IMARC Group's report titled "Advanced Analytics Market by Component (Software, Service), Type (Big Data Analytics, Business Analytics, Customer Analytics, Statistical Analytics, Risk Analytics, and Others), Deployment Mode (On-premises, Cloud-based), Business Function (Supply Chain, Sales and Marketing, Finance, Human Resource (HR), and Others), Enterprise Size (Large Enterprise, Small and Medium-sized Enterprise), Industry Vertical (BFSI, Healthcare, Government, IT and Telecom, Military and Defense, and Others), and Region 2024-2032". offers a comprehensive analysis of the industry, which comprises insights on the global advanced analytics market trends. The global market size reached US$ 22.7 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 106.4 Billion by 2032, exhibiting a growth rate (CAGR) of 18.18% during 2024-2032.
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Factors Affecting the Growth of the Advanced Analytics Industry:
- Need for Real-Time Decision Making:
The rising need for real-time decision making in the business environment is propelling the market growth. Organizations are seeking the ability to analyze data and derive insights in real-time to make informed decisions quickly. This capability is vital in many sectors, including finance, healthcare, retail, and manufacturing, where the speed of decision-making can impact performance and outcomes. Advanced analytics technologies, such as streaming analytics and real-time data processing, enable businesses to monitor operations, user interactions, and market conditions as they happen. This immediacy helps companies to respond swiftly to emerging opportunities, manage risks more effectively, and enhance operational efficiency. The increasing demand for real-time analytics solutions underscores the importance of advanced analytics in supporting dynamic and agile business strategies.
- Advancements in Technology Infrastructure:
The continuous advancements in technology infrastructure, including cloud computing, high-performance computing (HPC), and edge computing, are strengthening the market growth. These technologies provide the necessary computing power and storage capabilities required to process and analyze large datasets efficiently. Cloud computing offers scalable and flexible resources that make advanced analytics solutions more accessible to businesses of all sizes, facilitating the adoption of data analytics practices without the need for significant upfront investment in information technology (IT) infrastructure. Moreover, the rise of edge computing allows for data processing closer to the source, enabling faster insights and actions, particularly in applications requiring real-time analysis.
- Regulatory Compliance and Risk Management:
The increasing emphasis on regulatory compliance and risk management across industries is bolstering the market growth. Businesses are operating in regulated environments and facing challenges associated with managing risks effectively. Advanced analytics play an essential role in this by offering sophisticated tools for fraud detection, financial reporting, and compliance monitoring. These tools leverage data analytics to identify potential risks and anomalies, enabling organizations to take preemptive action to mitigate losses and comply with regulatory requirements. Additionally, in the financial services, advanced analytics aids in combating money laundering and ensuring compliance with regulations.
Leading Companies Operating in the Global Advanced Analytics Industry:
- Absolutdata Technologies Inc. (Infogain Corporation)
- Adobe Inc.
- Altair Engineering Inc.
- Alteryx Inc.
- Amazon Web Services Inc. (Amazon.com Inc.)
- Fair Isaac Corporation (FICO)
- Hewlett Packard Enterprise Company
- International Business Machines Corporation
- Microsoft Corporation
- Moody's Analytics Inc. (Moody's Corporation)
- SAS Institute Inc.
- TIBCO Software Inc.
Advanced Analytics Market Report Segmentation:
By Component:
- Software
- Service
- Professional Service
- Managed Service
Software exhibits a clear dominance in the market due to its essential role in providing the necessary tools and platforms for data analysis and interpretation.
By Type:
- Big Data Analytics
- Business Analytics
- Customer Analytics
- Statistical Analytics
- Risk Analytics
- Others
Big data analytics represent the largest segment, driven by the growing volume and complexity of data that organizations need to analyze for insights.
By Application:
- On-premises
- Cloud-based
On-premises accounts for the majority of the market share as many organizations prioritize data security and control, especially in handling sensitive or large-scale data.
By Business Function:
- Supply Chain
- Sales and Marketing
- Finance
- Human Resource (HR)
- Others
Supply chain holds the biggest market share accredited to the enhanced efficiency and optimization of supply chain operations by advanced analytics.
By Enterprise Size:
- Large Enterprise
- Small and Medium-sized Enterprise
Large Enterprises represent the leading segment attributed to their greater resources and need for comprehensive data analysis solutions.
By Industry Vertical:
- BFSI
- Healthcare
- Government
- IT and Telecom
- Military and Defense
- Others
BFSI accounts for the majority of the market share. These sectors heavily rely on data analytics for risk management, user insights, and regulatory compliance.
Regional Insights:
- North America (United States, Canada)
- Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, Others)
- Europe (Germany, France, United Kingdom, Italy, Spain, Russia, Others)
- Latin America (Brazil, Mexico, Others)
- Middle East and Africa
North America dominates the market owing to its early adoption of advanced analytics technologies, the presence of major players, and rising investments in research and development in this field.
Global Advanced Analytics Market Trends:
The growing integration of natural language processing (NLP) capabilities in advanced analytics is offering a favorable market outlook. This trend reflects the rising demand for more intuitive and accessible analytics tools that can understand, interpret, and generate human language. By incorporating NLP, advanced analytics platforms are becoming more user-friendly, allowing users without deep technical expertise to query data, generate reports, and gain insights using natural language commands. This democratization of data analytics enhances decision-making across all levels of an organization, making it easier for teams to extract valuable insights from complex datasets without relying heavily on data scientists.
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