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Streaming Analytics Market, Opportunity, Growth Drivers, Industry Trend Analysis and Forecast, 2024-2032

Publisher Global Market Insights
Published Jul 18, 2024
Length 270 Pages
SKU # GMI19126889

Description

Streaming Analytics Market, Opportunity, Growth Drivers, Industry Trend Analysis and Forecast, 2024-2032


Global Streaming Analytics Market will witness 27.5% CAGR between 2024 and 2032, propelled by the escalating demand for real-time data processing across various industries. As businesses increasingly rely on data-driven decision-making, the need for advanced analytics tools that can process and analyze data streams in real-time has surged. For instance, according to a report by Forbes, 95% of businesses cite the need to manage unstructured data as a problem for their business. Streaming analytics platforms enable organizations to gain actionable insights from data as it is generated, allowing for immediate responses to changing conditions and opportunities, thereby enhancing operational efficiency and competitiveness.

The overall Streaming Analytics Market is categorized based on component, deployment, organization size, application, industry, and region.

The services segment will experience substantial growth over the forecast period. As organizations adopt streaming analytics solutions, the demand for associated services, including consulting, integration, and support, has risen. These services play a crucial role in helping businesses implement and optimize streaming analytics platforms, ensuring seamless integration with existing systems and processes. Additionally, ongoing support and maintenance services are essential for keeping the analytics systems up-to-date and functioning optimally. The rising complexity of data environments and the need for customized solutions are further driving the growth of the services segment.

The fraud detection application will capture a significant share of the streaming analytics market by 2032. Streaming analytics is increasingly being utilized to detect and prevent fraudulent activities in real-time across various sectors, including finance, e-commerce, and telecommunications. By continuously monitoring data streams, these platforms can identify unusual patterns and anomalies that may indicate fraudulent behavior, enabling organizations to take immediate action. The growing sophistication of cyber threats and the increasing reliance on digital transactions are key factors driving the adoption of streaming analytics for fraud detection.

Europe streaming analytics industry will achieve substantial growth throughout the forecast period, supported by a strong digital infrastructure, significant investment in data-driven technologies, and a high level of awareness regarding the benefits of real-time analytics. European businesses across various sectors are increasingly adopting streaming analytics to enhance decision-making processes, improve customer experiences, and drive innovation. Furthermore, robust data protection regulations and government initiatives promoting digital transformation are fostering the widespread adoption of streaming analytics solutions in the region.

Table of Contents

270 Pages
Chapter 1 Scope and Methodology
1.1 Market scope and definition
1.2 Base estimates and calculations
1.3 Forecast parameters
1.4 Data sources
1.4.1 Primary
1.4.2 Secondary
1.4.2.1 Paid sources
1.4.2.2 Public sources
Chapter 2 Executive Summary
2.1 Industry 360º synopsis, 2021 - 2032
Chapter 3 Industry Insights
3.1 Industry ecosystem analysis
3.2 Vendor matrix
3.3 Technology and innovation landscape
3.4 Patent analysis
3.5 Key news and initiatives
3.6 Regulatory landscape
3.7 Impact forces
3.7.1 Growth drivers
3.7.1.1 Real-time data processing requirements
3.7.1.2 Growth of IoT
3.7.1.3 Demand for predictive analytics
3.7.1.4 Increasing use of cloud-based solutions
3.7.1.5 Need for enhanced customer experience
3.7.2 Industry pitfalls and challenges
3.7.2.1 Significant costs associated with technology implementation
3.7.2.2 Data privacy and security concerns
3.8 Growth potential analysis
3.9 Porter’s analysis
3.9.1 Supplier power
3.9.2 Buyer power
3.9.3 Threat of new entrants
3.9.4 Threat of substitutes
3.9.5 Industry rivalry
3.10 PESTEL analysis
Chapter 4 Competitive Landscape, 2023
4.1 Company market share analysis
4.2 Competitive positioning matrix
4.3 Strategic outlook matrix
Chapter 5 Market Estimates and Forecast, By Component, 2021 - 2032 (USD Million)
5.1 Key trends
5.2 Software
5.3 Services
5.3.1 Professional service
5.3.2 Managed service
Chapter 6 Market Estimates and Forecast, By Deployment, 2021 – 2032 (USD Million)
6.1 Key trends
6.2 Cloud-based
6.2.1 Public
6.2.2 Private
6.2.3 Hybrid
6.3 On-premises
Chapter 7 Market Estimates and Forecast, By Organization Size, 2021 – 2032 (USD Million)
7.1 Key trends
7.2 SMEs
7.3 Large-sized enterprises
Chapter 8 Market Estimates and Forecast, By Application, 2021 – 2032 (USD Million)
8.1 Key trends
8.2 Fraud detection
8.3 Sales and marketing
8.4 Risk management
8.5 Predictive asset management
8.6 Network management and optimization
8.7 Location intelligence
8.8 Supply chain management
8.9 Others
Chapter 9 Market Estimates and Forecast, By Industry, 2021 – 2032 (USD Million)
9.1 Key trends
9.2 BFSI
9.3 IT and telecom
9.4 Healthcare
9.5 Retail
9.6 Manufacturing
9.7 Government
9.8 Energy and utilities
9.9 Others
Chapter 10 Market Estimates and Forecast, By Region, 2021 - 2032 (USD Million)
10.1 Key trends
10.2 North America
10.2.1 U.S.
10.2.2 Canada
10.3 Europe
10.3.1 UK
10.3.2 Germany
10.3.3 France
10.3.4 Italy
10.3.5 Spain
10.3.6 Rest of Europe
10.4 Asia Pacific
10.4.1 China
10.4.2 India
10.4.3 Japan
10.4.4 South Korea
10.4.5 ANZ
10.4.6 Rest of Asia Pacific
10.5 Latin America
10.5.1 Brazil
10.5.2 Mexico
10.5.3 Rest of Latin America
10.6 MEA
10.6.1 UAE
10.6.2 Saudi Arabia
10.6.3 South Africa
10.6.4 Rest of MEA
Chapter 11 Company Profiles
11.1 Alphabet Inc.
11.2 Amazon.com, Inc.
11.3 Cloudera, Inc.
11.4 Hewlett Packard Enterprise Company
11.5 Impetus Technologies, Inc.
11.6 Informatica LLC
11.7 Intel Corporation
11.8 International Business Machines Corporation
11.9 Microsoft Corporation
11.10 Oracle Corporation
11.11 SAP SE
11.12 SAS Institute Inc.
11.13 Software AG
11.14 Teradata Corporation
11.15   TIBCO Software Inc

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