Oracle Corporation
10.3.4. SAS Institute
10.3.5. International Business Machines Corporation
10.3.6. Intel Corporation
10.3.7. Microsoft Corporation
10.3.8. Cisco Systems Inc.
10.3.9. Narrative Science
10.3.10. Nuance Communications, Inc.
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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