세계의 증강 분석 시장(2023-2030년)

Overview

Global Augmented Analytics Market reached US$ 8.5 billion in 2022 and is expected to reach US$ 46.3 billion by 2030, growing with a CAGR of 23.4% during the forecast period 2023-2030.

Continuous growth and development in technologies in AI and ML algorithms have made it easier for developing analytics tools that automate many tasks including data preparation, analysis and visualization. In order to make meaning from the massive volumes of data generated each day, which come from a variety of sources such as IoT devices, social media and online transactions, more sophisticated analytics tools are currently being expected.

By democratizing data, augmented analytics renders data analysis more approachable for non-technical users, allowing business users to carry out challenging analytics tasks without the assistance of data scientists or IT specialists. Data analysis becomes more understandable because of augmented analytics solutions intuitive user interfaces, support for natural language processing and interactive dashboards.

In 2022, Asia-Pacific is expected to be the fastest growing region having less than 1/4th of the global augmented analytics market. The region has world's most populous countries and generates vast data from many sources, such as e-commerce, mobile apps, IoT devices and social media. Augmented analytics assists organizations harness this data for insights and decision-making.

Dynamics

Growing Adoption of Industry 5.0

Several growth factors will continue to contribute to the adoption of Industry 5.0, which involves the combination of human intelligence with cutting-edge technology like augmented reality (AR). Industrial workers may now perceive complex data, equipment and processes in real-time because of augmented reality (AR) technology, which can offer a more immersive and interactive user experience and this improved user experience may encourage greater acceptance and adoption.

According to the article by Siemens in 2023, the shift from Industry 4.0 to Industry 5.0, puts a strong emphasis on the combination of human intelligence and artificial intelligence (AI) to achieve operational excellence. Through the supply of innovative tools and knowledge for data-driven decision-making to operational professionals, augmented analytics plays a crucial role in this shift.

Increase in Need to Make the Work Easier for Citizen Data Scientists and Business

Towards democratizing access to data and analytical tools, augmented reality is being utilized. It minimizes the need for in-depth technical skills by enabling business users and citizen data scientists to interact with complex data sets and analytics in a visual and accessible way. It has become easier to develop and interact with augmented reality-based data visualizations and analytics because augmented reality applications are being developed with user-friendly interfaces that require no coding or technical abilities.

In reality, data scientists spend more than 80% of their time performing routine, straightforward tasks like categorizing and cleaning the data. Augmented analytics can be used to shorten this period of time. It can be utilized directly by business users without the help of a business analyst or data scientist because it is meant to conduct analysis and create business insights automatically with little to no oversight. Through automation, it reduces the company's reliance on data scientists.

Technology Advancement

AI and ML are instrumental in the automation of data analysis, pattern recognition and predictive modeling. Augmented analytics leverages these technologies to assist users in data preparation, insights generation and anomaly detection. NLP enables users to interact with data and analytics platforms using natural language queries and commands. It leads to simplifies the process of asking questions and receiving insights, making analytics more accessible to non-technical users.

For instance, on 5 September 2023, Perfect Corp., a leading artificial intelligence and augmented reality beauty and fashion tech solutions provider, announced updates to its AI-powered Live Skin Analysis Solution and this HIPAA-compliant and dermatologist-verified technology offers users deep insights into their skin condition and personalized skincare recommendations. The AI Skin Analysis innovation can now analyze up to 14 skin concerns through live camera mode and it includes augmented reality overlay effects to highlight specific skin concerns in real-time.

Privacy Risk and Difficult in Interpretation

The application of augmented analytics largely depends on reliable, accurate and integrated data. Poor data quality could end up in incorrect findings and actions. It can be difficult and time-consuming to integrate data from numerous sources, especially when navigating outdated technologies and various data formats. Privacy risks arise when sensitive or personally identifiable information (PII) is analyzed, making compliance to data protection laws like the GDPR essential.

AI algorithms used in augmented analytics can inherit biases from training data, potentially leading to biased insights and recommendations. Ensuring fairness and equity in AI-driven analytics is a challenge, as it requires careful consideration of factors like demographic bias. Some AI models used in augmented analytics, such as deep learning models, can be difficult to interpret, making it challenging to understand how insights are generated.

Segment Analysis

The global augmented analytics market is segmented based on component, deployment, organization size, business function, end-user and region.

Rising Adoption of Cloud Platform

Cloud deployment is expected to be the dominant segment with about 1/3rd of the market during the forecast period 2023-2030. Cloud systems have virtually infinite scalability, allowing businesses to handle massive data volumes and conduct sophisticated analytical activities without requiring to invest in significant upfront equipment investments.

As it is more cost-effective than on-premises infrastructure, cloud-based augmented analytics solutions frequently employ a pay-as-you-go business model and this enables enterprises to avoid the high capital costs of on-premises infrastructure and makes augmented analytics available to a wider spectrum of companies.

For instance, on 6 September 2023, ZINFI Technologies, Inc., a leader in partner relationship management and through-channel marketing automation introduced advanced generative artificial intelligence capabilities into its SaaS platform for unified partner management. ZINFI's analytics capabilities, powered by Microsoft's Power BI, are further strengthened with the integration of Microsoft's Copilot technology and this enables the generation of insights based on partner performance analytics across various activities to improve return on investment.

Geographical Penetration

Technology Innovation in North America

North America is among the growing regions in the global augmented analytics market covering more than 1/3rd of the market. The region is a hub for technological innovation, with many AI and machine learning research centers and startups and this has led to the development of advanced analytics tools and algorithms that power augmented analytics solutions. According to a report by BCG, Australian Airlines saves US$ 40 million in annual costs by using cloud analytics.

In May 2022, Pyramid Analytics, a decision intelligence platform provider, achieved significant recognition in Gartner's Critical Capabilities for Analytics and Business Intelligence Platforms report. Pyramid Analytics secured the top ranking in the augmented analytics Use Case among 20 companies evaluated by Gartner. Augmented analytics involves using technologies like machine learning and AI to aid in data preparation, insight generation and explanation, enhancing data exploration and analysis in analytics and business intelligence platforms.

Competitive Landscape

The major global players in the market include: SAP SE, International Business Machines Corporation (IBM), Salesforce.com, Inc., Sisense Inc., Tableau Software, THOUGHTSPOT, Tibco Software Inc., QLIK, Microsoft and SAS Institute Inc.

COVID-19 Impact Analysis

The pandemic generated an unprecedented amount of data related to infection rates, healthcare resources, economic changes and remote work patterns. Analyzing this complex data presented challenges. Augmented analytics helped organizations make sense of this vast data by automating data preparation, pattern recognition and insights generation. Many businesses faced disruptions, changes in customer behavior and shifts in demand due to lockdowns and restrictions. Traditional data analytics models needed adaptation.

Augmented analytics allowed businesses to quickly adapt by automating the analysis of changing market conditions and customer preferences, helping them make data-driven decisions. With remote work becoming widespread, businesses needed to monitor and support employees' productivity and well-being. Augmented analytics tools provided insights into employee engagement, productivity and remote work challenges, helping organizations make data-driven adjustments to their policies and practices.

Augmented analytics played a crucial role in tracking and analyzing COVID-19 data, including infection rates, vaccination progress and healthcare resource allocation and the pandemic disrupted global supply chains, leading to challenges in logistics and inventory management and these analytics tools helped public health authorities and healthcare organizations make informed decisions about resource allocation and public health interventions.

AI Impact

AI streamlines data preparation tasks by automatically cleaning, transforming and integrating data from various sources and this reduces the time and effort required for data preparation. NLP capabilities in AI enable users to interact with data and analytics platforms using natural language queries and commands, this makes it easier for non-technical users to explore data and receive insights.

AI-powered data visualization tools automatically generate meaningful charts, graphs and dashboards based on the data, making it easier for users to visualize trends and patterns. AI algorithms can analyze data and automatically generate insights and recommendations and this helps users uncover hidden patterns and make data-driven decisions more quickly. The model can predict future trends and outcomes based on historical data.

For instance, on 29 August 2023, Wizeline, an AI-focused digital services provider, introduced its "AI-Native Offerings" at Disney's Data & Analytics Conference and these offerings emphasize the fusion of AI technology with a human-centric approach, highlighting Wizeline's belief in enhancing human capabilities with AI rather than replacing them.

The company showcased its capabilities through demonstrations centered on Generative AI and engaged with conference attendees to illustrate the real-world applications of their solutions. Wizeline's commitment to AI innovation is embodied in its AI-Native Framework, which aims to seamlessly integrate AI technologies into corporate infrastructures.

Russia- Ukraine War Impact

The war can disrupt supply chains, leading to fluctuations in the availability and cost of hardware components and data storage and this could affect the implementation and maintenance of augmented analytics solutions. In regions directly affected by the conflict, data collection and reporting may be disrupted. Augmented analytics relies on high-quality data, so any disruptions can hinder insights generation.

During times of geopolitical instability, there is often an uptick in cyberattacks and espionage. Augmented analytics platforms may need to strengthen their security measures to protect sensitive data. Organizations and governments may prioritize resources for immediate humanitarian and security needs, potentially diverting investments away from AI and analytics initiatives, including augmented analytics.

By Component

• Software
• Services

By Deployment

• Cloud
• On-Premise

By Organization Size

• Small & Medium Sized Enterprises
• Large Enterprises

By Business Function

• Sales & Marketing
• Finance
• IT
• Operations
• Others

By End-User

• Retail
• Healthcare and Life Sciences
• BFSI
• Telecom and IT
• Manufacturing
• Government
• Others

By Region

• North America
  • U.S.
  • Canada
  • Mexico

• Europe
  • Germany
  • UK
  • France
  • Italy
  • Russia
  • Rest of Europe

• South America
  • Brazil
  • Argentina
  • Rest of South America

• Asia-Pacific
  • China
  • India
  • Japan
  • Australia
  • Rest of Asia-Pacific

• Middle East and Africa

Key Developments

• On 9 November 2021, Narrative BI launched the Public Beta version of its platform, featuring a set of powerful features designed to provide valuable insights from Google Analytics. The platform includes an Insight Generation Engine that aims to simplify trend identification and anomaly detection in Google Analytics, making it easier for growth teams to stay ahead of emerging trends and identify blind spots and this launch offers growth teams a lightweight yet powerful marketing analytics solution.
• On 23 April 2021, Subex launched HyperSense, an end-to-end augmented analytics platform designed to leverage artificial intelligence (AI) across the data value chain. HyperSense offers a range of augmented analytics capabilities in a flexible and modular platform, with no-code features that allow users without coding knowledge to aggregate data from various sources, create, interpret and fine-tune AI models and share their findings within the organization.
• On 20 May 2022, Alteryx, a data and analytics vendor, introduced new integrations with cloud data platforms such as Databricks, Snowflake and Google BigQuery to allow users to work with data directly in their storage platform of choice and these integrations aim to enhance connectivity and streamline data preparation for analytics, reducing the time to gain insights.

Why Purchase the Report?

• To visualize the global augmented analytics market segmentation based on component, deployment, organization size, business function, end-user and region, as well as understand key commercial assets and players.
• Identify commercial opportunities by analyzing trends and co-development.
• Excel data sheet with numerous data points of augmented analytics market-level with all segments.
• PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
• Product mapping available as excel consisting of key products of all the major players.

The global augmented analytics market report would provide approximately 61 tables, 58 figures and 186 Pages.

Target Audience 2023

• Manufacturers/ Buyers
• Industry Investors/Investment Bankers
• Research Professionals
• Emerging Co.mpanies

Table of Contents

1. Methodology and Scope

• 1.1. Research Methodology
• 1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

• 3.1. Snippet by Component
• 3.2. Snippet by Deployment
• 3.3. Snippet by Organization Size
• 3.4. Snippet by Business Function
• 3.5. Snippet by End-User
• 3.6. Snippet by Region

4. Dynamics

• 4.1. Impacting Factors
  • 4.1.1. Drivers
    • 4.1.1.1. Growing Adoption of Industry 5.0
    • 4.1.1.2. Increase in Need to Make the Work Easier for Citizen Data Scientists and Business
    • 4.1.1.3. Technology Advancement
  • 4.1.2. Restraints
    • 4.1.2.1. Privacy Risk and Difficult in Interpretation
  • 4.1.3. Opportunity
  • 4.1.4. Impact Analysis

5. Industry Analysis

• 5.1. Porter's Five Force Analysis
• 5.2. Supply Chain Analysis
• 5.3. Pricing Analysis
• 5.4. Regulatory Analysis
• 5.5. Russia-Ukraine War Impact Analysis
• 5.6. DMI Opinion

6. COVID-19 Analysis

• 6.1. Analysis of COVID-19
  • 6.1.1. Scenario Before COVID
  • 6.1.2. Scenario During COVID
  • 6.1.3. Scenario Post COVID
• 6.2. Pricing Dynamics Amid COVID-19
• 6.3. Demand-Supply Spectrum
• 6.4. Government Initiatives Related to the Market During Pandemic
• 6.5. Manufacturers Strategic Initiatives
• 6.6. Conclusion

7. By Component

• 7.1. Introduction
  • 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
  • 7.1.2. Market Attractiveness Index, By Component
• 7.2. Software*
  • 7.2.1. Introduction
  • 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 7.3. Services

8. By Deployment

• 8.1. Introduction
  • 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
  • 8.1.2. Market Attractiveness Index, By Deployment
• 8.2. Cloud *
  • 8.2.1. Introduction
  • 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 8.3. On-Premise

9. By Organization Size

• 9.1. Introduction
  • 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
  • 9.1.2. Market Attractiveness Index, By Organization Size
• 9.2. Small & Medium Sized Enterprises*
  • 9.2.1. Introduction
  • 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 9.3. Large Enterprises

10. By Business Function

• 10.1. Introduction
  • 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Business Function
  • 10.1.2. Market Attractiveness Index, By Business Function
• 10.2. Sales & Marketing*
  • 10.2.1. Introduction
  • 10.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 10.3. Finance
• 10.4. IT
• 10.5. Operations
• 10.6. Others

11. By End-User

• 11.1. Introduction
  • 11.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 11.1.2. Market Attractiveness Index, By End-User
• 11.2. Retail*
  • 11.2.1. Introduction
  • 11.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 11.3. Healthcare and Life Sciences
• 11.4. BFSI
• 11.5. Telecom and IT
• 11.6. Manufacturing
• 11.7. Government
• 11.8. Others

12. By Region

• 12.1. Introduction
  • 12.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
  • 12.1.2. Market Attractiveness Index, By Region
• 12.2. North America
  • 12.2.1. Introduction
  • 12.2.2. Key Region-Specific Dynamics
  • 12.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
  • 12.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
  • 12.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
  • 12.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Business Function
  • 12.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 12.2.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 12.2.8.1. U.S.
    • 12.2.8.2. Canada
    • 12.2.8.3. Mexico
• 12.3. Europe
  • 12.3.1. Introduction
  • 12.3.2. Key Region-Specific Dynamics
  • 12.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
  • 12.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
  • 12.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
  • 12.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Business Function
  • 12.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 12.3.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 12.3.8.1. Germany
    • 12.3.8.2. UK
    • 12.3.8.3. France
    • 12.3.8.4. Italy
    • 12.3.8.5. Russia
    • 12.3.8.6. Rest of Europe
• 12.4. South America
  • 12.4.1. Introduction
  • 12.4.2. Key Region-Specific Dynamics
  • 12.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
  • 12.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
  • 12.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
  • 12.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Business Function
  • 12.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 12.4.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 12.4.8.1. Brazil
    • 12.4.8.2. Argentina
    • 12.4.8.3. Rest of South America
• 12.5. Asia-Pacific
  • 12.5.1. Introduction
  • 12.5.2. Key Region-Specific Dynamics
  • 12.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
  • 12.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
  • 12.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
  • 12.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Business Function
  • 12.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 12.5.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 12.5.8.1. China
    • 12.5.8.2. India
    • 12.5.8.3. Japan
    • 12.5.8.4. Australia
    • 12.5.8.5. Rest of Asia-Pacific
• 12.6. Middle East and Africa
  • 12.6.1. Introduction
  • 12.6.2. Key Region-Specific Dynamics
  • 12.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
  • 12.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
  • 12.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
  • 12.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Business Function
  • 12.6.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User

13. Competitive Landscape

• 13.1. Competitive Scenario
• 13.2. Market Positioning/Share Analysis
• 13.3. Mergers and Acquisitions Analysis

14. Company Profiles

• 14.1. SAP SE*
  • 14.1.1. Company Overview
  • 14.1.2. Product Portfolio and Description
  • 14.1.3. Financial Overview
  • 14.1.4. Key Developments
• 14.2. International Business Machines Corporation (IBM)
• 14.3. Salesforce.com, Inc.
• 14.4. Sisense Inc.
• 14.5. Tableau Software
• 14.6. THOUGHTSPOT
• 14.7. Tibco Software Inc.
• 14.8. QLIK
• 14.9. Microsoft
• 14.10. SAS Institute Inc.

LIST NOT EXHAUSTIVE

15. Appendix

• 15.1. About Us and Services
• 15.2. Contact Us