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시장보고서
상품코드
1690030
데이터 분석 시장 규모, 점유율, 성장 분석 : 유형별, 솔루션별, 용도별, 산업별, 지역별 - 산업 예측(2025-2032년)Data Analytics Market Size, Share, and Growth Analysis, By Type (Descriptive Analytics, Predictive Analytics), By Solution (Data Management, Data Mining), By Application, By Industry, By Region - Industry Forecast 2025-2032 |
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데이터 분석 시장 규모는 2023년에 650억 달러로 평가되며, 2024년 828억 8,000만 달러에서 2032년에는 5,787억 7,000만 달러로 성장하며, 예측 기간(2025-2032년)의 CAGR은 27.5%로 성장할 전망입니다.
세계 데이터 분석 시장은 빅데이터 및 예측 분석에 대한 수요 증가로 인해 업계 전반에 걸쳐 강력한 성장세를 보이고 있습니다. 컴퓨터 프로그래밍, 수학, 통계학을 통합한 데이터 분석은 가치 있는 인사이트를 도출하고 복잡한 비즈니스 문제를 해결하는 데 매우 중요합니다. Qualtrics와 ServiceNow의 조사에 따르면 소비자의 83%는 원활한 디지털 경험을 원하며, Qualtrics와 ServiceNow의 조사에 따르면 소비자의 83%는 원활한 디지털 경험을 원한다고 응답했습니다. 는 원활한 디지털 경험을 제공하는 제품과의 소통을 선호하고, 70%는 이러한 제품을 더 신뢰하는 것으로 나타났습니다. 기업이 데이터베이스 의사결정을 우선시하는 가운데, AI와 자동화가 효율성과 경쟁 우위를 강화하는 데 매우 중요한 역할을 하면서 시장은 더욱 확대될 것으로 보입니다.
Data Analytics Market size was valued at USD 65.0 billion in 2023 and is poised to grow from USD 82.88 billion in 2024 to USD 578.77 billion by 2032, growing at a CAGR of 27.5% during the forecast period (2025-2032).
The Global Data Analytics Market is experiencing robust growth, driven by the rising demand for big data and predictive analytics across industries. Data analysis, which integrates computer programming, mathematics, and statistics, is crucial for extracting valuable insights and solving complex business challenges. Leading market players are increasingly investing in scalable data-sharing solutions, data fabrics, and AI-driven analytics to foster innovation and digital transformation. According to a survey by Qualtrics and ServiceNow, 83% of consumers prefer engaging with products that offer seamless digital experiences, while 70% place greater trust in such offerings. As organizations prioritize data-driven decision-making, the market is set to expand further, with AI and automation playing a pivotal role in enhancing efficiency and competitive advantage.
Top-down and bottom-up approaches were used to estimate and validate the size of the Global Data Analytics market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
Global Data Analytics Market Segments Analysis
Global Data Analytics Market is segmented by Type, Solution, Application, Industry and region. Based on Type, the market is segmented into Descriptive Analytics, Predictive Analytics, Augmented Analytics, Real-Time Analytics, Prescriptive Analytics and Others (Diagnostic Analytics). Based on Solution, the market is segmented into Data Management, Data Mining, Security Intelligence and Data Monitoring. Based on Application, the market is segmented into Supply Chain Management, Enterprise Resource Planning, Database Management, Human Resource Management, Customer Relationship Management and Others (Product Lifecycle Management). Based on Industry, the market is segmented into Healthcare, IT & Telecom, BFSI, Education, Manufacturing, Government, Transportation & Logistics, Retail & E-commerce and Others (Media & Entertainment). Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & Africa.
Driver of the Global Data Analytics Market
The exponential surge in data generation from businesses and consumers is a key driver propelling the growth of the global data analytics market. Organizations across industries are increasingly leveraging advanced big data analytics solutions to process and interpret vast volumes of structured and unstructured data. The ability to extract actionable insights from this information enhances decision-making, optimizes operations, and fosters competitive advantage. Additionally, the rise of digital transformation, IoT adoption, and AI-driven analytics is further accelerating the demand for robust data analytics platforms. As companies prioritize data-driven strategies to improve efficiency and customer experience, the need for scalable and intelligent analytics solutions continues to expand, fueling market growth on a global scale.
Restraints in the Global Data Analytics Market
Growing concerns over data privacy, coupled with increasingly stringent regulations such as the General Data Protection Regulation (GDPR), are emerging as significant restraints in the Global Data Analytics Market. Organizations face mounting challenges in collecting, storing, and processing personal data, as regulatory frameworks impose strict compliance requirements and potential financial penalties for non-compliance. These legal constraints can limit the scope of data-driven insights, reducing the effectiveness of advanced analytics solutions, particularly in industries reliant on customer data. Moreover, evolving global policies on cross-border data transfers further complicate operational strategies for multinational enterprises, leading to increased compliance costs and potential restrictions on leveraging big data for competitive advantage, thereby slowing market expansion.
Market Trends of the Global Data Analytics Market
The integration of artificial intelligence (AI) and machine learning (ML) with big data analytics is driving a transformative shift in the Global Data Analytics Market. This convergence is enhancing the ability of enterprises to identify complex patterns, generate predictive insights, and automate decision-making processes with greater precision. By leveraging AI and ML algorithms, organizations can extract deeper, more actionable intelligence from vast datasets, enabling data-driven strategies that optimize operations and improve business outcomes. This trend is accelerating the adoption of advanced analytics tools across industries, empowering companies to gain a competitive edge through real-time forecasting, risk assessment, and process automation. As AI-driven analytics continue to evolve, businesses are increasingly prioritizing intelligent, automated solutions to maximize efficiency and innovation.