Synthetic Data Platform Market 2022

Industry Size, Emerging Trends, Regions, Growth Insights, Opportunities, and Forecast By 2033

Synthetic Data Platform Market by Type, by Application (Telecom and IT, Healthcare and Life Sciences, BFSI, Retail and eCommerce, Transportation and Logistics, Government and Manufacturing), and by Region – Global Share and Forecast to 2033

Region: Global | Format: Word, PPT, Excel | Report Status: Ongoing

According to the Market Statsville Group (MSG), the global synthetic data platform market size is expected to grow from USD 218.56 million in 2022 to USD 3,722.55 million by 2033, growing at a CAGR of 29.40% from 2023 to 2033.

Synthetic data is incredibly useful for detecting fraud in the financial sector. Using created fraud data, new fraud prevention and detection systems may be assessed for efficacy. The sector also uses synthetic data for customer analytics to analyze consumer behavior. In the industrial sector, synthetic data is used to improve the effectiveness of quality control systems and enable more efficient testing. Despite exchanging patient information internally or externally, synthetic data aids healthcare providers in maintaining the privacy of patient information. Due to these factors, the market is expected to grow rapidly. However, the scarcity of highly skilled labor force is hampering the market growth over the forecasting period. Additionally, an increase in demand for connected devices, IoT, and other technologies is likely to present the market with attractive growth possibilities in future years.

Definition of the Global Synthetic Data Platform Market

Synthetic data software enables users to build artificial datasets, such as images, text, or structured data on the basis of an initial dataset or data source. Users can use synthetic data tools to produce data from scratch while retaining the patterns and correlations seen in the original dataset. This protects personally identifiable information. Methods for synthesizing this synthetic data include computer-generated imagery (CGI), generative neural networks (GANs), and heuristics. Synthetic data is information that is created artificially rather than by natural events. To test mathematical models and train machine learning algorithms, synthetic data can be employed. Algorithms are frequently used to create it. Computer simulations are used to generate synthetic data. This includes most physical modeling applications, such as flight simulators and music synthesizers. These systems provide output that closely mimics the real thing but is totally generated by algorithms. Synthetic data platform is used as a filter in many industries to remove information that might threaten the confidentiality of certain data points. In theory, datasets for many sensitive applications exist but are not available to the general public; synthetic data eliminates the privacy risks of obtaining genuine customer information without consent or payment.

COVID-19 Impact on the Global Synthetic Data Platform Market

COVID-19 has impacted business continuity across entire economies. The COVID-19 pandemic is affecting organizations of all sizes in every industry. The effect of COVID-19 has disrupted data center transformation. Data center services such as video gaming, cloud computing, internet exchanges, content delivery networks, and other online services have grown as a result of initiatives such as work from home and lockdowns. Data center companies are being forced to improve their infrastructure, which is expected to drive the market's growth in the forecast period.

Throughout the projected period, the emergence of COVID-19 is likely to present numerous potential possibilities for the market. This potential includes a surge in demand for AI-driven synthetic data production in organizations as firms recognize the benefits of these platforms. The pandemic had a good influence on mobile and internet usage and the expanding use of computing services, which is expected to provide numerous prospects for synthetic data creation market growth in the following year.

Global Synthetic Data Platform Market Dynamics

Drivers: Rise in adoption of advanced technology such AI and ML

Synthetic data is computer-generated data that is quickly replacing real-world data. Computer algorithms create synthetic data rather than real-world documentation. As advanced AI applications are being developed, companies find it difficult to acquire large quantities of quality datasets for training ML models. Synthetic data, on the other hand, is assisting data scientists and developers in overcoming these obstacles and developing extremely trustworthy ML models. Such advancement provides boosted the market growth over the forecasting period.

In contrast, engineers are often required to train and build accurate machine learning models from highly quantitative and accurate datasets. Synthetic data also aids in the reduction of data collecting and labelling expenses. Synthetic raw data, in addition to saving costs, aids in addressing privacy concerns linked with sensitive real-world data.

Restraints: Lack of accuracy and high dependency on the real data

The nature of synthetic data is that it is usually generated by a computer program, which may or may not be accurate. As a result, synthetic data might generate erroneous conclusions on occasion. The lack of variability and correlation in synthetic data can lead to misleading, limited, or discriminatory conclusions. Synthetic data is partly dependent on the real model and dataset that is used to generate synthetic data. It is likely that numerous synthetic datasets which are generated in large amounts using the original dataset will perform ineffectively and sometimes even incorrectly in the absence of a desirable and qualitative real dataset. Due to lack of accuracy and highly dependency on the real data has hindered the market growth over the forecasting period.

Opportunities: Growing concept of Internet of Things (IoT) in synthetic data platform

The Internet of Things (IoT) idea is fast evolving from a vision to being prevalent in people's daily lives. This is seen in the integration of linked sensors from a wide range of devices, including mobile phones, healthcare equipment, and cars. There is a need for the development of infrastructure support and analytical tools to handle IoT data, which are naturally big and complex. The framework enables synthetic data to exhibit the complex characteristics of original data without compromising proprietary information and personal privacy. Due to increasing demand for data has become pronounced with a growing footfall of connected devices and IoT, further expediting the need for synthetic data to generate on-demand data.

Scope of the Global Synthetic Data Platform Market

The study categorizes the synthetic data platform market based on type, and application area at the regional and global levels.

By Type Outlook (Sales, USD Million, 2019-2033)

  • Conversational AI Based
  • Rule Based

By Application Outlook (Sales, USD Million, 2019-2033)

  • Telecom and IT
  • Healthcare and Life Sciences
  • BFSI
  • Retail and eCommerce
  • Transportation and Logistics
  • Government
  • Manufacturing

By Region Outlook (Sales, USD Million, 2019-2033)

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • Italy
    • France
    • UK
    • Spain
    • Poland
    • Russia
    • The Netherlands
    • Norway
    • Czech Republic
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Indonesia
    • Malaysia
    • Thailand
    • Singapore
    • Australia & New Zealand
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Rest of South America
  • The Middle East & Africa
    • Saudi Arabia
    • UAE
    • South Africa
    • Northern Africa
    • Rest of MEA

Healthcare and Life Sciences segment accounts for the largest market share by type

Based on the type, the market is divided into telecom and it, healthcare and life sciences, bfsi, retail and ecommerce, transportation and logistics, government and manufacturing. The healthcare and life sciences segment is expected to dominate the market share in 2022 in the global synthetic data platform market. The healthcare and life science industries are expected to exhibit strong demand for privacy-protecting synthetic data. Patient privacy, legal frameworks, distinct data sources, and artificial data creation techniques have acquired substantial traction in the face of data breach dangers. For instance, Anthem Inc. had established a partnership with Alphabet Inc.'s Google Cloud to generate 1.5 to 2 petabytes of synthetic data for improved fraud detection and tailored services. The enormous potential of synthetic data in healthcare for enhanced agility and privacy rules has continued to strengthen the worldwide market position of top enterprises.

North America is expected to witness the largest market share by Region

Based on the regions, the global synthetic data platform market has been segmented across Europe, North America, the Middle East & Africa, Asia-Pacific, and South America. North America is projected to account for the highest market share in 2022. Since end-use industries have shifted towards fraud detection, NLP, and image data, the United States and Canada have emerged as profitable regions. J.P. Morgan, American Express, Amazon, and Google's Waymo have all increased their investments in synthetic data. For instance, Amazon SageMaker Ground Truth was offered to produce tagged synthetic picture data. These industry participants will favor synthetic data for training machine learning, payment data for fraud detection, and anti-money laundering practices.

Competitive Landscape: Global Synthetic Data Platform Market

The synthetic data platform market is a significant competitor, and extremely cutthroat in the sector are using strategies including product launches, partnerships, acquisitions, agreements, and growth to enhance their market positions. Most sector businesses focus on increasing their operations worldwide and cultivating long-lasting partnerships.

Major key players in the global synthetic data platform market are:

  • Rendered.ai
  • Conversica
  • E-bot7
  • Ultimate.ai
  • Ada
  • Microsoft
  • Nuance Communications, Inc.
  • IPsoft /Amelia US LLC
  • LogMeIn.Inc / GoTo
  • Netomi
  • Company 11
  • Company 12
  • Company 13
  • Company 14
  • Company 15

Key Issues Addressed

  • What is the market size by various segmentation of the synthetic data platform by region and its respective countries?
  • What are the customer buying behavior, key takeaways, and Porter's 5 forces of the synthetic data platform market?
  • What are the key opportunities and trends for manufacturers involved in the synthetic data platform supply chain?
  • What are the fundamental dynamics (drivers, restraints, opportunities, and challenges) of the market?
  • What and how regulations, schemes, patents, and policies are impacting the growth of the market?
  • What are the upcoming technological solutions influencing market trends? How will existing companies adapt to the new change in technology?
  • The market player positioning, top winning strategies by years, company product developments, and launches will be?
  • How has COVID-19 impacted the demand and sales of synthetic data platform in the global market? Also, the expected BPS drop or rise count of the market and market predicted recovery period.
  • Detailed analysis of the competitors and their latest launch, and what are the prominent startups introduced in the target market? Also, detailed company profiling of 25+ leading and prominent companies in the market.

Frequently Asked Questions

  • Key Issues Addressed
  • What is the market size and growth rate for different segmentations at a global, regional, & country level?
  • What is the customer buying behavior, key takeaways, and Porter's 5 forces of the market?
  • What are the key opportunities and trends for manufacturers involved in the supply chain?
  • What are the fundamental dynamics (drivers, restraints, opportunities, and challenges) of the market?
  • What and how regulations, schemes, patents, and policies are impacting the growth of the market?
  • How will existing companies adapt to the new change in technology?
  • The market player positioning, top winning strategies by years, company product developments, and launches will be?
  • How has COVID-19 impacted the demand and sales of in the market? Also, the expected BPS drop or rise count of the market and market predicted recovery period.
  • Who are the leading companies operating in the market? Also, who are the prominent startups that disrupt the market in coming years?
  • PUBLISHED ON: Dec, 2022
  • BASE YEAR: 2022
  • STUDY PERIOD: 2019-2033
  • COMPANIES COVERED: 15
  • COUNTRIES COVERED: 24
  • NO OF PAGES: 243

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