The Big Data as a Service (BDaaS) Market size was valued at USD 21.1 Bn in 2022 and is expected to reach USD 152.80 Bn by 2030 and grow at a CAGR of 28.08 % over the forecast period 2023-2030.
Big data as a service is defined as the distribution of statistical analysis information from a third party or service provider to an enterprise to assist it in grasping the insights and gaining a competitive edge. Big data as a service is frequently provided in a variety of forms, such as big data analytics software as a service or as a data fabric that incorporates data management and data aggregation. It may also be provided as a data platform service, which primarily focuses on analytical programming, as well as cloud infrastructure.
Big data as a service is the providing of statistical analysis information or tools by a third party. Big data as a service might take the shape of software or a contract for a data analysis team. Big data as a service is performed to assist enterprises in better comprehending and acquiring a better knowledge of the insights that may be gleaned from massive volumes of data to acquire a competitive advantage over rival firms.
The Big Data as a Service (BDaaS) market is poised for remarkable growth, driven by the exponential rise in connected devices worldwide. Industries spanning government, media & entertainment, retail, BFSI, and manufacturing are eagerly embracing connected devices to revolutionize their business operations and manufacturing units. Moreover, the market's expansion is further propelled by the soaring demand for real-time data analytics, which has become a crucial driver of success in today's dynamic business landscape.
KEY DRIVERS:
The increasing number of e-commerce platforms, With the rise of online shopping Drives The Market.
Data growth as a result of digitization and automation.
The main factors driving this growth is the increasing number of e-commerce platforms. With the rise of online shopping, more and more businesses are setting up their own ecommerce websites to reach a wider customer base. This has led to a surge in the amount of data being generated and collected by these platforms.
Industries such as government, media & entertainment, retail, BFSI, and manufacturing are also embracing connected devices as part of their operations. These devices, which are part of the internet of things (IoT) ecosystem, generate a vast amount of data. This data is then used for various analytical purposes, such as data/text mining, complex event processing, multivariate statistics, and neural networks.
RESTRAINTS:
The Difficulty of Extracting Valuable Insights from Massive Data Sources.
The Lack of Skilled Professionals and Rising Security Breaches are Impede Market Growth
Despite the numerous benefits offered by BDaaS, including end-to-end solutions, enhanced storage services, and traceability, there are several challenges that hinder its widespread adoption. The primary obstacles in the market include security breaches, deployment and operability issues, and a shortage of skilled professionals. Additionally, the recruitment and retention of qualified experts to develop advanced BDaaS solutions further hamper market growth. Organizations require experienced professionals in the relevant field to design, develop, and operate BDaaS applications effectively. However, due to the scarcity of such professionals, only 14% of organizations have successfully deployed BDaaS, while the majority still rely on pilot projects. Consequently, the demand and compensation for skilled professionals in the market have surged.
OPPORTUNITY:
BdaaS Solutions to Improve Return on Investment and Decision-Making Capabilities.
Growing Advancement of Cloud AI, Machine Learning, IoT, and Advanced Analytics to Increase Opportunities for BdaaS Vendors.
CHALLENGES:
Concerns about security and privacy.
Inadequate Knowledge of BdaaS Solutions and Professional Expertise.
Geopolitical tension or conflict in the region could disrupt the flow of services, data centers, or cloud infrastructures located in these countries. This could lead to concerns about data security and business continuity for companies using BDaaS solutions based in these regions. BDaaS providers might face challenges in sourcing hardware components or maintaining their services due to disruptions in supply chains caused by the conflict. This could impact the availability and reliability of BDaaS offerings, affecting the market's growth and stability. Heightened tensions might lead to increased scrutiny or changes in data privacy laws and regulations. Companies utilizing BDaaS might face new compliance requirements or stricter regulations, impacting their operations and potentially increasing costs. Geopolitical conflicts often create market uncertainties. Businesses may become hesitant to invest in BDaaS solutions, leading to a slowdown in market growth or adoption until the situation stabilizes. Due to the conflict, companies might prefer to work with BDaaS providers located in regions perceived as more stable or neutral. This could lead to a shift in market dynamics, benefiting providers from different geographical areas. During times of conflict, there is a heightened risk of cyberattacks or data breaches. BDaaS providers may need to invest more in cybersecurity measures to reassure their clients, which could impact their operational costs and pricing models.
Impact of Economic Downturn:
Challenges:
Companies might reduce spending on non-essential services, impacting the adoption of BDaaS due to budgetary constraints. Organizations may postpone or scale back their investments in new technologies like BDaaS during uncertain economic times. Businesses might delay or slow down their plans to adopt BDaaS due to the need to focus on immediate cost-cutting measures. Enterprises may become more risk-averse, leading to longer decision-making cycles for adopting new services like BDaaS.
Opportunities:
BDaaS can be seen as a cost-effective solution compared to maintaining in-house big data infrastructure, encouraging its adoption during economic downturns as companies seek cost savings. Organizations aiming to optimize their operations might turn to BDaaS to improve data analysis, decision-making, and resource utilization, ultimately improving efficiency and reducing costs. Even during downturns, the need for data-driven insights remains crucial. Companies may turn to BDaaS to derive valuable insights that could help them navigate challenging times and make informed strategic decisions. BDaaS providers might offer flexible pricing or subscription models, making it more appealing to companies trying to manage costs during an economic downturn.
By Deployment
Public Cloud
Private Cloud
Hybrid Cloud
The public cloud is projected to dominate the market during the forecast period. The BDaaS market has been divided into three deployment types: public cloud, hybrid cloud, and private cloud. BDaaS solutions provide organizations with the ability to reduce costs associated with IT infrastructure, software, storage, and technical staff. These solutions can be implemented on the public, private, or hybrid cloud, depending on the specific needs of the client. The public cloud is expected to have the largest market share due to its cost-effective nature. The private cloud allows organizations to maintain complete control over their systems and data, ensuring enhanced security. On the other hand, the hybrid cloud allows organizations to take advantage of both the cost-efficiency of the public cloud and the enhanced security of the private cloud.
By Component
Solution
Services
By Enterprise Size
Small and Medium-sized business
Large enterprise
During the forecast period, it is expected that large enterprises will dominate the market share. In today's highly competitive business landscape, large enterprises are determined to capture a larger market share and therefore, they are embracing BDaaS solutions at a high rate. These organizations typically have data spread across various departments, and to extract valuable insights from this scattered data, they are turning to on-demand services that leverage cloud-based analysis of big data. By utilizing cloud-based analytics, large enterprises are able to combine their internal and external information, enabling them to gain valuable insights. This approach provides faster access to data, prompting these enterprises to invest significantly in becoming technologically proficient. As a result, the adoption of BDaaS solutions is higher among large enterprises compared to Small and Medium-sized Enterprises (SMEs). Additionally, large enterprises allocate a significant amount of resources towards training workshops and education to ensure their employees can effectively leverage the benefits of BDaaS solutions. The Small and Medium-sized Enterprises (SMEs) are growing with the highest CAGR.
By End-Use
BFSI
Manufacturing
Retail
Media & Entertainment
Healthcare
IT & Telecommunication
Government
Others
The North American market held a significant revenue share of nearly 34.0% due to the rapid growth of e-commerce and the increasing government funding for big data projects in the United States. Additionally, the adoption of Big Data as a Service is on the rise in various sectors such as discrete manufacturing, professional services, banking, and federal/central government, further contributing to the market's growth. It is expected that the United States will dominate the North American market, as many major vendors operating in this market are based in the U.S.
APAC region is also expected to experience substantial growth during the projected period. This growth can be attributed to the increasing number of smartphone and internet users, which in turn generates a significant amount of big data. Countries like China, India, Japan, South Korea, and others are expected to contribute to this growth by supporting the market. the increasing number of retailers and emerging small and medium-sized enterprises (SMEs) that are adopting big data services based on the public cloud. Moreover, domestic players offering big data as a service (BDaaS) are actively pursuing mergers, acquisitions, and partnerships to launch various big data projects. For example, SMEs in India and Bangladesh have partnered with National Research Systems (NRS) to launch the Big Data2 CSA project in Southeast Asia.
In the Middle East and Africa, the adoption of 5G infrastructure and the growing penetration of smartphones will contribute to the rising demand for BDaaS. Similarly, the Latin American market is expected to experience significant growth due to increasing internet penetration. Furthermore, the market will be driven by the growing investment in the IT and telecom industry, the rise in regional startups, and the presence of local providers.
REGIONAL COVERAGE:
North America
US
Canada
Mexico
Europe
Eastern Europe
Poland
Romania
Hungary
Turkey
Rest of Eastern Europe
Western Europe
Germany
France
UK
Italy
Spain
Netherlands
Switzerland
Austria
Rest of Western Europe
Asia Pacific
China
India
Japan
South Korea
Vietnam
Singapore
Australia
Rest of Asia Pacific
Middle East & Africa
Middle East
UAE
Egypt
Saudi Arabia
Qatar
Rest of the Middle East
Africa
Nigeria
South Africa
Rest of Africa
Latin America
Brazil
Argentina
Colombia
Rest of Latin America
The major key players are Accenture, Amazon Web Services, inc., Google LLC, Hewlett Packard Enterprise Development lp, International Business Machines Corporation, Microsoft Corporation, Oracle Corporation, SAP SE, SAS Institute Inc., GoodData, Hitachi Vantara, Teradata & Other Players and other key players mentioned in the final report.
In November 2022, Amazon Web Services, Inc. (AWS) unveiled five groundbreaking features in its database and analytics portfolios. These cutting-edge updates empower users to efficiently and swiftly manage and analyze data on a petabyte scale, revolutionizing the way customers operate high-performance database and analytics workloads at scale.
In October 2022, Oracle made a significant stride with the introduction of the Oracle Network Analytics Suite. This groundbreaking suite encompasses a state-of-the-art collection of cloud-native analytics tools. By merging network function data with the power of machine learning and artificial intelligence, operators can now make automated and well-informed decisions regarding the performance and stability of their entire 5G network core.
Wipro Ltd. also made waves in November 2022 with the launch of the Wipro Data Intelligence Suite. This comprehensive suite serves as a one-stop destination for accelerating cloud modernization and data monetization. Specifically designed to enhance data estates, including data stores, pipelines, and visualizations, that operate on Amazon Web Services (AWS), this suite is a game-changer in the industry.
In February 2023, Microsoft announced its plans to establish a new region for its cloud data centers in the Kingdom of Saudi Arabia (KSA). This strategic move by the tech giant is a direct response to the growing demand from global enterprises, local businesses, and public sector institutions in Saudi Arabia for cloud services and data residency. By investing in the country's infrastructure, Microsoft aims to cater to the increasing needs of its customers and further solidify its presence in the region.
| Report Attributes | Details |
| Market Size in 2022 | US$ 21.1 Bn |
| Market Size by 2030 | US$ 152.80 Bn |
| CAGR | CAGR of 28.08% From 2023 to 2030 |
| Base Year | 2022 |
| Forecast Period | 2023-2030 |
| Historical Data | 2020-2021 |
| Report Scope & Coverage | Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
| Key Segments | • By Deployment (Public Cloud, Private Cloud, And Hybrid Cloud) • By Component {Solution (Hadoop-As-A-Service, Data-As-A-Service, And Data Analytics-As-A-Service), Services}, • By Enterprise Size (Small and Medium-Sized Business, And Large Enterprises) • By End-Use (BFSI, Manufacturing, Retail, Media & Entertainment, Healthcare, IT & Telecommunication, Government, And Others) |
| Regional Analysis/Coverage | North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe] Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]), Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia Rest of Latin America) |
| Company Profiles | Accenture, Amazon Web Services, inc., Google LLC, Hewlett Packard Enterprise Development lp, International Business Machines Corporation, Microsoft Corporation, Oracle Corporation, SAP SE, SAS Institute Inc., GoodData, Hitachi Vantara, Teradata |
| Key Drivers | • The increasing number of e-commerce platforms, With the rise of online shopping Drives The Market. • Data growth as a result of digitization and automation. |
| Market Opportunities | • BdaaS Solutions to Improve Return on Investment and Decision-Making Capabilities. • Growing Advancement of Cloud AI, Machine Learning, IoT, and Advanced Analytics to Increase Opportunities for BdaaS Vendors. |
Ans. The projected market size for the Big Data as A Service (BDaaS) Market is USD 152.80 million by 2030.
Ans. The Compound Annual Growth rate for the Big Data as A Service (BDaaS) Market over the forecast period is 28.08%.
Ans: The Public Cloud Deployment segment dominated the Big Data as A Service (BDaaS) Market with the highest revenue share of about 45% in 2022.
Ans: - The major key players are Accenture, Amazon Web Services, inc., Google LLC, Hewlett Packard Enterprise Development lp, International Business Machines Corporation, Microsoft Corporation, Oracle Corporation, SAP SE, SAS Institute Inc., GoodData, Hitachi Vantara, Teradata & Other Players and other key players mentioned in the final report.
Ans: - The study includes a comprehensive analysis of Big Data as a Service (BDaaS)Market trends, as well as present and future market forecasts. DROC analysis, as well as impact analysis for the projected period. Porter's five forces analysis aids in the study of buyer and supplier potential as well as the competitive landscape etc.
TABLE OF CONTENTS
1. Introduction
1.1 Market Definition
1.2 Scope
1.3 Research Assumptions
2. Research Methodology
3. Market Dynamics
3.1 Drivers
3.2 Restraints
3.3 Opportunities
3.4 Challenges
4. Impact Analysis
4.1 Impact of Russia-Ukraine War
4.2 Impact of Economic Slowdown
4.2.1 Introduction
4.2.2 Impact on major economies
4.2.2.1 US
4.2.2.2 Canada
4.2.2.3 Germany
4.2.2.4 France
4.2.2.5 United Kingdom
4.2.2.6 China
4.2.2.7 Japan
4.2.2.8 South Korea
4.2.2.9 India
5. Value Chain Analysis
6. Porter’s 5 forces model
7. PEST Analysis
8. Big Data as A Service (BDaaS) Market Segmentation, By Deployment
8.1 Introduction
8.2 Trend Analysis
8.3 Public Cloud
8.4 Private Cloud
8.5 Hybrid Cloud
9. Big Data as A Service (BDaaS) Market Segmentation, By Component
9.1 Introduction
9.2 Trend Analysis
9.3 Solution
9.3.1 Hadoop-as-a-Service
9.3.2 Data-as-a-Service
9.3.3 Data Analytics-as-a-Service
9.4 Services
10. Big Data as A Service (BDaaS) Market Segmentation, By Enterprise Size
10.1 Introduction
10.2 Trend Analysis
10.3 Small and Medium-sized business
10.4 Large enterprise
11. Big Data as A Service (BDaaS) Market Segmentation, By End-Use
11.1 Introduction
11.2 Trend Analysis
11.3 BFSI
11.4 Manufacturing
11.5 Retail
11.6 Media & Entertainment
11.7 Healthcare
11.8 IT & Telecommunication
11.9 Government
11.10 Others
12. Regional Analysis
12.1 Introduction
12.2 North America
12.2.1 Trend Analysis
12.2.2 North America Big Data as A Service (BDaaS) Market By Country
12.2.3 North America Big Data as A Service (BDaaS) Market By Deployment
12.2.4 North America Big Data as A Service (BDaaS) Market By Component
12.2.5 North America Big Data as A Service (BDaaS) Market By Enterprise Size
12.2.6 North America Big Data as A Service (BDaaS) Market, By End-Use
12.2.7 USA
12.2.7.1 USA Big Data as A Service (BDaaS) Market By Deployment
12.2.7.2 USA Big Data as A Service (BDaaS) Market By Component
12.2.7.3 USA Big Data as A Service (BDaaS) Market By Enterprise Size
12.2.7.4 USA Big Data as A Service (BDaaS) Market, By End-Use
12.2.8 Canada
12.2.8.1 Canada Big Data as A Service (BDaaS) Market By Deployment
12.2.8.2 Canada Big Data as A Service (BDaaS) Market By Component
12.2.8.3 Canada Big Data as A Service (BDaaS) Market By Enterprise Size
12.2.8.4 Canada Big Data as A Service (BDaaS) Market, By End-Use
12.2.9 Mexico
12.2.9.1 Mexico Big Data as A Service (BDaaS) Market By Deployment
12.2.9.2 Mexico Big Data as A Service (BDaaS) Market By Component
12.2.9.3 Mexico Big Data as A Service (BDaaS) Market By Enterprise Size
12.2.9.4 Mexico Big Data as A Service (BDaaS) Market, By End-Use
12.3 Europe
12.3.1 Trend Analysis
12.3.2 Eastern Europe
12.3.2.1 Eastern Europe Big Data as A Service (BDaaS) Market By Country
12.3.2.2 Eastern Europe Big Data as A Service (BDaaS) Market By Deployment
12.3.2.3 Eastern Europe Big Data as A Service (BDaaS) Market By Component
12.3.2.4 Eastern Europe Big Data as A Service (BDaaS) Market By Enterprise Size
12.3.2.5 Eastern Europe Big Data as A Service (BDaaS) Market By End-Use
12.3.2.6 Poland
12.3.2.6.1 Poland Big Data as A Service (BDaaS) Market By Deployment
12.3.2.6.2 Poland Big Data as A Service (BDaaS) Market By Component
12.3.2.6.3 Poland Big Data as A Service (BDaaS) Market By Enterprise Size
12.3.2.6.4 Poland Big Data as A Service (BDaaS) Market By End-Use
12.3.2.7 Romania
12.3.2.7.1 Romania Big Data as A Service (BDaaS) Market By Deployment
12.3.2.7.2 Romania Big Data as A Service (BDaaS) Market By Component
12.3.2.7.3 Romania Big Data as A Service (BDaaS) Market By Enterprise Size
12.3.2.7.4 Romania Big Data as A Service (BDaaS) Market By End-Use
12.3.2.8 Hungary
12.3.2.8.1 Hungary Big Data as A Service (BDaaS) Market By Deployment
12.3.2.8.2 Hungary Big Data as A Service (BDaaS) Market By Component
12.3.2.8.3 Hungary Big Data as A Service (BDaaS) Market By Enterprise Size
12.3.2.8.4 Hungary Big Data as A Service (BDaaS) Market By End-Use
12.3.2.9 Turkey
12.3.2.9.1 Turkey Big Data as A Service (BDaaS) Market By Deployment
12.3.2.9.2 Turkey Big Data as A Service (BDaaS) Market By Component
12.3.2.9.3 Turkey Big Data as A Service (BDaaS) Market By Enterprise Size
12.3.2.9.4 Turkey Big Data as A Service (BDaaS) Market By End-Use
12.3.2.10 Rest of Eastern Europe
12.3.2.10.1 Rest of Eastern Europe Big Data as A Service (BDaaS) Market By Deployment
12.3.2.10.2 Rest of Eastern Europe Big Data as A Service (BDaaS) Market By Component
12.3.2.10.3 Rest of Eastern Europe Big Data as A Service (BDaaS) Market By Enterprise Size
12.3.2.10.4 Rest of Eastern Europe Big Data as A Service (BDaaS) Market By End-Use
12.3.3 Western Europe
12.3.3.1 Western Europe Big Data as A Service (BDaaS) Market By Country
12.3.3.2 Western Europe Big Data as A Service (BDaaS) Market By Deployment
12.3.3.3 Western Europe Big Data as A Service (BDaaS) Market By Component
12.3.3.4 Western Europe Big Data as A Service (BDaaS) Market By Enterprise Size
12.3.3.5 Western Europe Big Data as A Service (BDaaS) Market By End-Use
12.3.3.6 Germany
12.3.3.6.1 Germany Big Data as A Service (BDaaS) Market By Deployment
12.3.3.6.2 Germany Big Data as A Service (BDaaS) Market By Component
12.3.3.6.3 Germany Big Data as A Service (BDaaS) Market By Enterprise Size
12.3.3.6.4 Germany Big Data as A Service (BDaaS) Market By End-Use
12.3.3.7 France
12.3.3.7.1 France Big Data as A Service (BDaaS) Market By Deployment
12.3.3.7.2 France Big Data as A Service (BDaaS) Market By Component
12.3.3.7.3 France Big Data as A Service (BDaaS) Market By Enterprise Size
12.3.3.7.4 France Big Data as A Service (BDaaS) Market By End-Use
12.3.3.8 UK
12.3.3.8.1 UK Big Data as A Service (BDaaS) Market By Deployment
12.3.3.8.2 UK Big Data as A Service (BDaaS) Market By Component
12.3.3.8.3 UK Big Data as A Service (BDaaS) Market By Enterprise Size
12.3.3.8.4 UK Big Data as A Service (BDaaS) Market By End-Use
12.3.3.9 Italy
12.3.3.9.1 Italy Big Data as A Service (BDaaS) Market By Deployment
12.3.3.9.2 Italy Big Data as A Service (BDaaS) Market By Component
12.3.3.9.3 Italy Big Data as A Service (BDaaS) Market By Enterprise Size
12.3.3.9.4 Italy Big Data as A Service (BDaaS) Market By End-Use
12.3.3.10 Spain
12.3.3.10.1 Spain Big Data as A Service (BDaaS) Market By Deployment
12.3.3.10.2 Spain Big Data as A Service (BDaaS) Market By Component
12.3.3.10.3 Spain Big Data as A Service (BDaaS) Market By Enterprise Size
12.3.3.10.4 Spain Big Data as A Service (BDaaS) Market By End-Use
12.3.3.11 Netherlands
12.3.3.11.1 Netherlands Big Data as A Service (BDaaS) Market By Deployment
12.3.3.11.2 Netherlands Big Data as A Service (BDaaS) Market By Component
12.3.3.11.3 Netherlands Big Data as A Service (BDaaS) Market By Enterprise Size
12.3.3.11.4 Netherlands Big Data as A Service (BDaaS) Market By End-Use
12.3.3.12 Switzerland
12.3.3.12.1 Switzerland Big Data as A Service (BDaaS) Market By Deployment
12.3.3.12.2 Switzerland Big Data as A Service (BDaaS) Market By Component
12.3.3.12.3 Switzerland Big Data as A Service (BDaaS) Market By Enterprise Size
12.3.3.12.4 Switzerland Big Data as A Service (BDaaS) Market By End-Use
12.3.3.13 Austria
12.3.3.13.1 Austria Big Data as A Service (BDaaS) Market By Deployment
12.3.3.13.2 Austria Big Data as A Service (BDaaS) Market By Component
12.3.3.13.3 Austria Big Data as A Service (BDaaS) Market By Enterprise Size
12.3.3.13.4 Austria Big Data as A Service (BDaaS) Market By End-Use
12.3.3.14 Rest of Western Europe
12.3.3.14.1 Rest of Western Europe Big Data as A Service (BDaaS) Market By Deployment
12.3.3.14.2 Rest of Western Europe Big Data as A Service (BDaaS) Market By Component
12.3.3.14.3 Rest of Western Europe Big Data as A Service (BDaaS) Market By Enterprise Size
12.3.3.14.4 Rest of Western Europe Big Data as A Service (BDaaS) Market By End-Use
12.4 Asia-Pacific
12.4.1 Trend Analysis
12.4.2 Asia-Pacific Big Data as A Service (BDaaS) Market By Country
12.4.3 Asia-Pacific Big Data as A Service (BDaaS) Market By Deployment
12.4.4 Asia-Pacific Big Data as A Service (BDaaS) Market By Component
12.4.5 Asia-Pacific Big Data as A Service (BDaaS) Market By Enterprise Size
12.4.6 Asia-Pacific Big Data as A Service (BDaaS) Market By End-Use
12.4.7 China
12.4.7.1 China Big Data as A Service (BDaaS) Market By Deployment
12.4.7.2 China Big Data as A Service (BDaaS) Market By Component
12.4.7.3 China Big Data as A Service (BDaaS) Market By Enterprise Size
12.4.7.4 China Big Data as A Service (BDaaS) Market By End-Use
12.4.8 India
12.4.8.1 India Big Data as A Service (BDaaS) Market By Deployment
12.4.8.2 India Big Data as A Service (BDaaS) Market By Component
12.4.8.3 India Big Data as A Service (BDaaS) Market By Enterprise Size
12.4.8.4 India Big Data as A Service (BDaaS) Market By End-Use
12.4.9 Japan
12.4.9.1 Japan Big Data as A Service (BDaaS) Market By Deployment
12.4.9.2 Japan Big Data as A Service (BDaaS) Market By Component
12.4.9.3 Japan Big Data as A Service (BDaaS) Market By Enterprise Size
12.4.9.4 Japan Big Data as A Service (BDaaS) Market By End-Use
12.4.10 South Korea
12.4.10.1 South Korea Big Data as A Service (BDaaS) Market By Deployment
12.4.10.2 South Korea Big Data as A Service (BDaaS) Market By Component
12.4.10.3 South Korea Big Data as A Service (BDaaS) Market By Enterprise Size
12.4.10.4 South Korea Big Data as A Service (BDaaS) Market By End-Use
12.4.11 Vietnam
12.4.11.1 Vietnam Big Data as A Service (BDaaS) Market By Deployment
12.4.11.2 Vietnam Big Data as A Service (BDaaS) Market By Component
12.4.11.3 Vietnam Big Data as A Service (BDaaS) Market By Enterprise Size
12.4.11.4 Vietnam Big Data as A Service (BDaaS) Market By End-Use
12.4.12 Singapore
12.4.12.1 Singapore Big Data as A Service (BDaaS) Market By Deployment
12.4.12.2 Singapore Big Data as A Service (BDaaS) Market By Component
12.4.12.3 Singapore Big Data as A Service (BDaaS) Market By Enterprise Size
12.4.12.4 Singapore Big Data as A Service (BDaaS) Market By End-Use
12.4.13 Australia
12.4.13.1 Australia Big Data as A Service (BDaaS) Market By Deployment
12.4.13.2 Australia Big Data as A Service (BDaaS) Market By Component
12.4.13.3 Australia Big Data as A Service (BDaaS) Market By Enterprise Size
12.4.13.4 Australia Big Data as A Service (BDaaS) Market By End-Use
12.4.14 Rest of Asia-Pacific
12.4.14.1 Rest of Asia-Pacific Big Data as A Service (BDaaS) Market By Deployment
12.4.14.2 Rest of Asia-Pacific Big Data as A Service (BDaaS) Market By Component
12.4.14.3 Rest of Asia-Pacific Big Data as A Service (BDaaS) Market By Enterprise Size
12.4.14.4 Rest of Asia-Pacific Big Data as A Service (BDaaS) Market By End-Use
12.5 Middle East & Africa
12.5.1 Trend Analysis
12.5.2 Middle East
12.5.2.1 Middle East Big Data as A Service (BDaaS) Market By Country
12.5.2.2 Middle East Big Data as A Service (BDaaS) Market By Deployment
12.5.2.3 Middle East Big Data as A Service (BDaaS) Market By Component
12.5.2.4 Middle East Big Data as A Service (BDaaS) Market By Enterprise Size
12.5.2.5 Middle East Big Data as A Service (BDaaS) Market By End-Use
12.5.2.6 UAE
12.5.2.6.1 UAE Big Data as A Service (BDaaS) Market By Deployment
12.5.2.6.2 UAE Big Data as A Service (BDaaS) Market By Component
12.5.2.6.3 UAE Big Data as A Service (BDaaS) Market By Enterprise Size
12.5.2.6.4 UAE Big Data as A Service (BDaaS) Market By End-Use
12.5.2.7 Egypt
12.5.2.7.1 Egypt Big Data as A Service (BDaaS) Market By Deployment
12.5.2.7.2 Egypt Big Data as A Service (BDaaS) Market By Component
12.5.2.7.3 Egypt Big Data as A Service (BDaaS) Market By Enterprise Size
12.5.2.7.4 Egypt Big Data as A Service (BDaaS) Market By End-Use
12.5.2.8 Saudi Arabia
12.5.2.8.1 Saudi Arabia Big Data as A Service (BDaaS) Market By Deployment
12.5.2.8.2 Saudi Arabia Big Data as A Service (BDaaS) Market By Component
12.5.2.8.3 Saudi Arabia Big Data as A Service (BDaaS) Market By Enterprise Size
12.5.2.8.4 Saudi Arabia Big Data as A Service (BDaaS) Market By End-Use
12.5.2.9 Qatar
12.5.2.9.1 Qatar Big Data as A Service (BDaaS) Market By Deployment
12.5.2.9.2 Qatar Big Data as A Service (BDaaS) Market By Component
12.5.2.9.3 Qatar Big Data as A Service (BDaaS) Market By Enterprise Size
12.5.2.9.4 Qatar Big Data as A Service (BDaaS) Market By End-Use
12.5.2.10 Rest of Middle East
12.5.2.10.1 Rest of Middle East Big Data as A Service (BDaaS) Market By Deployment
12.5.2.10.2 Rest of Middle East Big Data as A Service (BDaaS) Market By Component
12.5.2.10.3 Rest of Middle East Big Data as A Service (BDaaS) Market By Enterprise Size
12.5.2.10.4 Rest of Middle East Big Data as A Service (BDaaS) Market By End-Use
12.5.3 Africa
12.5.3.1 Africa Big Data as A Service (BDaaS) Market By Country
12.5.3.2 Africa Big Data as A Service (BDaaS) Market By Deployment
12.5.3.3 Africa Big Data as A Service (BDaaS) Market By Component
12.5.3.4 Africa Big Data as A Service (BDaaS) Market By Enterprise Size
12.5.3.5 Africa Big Data as A Service (BDaaS) Market By End-Use
12.5.3.6 Nigeria
12.5.3.6.1 Nigeria Big Data as A Service (BDaaS) Market By Deployment
12.5.3.6.2 Nigeria Big Data as A Service (BDaaS) Market By Component
12.5.3.6.3 Nigeria Big Data as A Service (BDaaS) Market By Enterprise Size
12.5.3.6.4 Nigeria Big Data as A Service (BDaaS) Market By End-Use
12.5.3.7 South Africa
12.5.3.7.1 South Africa Big Data as A Service (BDaaS) Market By Deployment
12.5.3.7.2 South Africa Big Data as A Service (BDaaS) Market By Component
12.5.3.7.3 South Africa Big Data as A Service (BDaaS) Market By Enterprise Size
12.5.3.7.4 South Africa Big Data as A Service (BDaaS) Market By End-Use
12.5.3.8 Rest of Africa
12.5.3.8.1 Rest of Africa Big Data as A Service (BDaaS) Market By Deployment
12.5.3.8.2 Rest of Africa Big Data as A Service (BDaaS) Market By Component
12.5.3.8.3 Rest of Africa Big Data as A Service (BDaaS) Market By Enterprise Size
12.5.3.8.4 Rest of Africa Big Data as A Service (BDaaS) Market By End-Use
12.6 Latin America
12.6.1 Trend Analysis
12.6.2 Latin America Big Data as A Service (BDaaS) Market By Country
12.6.3 Latin America Big Data as A Service (BDaaS) Market By Deployment
12.6.4 Latin America Big Data as A Service (BDaaS) Market By Component
12.6.5 Latin America Big Data as A Service (BDaaS) Market By Enterprise Size
12.6.6 Latin America Big Data as A Service (BDaaS) Market By End-Use
12.6.7 Brazil
12.6.7.1 Brazil Big Data as A Service (BDaaS) Market By Deployment
12.6.7.2 Brazil Big Data as A Service (BDaaS) Market By Component
12.6.7.3 Brazil Big Data as A Service (BDaaS) Market By Enterprise Size
12.6.7.4 Brazil Big Data as A Service (BDaaS) Market By End-Use
12.6.8 Argentina
12.6.8.1 Argentina Big Data as A Service (BDaaS) Market By Deployment
12.6.8.2 Argentina Big Data as A Service (BDaaS) Market By Component
12.6.8.3 Argentina Big Data as A Service (BDaaS) Market By Enterprise Size
12.6.8.4 Argentina Big Data as A Service (BDaaS) Market By End-Use
12.6.9 Colombia
12.6.9.1 Colombia Big Data as A Service (BDaaS) Market By Deployment
12.6.9.2 Colombia Big Data as A Service (BDaaS) Market By Component
12.6.9.3 Colombia Big Data as A Service (BDaaS) Market By Enterprise Size
12.6.9.4 Colombia Big Data as A Service (BDaaS) Market By End-Use
12.6.10 Rest of Latin America
12.6.10.1 Rest of Latin America Big Data as A Service (BDaaS) Market By Deployment
12.6.10.2 Rest of Latin America Big Data as A Service (BDaaS) Market By Component
12.6.10.3 Rest of Latin America Big Data as A Service (BDaaS) Market By Enterprise Size
12.6.10.4 Rest of Latin America Big Data as A Service (BDaaS) Market By End-Use
13. Company Profiles
13.1 Accenture
13.1.1 Company Overview
13.1.2 Financial
13.1.3 Products/ Services Offered
13.1.4 SWOT Analysis
13.1.5 The SNS View
13.2 Amazon Web Services, inc.
13.2.1 Company Overview
13.2.2 Financial
13.2.3 Products/ Services Offered
13.2.4 SWOT Analysis
13.2.5 The SNS View
13.3 Google LLC.
13.3.1 Company Overview
13.3.2 Financial
13.3.3 Products/ Services Offered
13.3.4 SWOT Analysis
13.3.5 The SNS View
13.4 Hewlett Packard Enterprise Development lp
13.4.1 Company Overview
13.4.2 Financial
13.4.3 Products/ Services Offered
13.4.4 SWOT Analysis
13.4.5 The SNS View
13.5 International Business Machines Corporation
13.5.1 Company Overview
13.5.2 Financial
13.5.3 Products/ Services Offered
13.5.4 SWOT Analysis
13.5.5 The SNS View
13.6 Microsoft Corporation.
13.6.1 Company Overview
13.6.2 Financial
13.6.3 Products/ Services Offered
13.6.4 SWOT Analysis
13.6.5 The SNS View
13.7 Oracle Corporation.
13.7.1 Company Overview
13.7.2 Financial
13.7.3 Products/ Services Offered
13.7.4 SWOT Analysis
13.7.5 The SNS View
13.8 SAP SE.
13.8.1 Company Overview
13.8.2 Financial
13.8.3 Products/ Services Offered
13.8.4 SWOT Analysis
13.8.5 The SNS View
13.9 SAS Institute Inc.
13.9.1 Company Overview
13.9.2 Financial
13.9.3 Products/ Services Offered
13.9.4 SWOT Analysis
13.9.5 The SNS View
13.10 GoodData.
13.10.1 Company Overview
13.10.2 Financial
13.10.3 Products/ Services Offered
13.10.4 SWOT Analysis
13.10.5 The SNS View
14. Competitive Landscape
14.1 Competitive Benchmarking
14.2 Market Share Analysis
14.3 Recent Developments
14.3.1 Industry News
14.3.2 Company News
14.3.3 Mergers & Acquisitions
15. Use Case and Best Practices
16. Conclusion
An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.
Each report that we prepare takes a timeframe of 350-400 business hours for production. Starting from the selection of titles through a couple of in-depth brain storming session to the final QC process before uploading our titles on our website we dedicate around 350 working hours. The titles are selected based on their current market cap and the foreseen CAGR and growth.
The 5 steps process:
Step 1: Secondary Research:
Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.
Step 2: Primary Research
When we talk about primary research, it is a type of study in which the researchers collect relevant data samples directly, rather than relying on previously collected data. This type of research is focused on gaining content specific facts that can be sued to solve specific problems. Since the collected data is fresh and first hand therefore it makes the study more accurate and genuine.
We at SNS Insider have divided Primary Research into 2 parts.
Part 1 wherein we interview the KOLs of major players as well as the upcoming ones across various geographic regions. This allows us to have their view over the market scenario and acts as an important tool to come closer to the accurate market numbers. As many as 45 paid and unpaid primary interviews are taken from both the demand and supply side of the industry to make sure we land at an accurate judgement and analysis of the market.
This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.
Part 2: In this part of primary research the data collected via secondary research and the part 1 of the primary research is validated with the interviews from individual consultants and subject matter experts.
Consultants are those set of people who have at least 12 years of experience and expertise within the industry whereas Subject Matter Experts are those with at least 15 years of experience behind their back within the same space. The data with the help of two main processes i.e., FGDs (Focused Group Discussions) and IDs (Individual Discussions). This gives us a 3rd party nonbiased primary view of the market scenario making it a more dependable one while collation of the data pointers.
Step 3: Data Bank Validation
Once all the information is collected via primary and secondary sources, we run that information for data validation. At our intelligence centre our research heads track a lot of information related to the market which includes the quarterly reports, the daily stock prices, and other relevant information. Our data bank server gets updated every fortnight and that is how the information which we collected using our primary and secondary information is revalidated in real time.
Step 4: QA/QC Process
After all the data collection and validation our team does a final level of quality check and quality assurance to get rid of any unwanted or undesired mistakes. This might include but not limited to getting rid of the any typos, duplication of numbers or missing of any important information. The people involved in this process include technical content writers, research heads and graphics people. Once this process is completed the title gets uploader on our platform for our clients to read it.
Step 5: Final QC/QA Process:
This is the last process and comes when the client has ordered the study. In this process a final QA/QC is done before the study is emailed to the client. Since we believe in giving our clients a good experience of our research studies, therefore, to make sure that we do not lack at our end in any way humanly possible we do a final round of quality check and then dispatch the study to the client.
The Sensitive Data Discovery Market size was USD 6.8 billion in 2022 and is expected to Reach USD 23.0 billion by 2030 and grow at a CAGR of 16.5% over the forecast period of 2023-2030.
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