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Global Analytics as a Service Market to reach USD 462.91 billion by the end of 2030

Global Analytics as a Service Market Size study & Forecast, by Component (Solutions and Services), By Analytics Type (Predictive Analytics, Prescriptive Analytics, Diagnostic Analytics, Descriptive Analytics), By Deployment Type (Private Cloud, Public Cloud, Hybrid Cloud), By Industry Vertical (BFSI, Retail, Government & Public Sector, IT & Telecommunication, Transportation & Logistics, Manufacturing, and Others) and Regional Analysis, 2023-2030

Product Code: ICTICTS-28276442
Publish Date: 20-07-2023
Page: 200

Global Analytics as a Service Market is valued at approximately USD 34.99 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 38.1% over the forecast period 2023-2030. Analytics as a Service offers businesses fully customizable and comprehensive business intelligence solutions that cover the entire data lifecycle, including data organization, analysis, and presentation. These solutions are specifically designed to empower non-technical professionals, enabling them to extract valuable insights from data and make well-informed decisions. The Analytics as a Service Market is expanding because of factors such as increasing Cloud Adoption and increasing awareness of IoT devices. Moreover, the growth of Software as a Service can be attributed to several factors, including increased adoption of cloud-based solutions, seamless integration with other tools, and the utilization of centralized data-driven analytics.

According to Statista in 2023, the global market for cloud applications was valued at USD 133.6 billion in 2021, and it is projected to reach USD 168.6 billion by 2025. The cloud applications software market is expected to grow at a compound annual growth rate (CAGR) of 4.8 percent. The growing demand for Analytics as a Service (AaaS) is driven by the rising number of IoT devices and the requirement for cost-effective analytics solutions. Organizations are seeking analytics capabilities without significant investments, leading to an increased demand for AaaS. According to Statista in 2022, the global count of Internet of Things (IoT) devices is projected to nearly triple, going from 9.7 billion in 2020 to over 29 billion by 2030. By 2030, China is expected to have the highest number of IoT devices, with approximately 5 billion consumer devices. In addition, technological advancements in analytics as a service and increasing demand for customized AaaS solutions would create a lucrative growth opportunity. However, data security concerns and a lack of skilled professionals stifle market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Analytics as a Service Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. period, North America dominated the region during the forecast period owing to the factors such , rising adoption of cloud solutions, increased demand for advanced analytics capabilities and the need for cost-effective analytics solutions. Asia Pacific is expected to grow significantly during the forecast period, owing to factors such as the rising number of analytics firms and increased investments in emerging analytics companies within the region.

Major market player included in this report are:
Microsoft Corporation
Oracle Corporation
SAP societas Europaea
Hewlett Packard Enterprise Development LP
TIBCO Software Inc.
Amazon Web Services, Inc.
GoodData Corporation
SAS Institute Inc.
International Business Machines Corporation
Google LLC

Recent Developments in the Market:

Ø In October 2021, Amazon launched the Search Analytics Dashboard, the latest tool that assists Brand Registry merchants in gathering insights from their product search performance. The Search Analytics Dashboard gives retailers access to a wealth of anonymized data that will help them better understand their consumers’ interests and purchasing preferences for their products.

Ø In April 2022 Kyndryl announced an expansion of its partnership with SAP, aimed at helping customers overcome digital transformation challenges. As part of this expanded collaboration, Kyndryl offered services that complemented the RISE with SAP solution. These services included proven migration tools, scalable offerings, AI-driven business data management, analytics solutions and application modernization.

Global Analytics as a Service 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 – Component, Analytics Type, Deployment Type, Industry Vertical, 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 product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Component:

By Analytics Type:
Predictive Analytics
Prescriptive Analytics
Diagnostic Analytics
Descriptive Analytics

By Deployment Type:
Private Cloud
Public Cloud
Hybrid Cloud

By Industry Vertical:
Government & Public Sector
IT & Telecommunication
Transportation & Logistics

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. Analytics as a Service Market, by Region, 2020-2030 (USD Billion)
1.2.2. Analytics as a Service Market, by Component , 2020-2030 (USD Billion)
1.2.3. Analytics as a Service Market, by Analytics Type , 2020-2030 (USD Billion)
1.2.4. Analytics as a Service Market, by Deployment Type , 2020-2030 (USD Billion)
1.2.5. Analytics as a Service Market, by Industry Vertical , 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Analytics as a Service 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 Analytics as a Service Market Dynamics
3.1. Analytics as a Service Market Impact Analysis (2020-2030)
3.1.1. Market Drivers Increasing Cloud Adoption Increasing awareness of IoT devices.
3.1.2. Market Challenges Data security concerns Lack of skilled professionals
3.1.3. Market Opportunities Technological advancements in analytics as a service Increasing demand for customized AaaS solutions
Chapter 4. Global Analytics as a Service 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 Analytics as a Service Market, by Component
5.1. Market Snapshot
5.2. Global Analytics as a Service Market by Component , Performance – Potential Analysis
5.3. Global Analytics as a Service Market Estimates & Forecasts by Component 2020-2030 (USD Billion)
5.4. Analytics as a Service Market, Sub Segment Analysis
5.4.1. Solutions
5.4.2. Services
Chapter 6. Global Analytics as a Service Market, by Analytics Type
6.1. Market Snapshot
6.2. Global Analytics as a Service Market by Analytics Type , Performance – Potential Analysis
6.3. Global Analytics as a Service Market Estimates & Forecasts by Analytics Type 2020-2030 (USD Billion)
6.4. Analytics as a Service Market, Sub Segment Analysis
6.4.1. Predictive Analytics
6.4.2. Prescriptive Analytics
6.4.3. Diagnostic Analytics
6.4.4. Descriptive Analytics
Chapter 7. Global Analytics as a Service Market, by Deployment Type
7.1. Market Snapshot
7.2. Global Analytics as a Service Market by Deployment Type , Performance – Potential Analysis
7.3. Global Analytics as a Service Market Estimates & Forecasts by Deployment Type 2020-2030 (USD Billion)
7.4. Analytics as a Service Market, Sub Segment Analysis
7.4.1. Private Cloud
7.4.2. Public Cloud
7.4.3. Hybrid Cloud
Chapter 8. Global Analytics as a Service Market, by Industry Vertical
8.1. Market Snapshot
8.2. Global Analytics as a Service Market by Industry Vertical , Performance – Potential Analysis
8.3. Global Analytics as a Service Market Estimates & Forecasts by Industry Vertical 2020-2030 (USD Billion)
8.4. Analytics as a Service Market, Sub Segment Analysis
8.4.1. BFSI
8.4.2. Retail
8.4.3. Government & Public Sector
8.4.4. IT & Telecommunication
8.4.5. Transportation & Logistics
8.4.6. Manufacturing
8.4.7. Others
Chapter 9. Global Analytics as a Service Market, Regional Analysis
9.1. Top Leading Countries
9.2. Top Emerging Countries
9.3. Analytics as a Service Market, Regional Market Snapshot
9.4. North America Analytics as a Service Market
9.4.1. U.S. Analytics as a Service Market Component breakdown estimates & forecasts, 2020-2030 Analytics Type breakdown estimates & forecasts, 2020-2030 Deployment Type breakdown estimates & forecasts, 2020-2030 Industry Vertical breakdown estimates & forecasts, 2020-2030
9.4.2. Canada Analytics as a Service Market
9.5. Europe Analytics as a Service Market Snapshot
9.5.1. U.K. Analytics as a Service Market
9.5.2. Germany Analytics as a Service Market
9.5.3. France Analytics as a Service Market
9.5.4. Spain Analytics as a Service Market
9.5.5. Italy Analytics as a Service Market
9.5.6. Rest of Europe Analytics as a Service Market
9.6. Asia-Pacific Analytics as a Service Market Snapshot
9.6.1. China Analytics as a Service Market
9.6.2. India Analytics as a Service Market
9.6.3. Japan Analytics as a Service Market
9.6.4. Australia Analytics as a Service Market
9.6.5. South Korea Analytics as a Service Market
9.6.6. Rest of Asia Pacific Analytics as a Service Market
9.7. Latin America Analytics as a Service Market Snapshot
9.7.1. Brazil Analytics as a Service Market
9.7.2. Mexico Analytics as a Service Market
9.8. Middle East & Africa Analytics as a Service Market
9.8.1. Saudi Arabia Analytics as a Service Market
9.8.2. South Africa Analytics as a Service Market
9.8.3. Rest of Middle East & Africa Analytics as a Service 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. Microsoft Corporation Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
10.3.2. Oracle Corporation
10.3.3. SAP societas Europaea
10.3.4. Hewlett Packard Enterprise Development LP
10.3.5. TIBCO Software Inc.
10.3.6. Amazon Web Services, Inc.
10.3.7. GoodData Corporation
10.3.8. SAS Institute Inc.
10.3.9. International Business Machines Corporation
10.3.10. Google LLC
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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