Data Analytics Market Size, Growth, Trends, Report 2023-2032
The global data analytics market was valued at USD 49.08 billion in 2022 and it is predicted to surpass around USD 524.44 billion by 2032 with a CAGR of 26.73% from 2023 to 2032. The data analytics market in the United States was accounted for USD 12 billion in 2022.
Key Pointers
Report Scope of the Data Analytics Market
| Report Coverage | Details |
| Revenue Share of North America in 2022 | 35% |
| CAGR of Asia Pacific from 2023 to 2032 | 34.25% |
| Revenue Forecast by 2032 | USD 524.44 billion |
| Growth Rate from 2023 to 2032 | CAGR of 26.73% |
| Base Year | 2022 |
| Forecast Period | 2023 to 2032 |
| Market Analysis (Terms Used) | Value (US$ Million/Billion) or (Volume/Units) |
| Companies Covered | Amazon Web Services Inc.; International Business Machines Corporation; Looker Data Sciences, Inc.; Mu Sigma, Oracle Corporation; SAP SE; Sisense Inc.; Tableau Software LLC.; Zoho Corporation Pvt. Ltd. |
The main factors propelling the data analytics market's expansion are the growing adoption of machine learning and artificial intelligence to offer increased acceptance of social networking platforms, individualized consumer experiences, and the rise of online shopping. For instance, in July 2022, IBM, a U.S.-based information technology company, acquired Databand.ai, a data observability platform in the U.S. This acquisition is intended to enhance IBM's software portfolio across AI, data, and automation to address the observability spectrum and help businesses ensure that reliable data is placed in the hands of the right users.
The rise of big data analytics, increasing cloud technology expenditures, and large amounts of data generated by virtual offices are all driving the expansion of the data analytics market. Enterprises can improve crucial business processes, goals, and activities by utilizing big data analytics. For instance, in April 2022, Accenture plc, an IT company in Ireland, acquired Ergo, a firm specializing in big data, analytics, and AI in Argentina. Through this acquisition, Accenture intends to devote more resources to help clients determine where to focus their transformation and how data can support better decision-making throughout the transformation process.
Increasing adoption of smart applications, emerging social media platforms, and the industrial revolution is expected to produce massive databases. Moreover, an enormous volume of data is generated from social media platforms, including Facebook, YouTube videos, Instagram, Snapchat, and others. Thus, rising databases across industries will fuel the data analytics market. Equipment used in agriculture, including smart machines, GPS-equipped tractors, and soil sensors, generate massive data sets. Moreover, data analytics is applied in agriculture to analyze huge data sets, including advanced risk assessment, natural trends, supply tracks, ideal crops, and more, which leads to market growth.
The need for connected devices is growing, accelerating the implementation of edge computing. Unlike clouds, edge computing solutions place processors closer to the data source or destination. Organizations achieve greater responsiveness and efficiency with data analytics operations at the edge. Edge computing is particularly applicable to the IoT due to its ability to process data in real-time and with a faster response time. For instance, in March 2023, Minima Global Ltd, a Europe-based blockchain platform developer, collaborated with Inferrix Limited, a software company in the U.K., by combining Minima's blockchain technology with Inferrix's IoT edge and AI offerings. This partnership aims to develop IoT solutions by ensuring efficient and secure sensor communication.
Type Insights
The predictive analytics segment dominates the market, with a revenue share of 33% in 2022. Predictive Analytics provides accurate and reliable insights, helping organizations to solve problems and identify opportunities, including detecting fraud, optimizing marketing campaigns, improving decision-making, and improving efficiency in operations. For instance, in June 2022, J.D. Power, U.S.-based data analytics and Artificial Intelligence Company acquired the predictive analytics business of We Predict, the UK-based company that offers hyper-vertically focused predictive analytics as a service. This acquisition is intended to provide a more comprehensive, detailed view of repair-related costs to anticipate financial risk exposure better.
With the increasing demand for client experience management, customer retention, and better lead management, the customer analytics segment is anticipated to enjoy a CAGR of 27.43%. Customer analytics is used in retail to create personalized communications and marketing campaigns. Customers' increasing demand for an omnichannel experience in the retail industry has fueled the segment's growth. Well-known companies such as Walmart and Amazon have successfully leveraged the benefits of various social media sites such as Facebook. The segment is expected to grow as more retail businesses focus on providing omnichannel services to their customers.
Solution Insights
The security intelligence segment dominates the market, with a revenue share of 36% in 2022. The growing adoption of advanced analytics to identify fraudulent activity, optimize processes, and address data risks drives the segment's growth. Increased deployment of business intelligence software to provide control access to customer databases, transaction security, and improved customer experience is also expected to drive segment growth over the forecast period. Security intelligence is becoming more popular because it employs a risk-reduction strategy that integrates internal and external threat, security, and business intelligence across an organization.
Data mining is used in diverse applications such as marketing, banking, healthcare, telecom industries, and other areas, leading to the segment's growth. Data mining benefits manufacturing and service companies because any significant amount of data is analyzed to help the business make strategic decisions to gain a competitive advantage. Many e-commerce sites use data mining to cross-sell and upsell their products. For instance, Amazon.com, Inc. uses text mining to find the product's lowest price. Moreover, Netflix, Inc. uses data mining insights to determine how to make a movie or series popular among customers.
Application Insights
The supply chain management segment dominates the market, with a revenue share of 31% in 2022. Data analytics in supply chain management help organizations increase profits through efficient production planning. The use of data analytics in supply chain management encourages the use of advanced technologies such as artificial intelligence and machine learning to uncover hidden patterns and gain valuable insights from available supply chain data. Manufacturing companies can use data analytics in sales and operations planning, capacity planning, business intelligence, and demand forecasting to optimize their supply chain processes, which propels the segment's growth.
The enterprise resource planning segment is expected to grow at the fastest CAGR during the forecast period. Data analytics applications can bridge data warehouses, traditional databases, and data lakes to incorporate Big Data with business application data to improve forecasting, analysis, and planning. Moreover, as organizations increasingly rely on data-driven decision-making, there is a greater need to access and analyze databases. The rapid advancements in hybrid cloud, artificial intelligence, IoT, and edge computing led to the exponential growth of big data, generating even more complexity for businesses to manage, resulting in the segment's growth.
Regional Insights
North America dominates the market with a revenue share of 35% in 2022. The region is home to prominent businesses from all industries, and the software is being widely implemented. For instance, Facebook, Twitter, and Instagram collect user information using data analytics about their preferences and send targeted advertisements. The availability of infrastructure that supports data analytics and the increased use of advanced technologies such as AI and machine learning are responsible for the market growth in North America. The U.S. is expected to experience rapid growth due to rising demand for analytics tools that provide advanced and enhanced compliance analytics, which are critical in uncovering policy, fraud violations, and other business misconduct.
Asia Pacific witnessed a significant CAGR of 34.25% during the forecast period due to the expansion of retail, BFSI, healthcare, automotive, and other industries. Moreover, the rising adoption of social media platforms, the internet, and smartphones, advancements in communication technologies, and digitalization are all expected to increase the market share of data analytics. Many Asian countries, including India, China, and Japan, are using the features of information-intensive AI and ML technologies in various industries, which leads to the growing use of data analytics. The growing adoption of big data analytics tools and solutions is also increasing market growth.
Data Analytics Market Segmentations:
By Type
By Solution
By Application
By Regional
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Type Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on Data Analytics Market
5.1. COVID-19 Landscape: Data Analytics Industry Impact
5.2. COVID 19 - Impact Assessment for the Industry
5.3. COVID 19 Impact: Global Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. Global Data Analytics Market, By Type
8.1. Data Analytics Market, by Type, 2023-2032
8.1.1 Prescriptive Analytics
8.1.1.1. Market Revenue and Forecast (2020-2032)
8.1.2. Predictive Analytics
8.1.2.1. Market Revenue and Forecast (2020-2032)
8.1.3. Customer Analytics
8.1.3.1. Market Revenue and Forecast (2020-2032)
8.1.4. Descriptive Analytics
8.1.4.1. Market Revenue and Forecast (2020-2032)
8.1.5. Others
8.1.5.1. Market Revenue and Forecast (2020-2032)
Chapter 9. Global Data Analytics Market, By Solution
9.1. Data Analytics Market, by Solution, 2023-2032
9.1.1. Security Intelligence
9.1.1.1. Market Revenue and Forecast (2020-2032)
9.1.2. Data Management
9.1.2.1. Market Revenue and Forecast (2020-2032)
9.1.3. Data Monitoring
9.1.3.1. Market Revenue and Forecast (2020-2032)
9.1.4. Data Mining
9.1.4.1. Market Revenue and Forecast (2020-2032)
Chapter 10. Global Data Analytics Market, By Application
10.1. Data Analytics Market, by Application, 2023-2032
10.1.1. Supply Chain Management
10.1.1.1. Market Revenue and Forecast (2020-2032)
10.1.2. Enterprise Resource Planning
10.1.2.1. Market Revenue and Forecast (2020-2032)
10.1.3. Database Management
10.1.3.1. Market Revenue and Forecast (2020-2032)
10.1.4. Human Resource Management
10.1.4.1. Market Revenue and Forecast (2020-2032)
10.1.5. Others
10.1.5.1. Market Revenue and Forecast (2020-2032)
Chapter 11. Global Data Analytics Market, Regional Estimates and Trend Forecast
11.1. North America
11.1.1. Market Revenue and Forecast, by Type (2020-2032)
11.1.2. Market Revenue and Forecast, by Solution (2020-2032)
11.1.3. Market Revenue and Forecast, by Application (2020-2032)
11.1.4. U.S.
11.1.4.1. Market Revenue and Forecast, by Type (2020-2032)
11.1.4.2. Market Revenue and Forecast, by Solution (2020-2032)
11.1.4.3. Market Revenue and Forecast, by Application (2020-2032)
11.1.5. Rest of North America
11.1.5.1. Market Revenue and Forecast, by Type (2020-2032)
11.1.5.2. Market Revenue and Forecast, by Solution (2020-2032)
11.1.5.3. Market Revenue and Forecast, by Application (2020-2032)
11.2. Europe
11.2.1. Market Revenue and Forecast, by Type (2020-2032)
11.2.2. Market Revenue and Forecast, by Solution (2020-2032)
11.2.3. Market Revenue and Forecast, by Application (2020-2032)
11.2.4. UK
11.2.4.1. Market Revenue and Forecast, by Type (2020-2032)
11.2.4.2. Market Revenue and Forecast, by Solution (2020-2032)
11.2.4.3. Market Revenue and Forecast, by Application (2020-2032)
11.2.5. Germany
11.2.5.1. Market Revenue and Forecast, by Type (2020-2032)
11.2.5.2. Market Revenue and Forecast, by Solution (2020-2032)
11.2.5.3. Market Revenue and Forecast, by Application (2020-2032)
11.2.6. France
11.2.6.1. Market Revenue and Forecast, by Type (2020-2032)
11.2.6.2. Market Revenue and Forecast, by Solution (2020-2032)
11.2.6.3. Market Revenue and Forecast, by Application (2020-2032)
11.2.7. Rest of Europe
11.2.7.1. Market Revenue and Forecast, by Type (2020-2032)
11.2.7.2. Market Revenue and Forecast, by Solution (2020-2032)
11.2.7.3. Market Revenue and Forecast, by Application (2020-2032)
11.3. APAC
11.3.1. Market Revenue and Forecast, by Type (2020-2032)
11.3.2. Market Revenue and Forecast, by Solution (2020-2032)
11.3.3. Market Revenue and Forecast, by Application (2020-2032)
11.3.4. India
11.3.4.1. Market Revenue and Forecast, by Type (2020-2032)
11.3.4.2. Market Revenue and Forecast, by Solution (2020-2032)
11.3.4.3. Market Revenue and Forecast, by Application (2020-2032)
11.3.5. China
11.3.5.1. Market Revenue and Forecast, by Type (2020-2032)
11.3.5.2. Market Revenue and Forecast, by Solution (2020-2032)
11.3.5.3. Market Revenue and Forecast, by Application (2020-2032)
11.3.6. Japan
11.3.6.1. Market Revenue and Forecast, by Type (2020-2032)
11.3.6.2. Market Revenue and Forecast, by Solution (2020-2032)
11.3.6.3. Market Revenue and Forecast, by Application (2020-2032)
11.3.7. Rest of APAC
11.3.7.1. Market Revenue and Forecast, by Type (2020-2032)
11.3.7.2. Market Revenue and Forecast, by Solution (2020-2032)
11.3.7.3. Market Revenue and Forecast, by Application (2020-2032)
11.4. MEA
11.4.1. Market Revenue and Forecast, by Type (2020-2032)
11.4.2. Market Revenue and Forecast, by Solution (2020-2032)
11.4.3. Market Revenue and Forecast, by Application (2020-2032)
11.4.4. GCC
11.4.4.1. Market Revenue and Forecast, by Type (2020-2032)
11.4.4.2. Market Revenue and Forecast, by Solution (2020-2032)
11.4.4.3. Market Revenue and Forecast, by Application (2020-2032)
11.4.5. North Africa
11.4.5.1. Market Revenue and Forecast, by Type (2020-2032)
11.4.5.2. Market Revenue and Forecast, by Solution (2020-2032)
11.4.5.3. Market Revenue and Forecast, by Application (2020-2032)
11.4.6. South Africa
11.4.6.1. Market Revenue and Forecast, by Type (2020-2032)
11.4.6.2. Market Revenue and Forecast, by Solution (2020-2032)
11.4.6.3. Market Revenue and Forecast, by Application (2020-2032)
11.4.7. Rest of MEA
11.4.7.1. Market Revenue and Forecast, by Type (2020-2032)
11.4.7.2. Market Revenue and Forecast, by Solution (2020-2032)
11.4.7.3. Market Revenue and Forecast, by Application (2020-2032)
11.5. Latin America
11.5.1. Market Revenue and Forecast, by Type (2020-2032)
11.5.2. Market Revenue and Forecast, by Solution (2020-2032)
11.5.3. Market Revenue and Forecast, by Application (2020-2032)
11.5.4. Brazil
11.5.4.1. Market Revenue and Forecast, by Type (2020-2032)
11.5.4.2. Market Revenue and Forecast, by Solution (2020-2032)
11.5.4.3. Market Revenue and Forecast, by Application (2020-2032)
11.5.5. Rest of LATAM
11.5.5.1. Market Revenue and Forecast, by Type (2020-2032)
11.5.5.2. Market Revenue and Forecast, by Solution (2020-2032)
11.5.5.3. Market Revenue and Forecast, by Application (2020-2032)
Chapter 12. Company Profiles
12.1. Amazon Web Services Inc.
12.1.1. Company Overview
12.1.2. Product Offerings
12.1.3. Financial Performance
12.1.4. Recent Initiatives
12.2. International Business Machines Corporation.
12.2.1. Company Overview
12.2.2. Product Offerings
12.2.3. Financial Performance
12.2.4. Recent Initiatives
12.3. Looker Data Sciences, Inc.
12.3.1. Company Overview
12.3.2. Product Offerings
12.3.3. Financial Performance
12.3.4. Recent Initiatives
12.4. Mu Sigma, Oracle Corporation
12.4.1. Company Overview
12.4.2. Product Offerings
12.4.3. Financial Performance
12.4.4. Recent Initiatives
12.5. SAP SE
12.5.1. Company Overview
12.5.2. Product Offerings
12.5.3. Financial Performance
12.5.4. Recent Initiatives
12.6. Sisense Inc.
12.6.1. Company Overview
12.6.2. Product Offerings
12.6.3. Financial Performance
12.6.4. Recent Initiatives
12.7. Tableau Software LLC.
12.7.1. Company Overview
12.7.2. Product Offerings
12.7.3. Financial Performance
12.7.4. Recent Initiatives
12.8. Zoho Corporation Pvt. Ltd.
12.8.1. Company Overview
12.8.2. Product Offerings
12.8.3. Financial Performance
12.8.4. Recent Initiatives
Chapter 13. Research Methodology
13.1. Primary Research
13.2. Secondary Research
13.3. Assumptions
Chapter 14. Appendix
14.1. About Us
14.2. Glossary of Terms
Cross-segment Market Size and Analysis for
Mentioned Segments
Additional Company Profiles (Upto 5 With No Cost)
Additional Countries (Apart From Mentioned Countries)
Country/Region-specific Report
Go To Market Strategy
Region Specific Market DynamicsRegion Level Market Share Import Export AnalysisProduction AnalysisOthers