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Global Cloud Analytics Market to reach USD 98.81 billion by the end of 2029

Global Cloud Analytics Market Size study & Forecast, by Solution (Cloud BI Tools, Hosted Data Warehouse Solutions, Complex Event Processing, Enterprise Information Management, Enterprise Performance Management, Governance, Risk, and Compliance, Analytics Solutions), by Deployment Mode (Public Cloud, Private Cloud, Hybrid Cloud), by Organization Size (SMEs, Large Enterprises), by End-User (Retail and Consumer Goods, Healthcare and Life Sciences, Media and Entertainment, Telecom and IT, Others) and Regional Analysis, 2022-2029

Product Code: ICTBC-75380601
Publish Date: 19-12-2022
Page: 200

Global Cloud Analytics Market is valued at approximately USD 18.86 billion in 2021 and is anticipated to grow with a healthy growth rate of more than 23.0% over the forecast period 2022-2029. Cloud analytics is generally adopted to analyze data by using cloud computing. This helps in streamlining business processes through the help of various analytical tools and techniques for extracting information from massive data. Factors such as the growing adoption of cloud-based applications, increasing trend for digitalization, and a massive rise in big data, coupled with the rising data connectivity via hybrid and multi-cloud environments are driving market growth across the globe.

According to Statista, the market for cloud applications was valued at USD 133.6 billion in 2020, which is expected to grow to USD 168.6 billion by 2025. Therefore, the rising inclination towards cloud-based applications among the end-users is leveraging the market expansion into the global market. Moreover, the scarcity of in-house IT expertise and equipment and the cost benefits of cloud-based analytics solutions are providing various growth opportunities over the forthcoming period. However, security and privacy concerns for confidential data and difficulties in running input/output-intensive applications are hindering market growth throughout the forecast period of 2022-2029.

The key regions considered for the Global Cloud Analytics Market study include Asia Pacific, North America, Europe, Latin America, and the Rest of the World. North America dominated the market in terms of revenue, owing to the increasing investments in technological advancements and the high presence of leading market vendors. Whereas, the Asia Pacific is expected to grow with the highest growth rate during the forecast period. Factors such as the rising adoption of AI and NLP technologies in various applications, the increasing number of start-up companies, as well as development of emerging economies, are burgeoning the market growth in the forecasting years.

Major market players included in this report are:
Microsoft Corporation
Google LLC
Oracle Corporation
IBM
Salesforce
SAP SE
TIBCO Software
SAS Institute
Teradata
MicroStrategy
Recent Developments in the Market:
 In July 2020, Google Cloud introduced its two new security offerings that are Assured Workloads for governments and Confidential VM to serve its customers in highly regulated and security-sensitive industries including healthcare, public sector, and financial services.
 In July 2020, Microsoft unveil its next-generation of Azure Stack HCI service. Microsoft is rolling out a broadcast of Azure Stack HCI v2, which allows users to perform their service on their own servers and like built-in integration with Azure Arc with other new features. The new iteration of Azure Stack HCI announced is a new host OS separated from Windows Server, which is designed specifically to run HCI and is integrated with Azure with hybrid by design.
 In July 2020, Google Cloud declared the introduction of its BigQuery Omni that enables its customers to gather the power of BigQuery to data stored in Google Cloud, Amazon Web Services (AWS), and Azure. This new innovation offers secure and cost-effective access, analysis, and new insights to power innovation in their business.

Global Cloud Analytics Market Report Scope:
Historical Data 2019-2020-2021
Base Year for Estimation 2021
Forecast period 2022-2029
Report Coverage Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
Segments Covered Solution, Deployment Mode, Organization Size, End-User, Region
Regional Scope North America; Europe; Asia Pacific; Latin America; Rest of the World
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 product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Solution:
Cloud BI Tools
Hosted Data Warehouse Solutions
Complex Event Processing
Enterprise Information Management
Enterprise Performance Management
Governance, Risk, and Compliance
Analytics Solutions

By Deployment Mode:
Public Cloud
Private Cloud
Hybrid Cloud

By Organization Size:
SMEs
Large Enterprises

By End-User:
BFSI
Retail and Consumer Goods
Healthcare and Life Sciences
Media and Entertainment
Telecom and IT
Others

By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
ROLA
Rest of the World

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2029 (USD Billion)
1.2.1. Cloud Analytics Market, by Region, 2019-2029 (USD Billion)
1.2.2. Cloud Analytics Market, by Solution, 2019-2029 (USD Billion)
1.2.3. Cloud Analytics Market, by Deployment Mode, 2019-2029 (USD Billion)
1.2.4. Cloud Analytics Market, by Organization Size, 2019-2029 (USD Billion)
1.2.5. Cloud Analytics Market, by End-User, 2019-2029 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Cloud Analytics Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Cloud Analytics Market Dynamics
3.1. Cloud Analytics Market Impact Analysis (2019-2029)
3.1.1. Market Drivers
3.1.1.1. Growing adoption of cloud-based applications
3.1.1.2. Increasing trend for digitalization and massive rise in big data
3.1.2. Market Challenges
3.1.2.1. Security and privacy concerns for confidential data
3.1.2.2. Difficulties in running input/output-intensive applications
3.1.3. Market Opportunities
3.1.3.1. Scarcity of in-house IT expertise and equipment
3.1.3.2. Cost benefits of cloud-based analytics solutions
Chapter 4. Global Cloud 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. Futuristic Approach to Porter’s 5 Force Model (2019-2029)
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. Industry Experts Prospective
4.7. Analyst Recommendation & Conclusion

Chapter 5. Risk Assessment: COVID-19 Impact
5.1. Assessment of the overall impact of COVID-19 on the industry
5.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global Cloud Analytics Market, by Solution
6.1. Market Snapshot
6.2. Global Cloud Analytics Market by Solution, Performance – Potential Analysis
6.3. Global Cloud Analytics Market Estimates & Forecasts by Solution 2019-2029 (USD Billion)
6.4. Cloud Analytics Market, Sub Segment Analysis
6.4.1. Cloud BI Tools
6.4.2. Hosted Data Warehouse Solutions
6.4.3. Complex Event Processing
6.4.4. Enterprise Information Management
6.4.5. Enterprise Performance Management
6.4.6. Governance, Risk, and Compliance
6.4.7. Analytics Solutions
Chapter 7. Global Cloud Analytics Market, by Deployment Mode
7.1. Market Snapshot
7.2. Global Cloud Analytics Market by Deployment Mode, Performance – Potential Analysis
7.3. Global Cloud Analytics Market Estimates & Forecasts by Deployment Mode 2019-2029 (USD Billion)
7.4. Cloud Analytics Market, Sub Segment Analysis
7.4.1. Public Cloud
7.4.2. Private Cloud
7.4.3. Hybrid Cloud
Chapter 8. Global Cloud Analytics Market, by Organization Size
8.1. Market Snapshot
8.2. Global Cloud Analytics Market by Organization Size, Performance – Potential Analysis
8.3. Global Cloud Analytics Market Estimates & Forecasts by Organization Size 2019-2029 (USD Billion)
8.4. Cloud Analytics Market, Sub Segment Analysis
8.4.1. SMEs
8.4.2. Large Enterprises
Chapter 9. Global Cloud Analytics Market, by End-User
9.1. Market Snapshot
9.2. Global Cloud Analytics Market by End-User, Performance – Potential Analysis
9.3. Global Cloud Analytics Market Estimates & Forecasts by End-User 2019-2029 (USD Billion)
9.4. Cloud Analytics Market, Sub Segment Analysis
9.4.1. Retail and Consumer Goods
9.4.2. Healthcare and Life Sciences
9.4.3. Media and Entertainment
9.4.4. Telecom and IT
9.4.5. Others
Chapter 10. Global Cloud Analytics Market, Regional Analysis
10.1. Cloud Analytics Market, Regional Market Snapshot
10.2. North America Cloud Analytics Market
10.2.1. U.S. Cloud Analytics Market
10.2.1.1. Solution breakdown estimates & forecasts, 2019-2029
10.2.1.2. Deployment Mode breakdown estimates & forecasts, 2019-2029
10.2.1.3. Organization Size breakdown estimates & forecasts, 2019-2029
10.2.1.4. End-User breakdown estimates & forecasts, 2019-2029
10.2.2. Canada Cloud Analytics Market
10.3. Europe Cloud Analytics Market Snapshot
10.3.1. U.K. Cloud Analytics Market
10.3.2. Germany Cloud Analytics Market
10.3.3. France Cloud Analytics Market
10.3.4. Spain Cloud Analytics Market
10.3.5. Italy Cloud Analytics Market
10.3.6. Rest of Europe Cloud Analytics Market
10.4. Asia-Pacific Cloud Analytics Market Snapshot
10.4.1. China Cloud Analytics Market
10.4.2. India Cloud Analytics Market
10.4.3. Japan Cloud Analytics Market
10.4.4. Australia Cloud Analytics Market
10.4.5. South Korea Cloud Analytics Market
10.4.6. Rest of Asia Pacific Cloud Analytics Market
10.5. Latin America Cloud Analytics Market Snapshot
10.5.1. Brazil Cloud Analytics Market
10.5.2. Mexico Cloud Analytics Market
10.5.3. Rest of Latin America
10.6. Rest of The World Cloud Analytics Market

Chapter 11. Competitive Intelligence
11.1. Top Market Strategies
11.2. Company Profiles
11.2.1. Microsoft Corporation
11.2.1.1. Key Information
11.2.1.2. Overview
11.2.1.3. Financial (Subject to Data Availability)
11.2.1.4. Product Summary
11.2.1.5. Recent Developments
11.2.2. Google LLC
11.2.3. Oracle Corporation
11.2.4. IBM
11.2.5. Salesforce
11.2.6. SAP SE
11.2.7. TIBCO Software
11.2.8. SAS Institute
11.2.9. Teradata
11.2.10. MicroStrategy
Chapter 12. Research Process
12.1. Research Process
12.1.1. Data Mining
12.1.2. Analysis
12.1.3. Market Estimation
12.1.4. Validation
12.1.5. Publishing
12.2. Research Attributes
12.3. 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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