Big Data Security Market Size Analysis Is Expected to Surpass $35.3 Billion by 2026 with CAGR of Roughly 12.4%

This research report categorizes the Big Data Security Market to forecast revenues, analyze trends, component, software, deployment type, organization size, vertical, and region.


Northbrook, IL 60062 -- (SBWire) -- 08/25/2023 --The global Big Data Security Market size is projected to grow from USD 17.5 billion in 2020 to USD 35.3 billion by 2026, recording a Compound Annual Growth Rate (CAGR) of 12.4% from 2020 to 2026, according to research report by MarketsandMarkets™.

The market's growth can be attributed to the increasing awareness and rising investments in big data security solutions across global organizations operating across verticals.

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Based on software, the data encryption, tokenization, and masking segment are estimated to lead the market in 2020.

Data encryption is a security method where information is encoded and can only be accessed or decrypted by users with the correct encryption key. Encrypted data, also known as ciphertext, appears scrambled or unreadable to persons or entities accessing without permission. Tokenization is the process of turning sensitive data into non-sensitive data called 'tokens' that can be used in a database or internal system without bringing it into scope. Data masking is a data security technique where a dataset is copied, but sensitive data is obfuscated. This copy is then used instead of the authentic data for testing or training purposes. By masking data, organizations can expose the data needed to test teams or database administrators without compromising it or getting out of compliance. The primary benefit is reduced security risks.

Based on Vertical, IT & ITES is estimated to lead the market in 2020.

The IT and ITES vertical is growing at an unprecedented rate in North America, Europe, and APAC. However, it is one of the major targets for cyberattacks as IT and ITES companies are dealing with storage and transfer of large volumes of critical business data and the employee data, such as names, addresses, and financial transactions. The rise in penetration of cloud computing, IoT devices, BYOD, and mobile and web applications has widened the surface of cyberattacks in the IT and ITES vertical.

North America is expected to hold the largest market share during the forecast period.

Most of the security vendors are based in North America, which makes the region to be among the early adopter of new and advanced security technologies. As a result, North America is expected to dominate the big data security market during the forecast period. Moreover, increase in the sophisticated cyber-attacks is anticipated to drive the implementation of big data security in several verticals such as banking, finance, government, and healthcare sectors. With the widespread use of digital payments, cloud based applications, IoT, security ecosystem has become more complex. Besides, various SMBs are welcoming disruptive work culture through services such as BYOD and work-from-home, exposing the enterprise data prone to number of cyber-attacks.

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Market Players

Major vendors, namely, include IBM (US), Oracle (US), Microsoft (US), Google (US), Amazon Web Services (US), Hewlett Packard Enterprise (US), Talend (US), Micro Focus (UK), Check Point (Israel), FireEye (US), Rapid7 (US), Thales (France), and Informatica (US).

Key Dynamic Factors For Big Data Security Market:

Privacy issues and data breaches: The demand for effective security solutions is still being driven by high-profile data breaches and worries about data privacy. Sensitive data being exposed highlights the necessity of comprehensive security procedures to safeguard vast amounts of data.

Growing Data Volume and Variety: Securing this complex and constantly changing data landscape is made more difficult by the exponential growth of data in terms of volume, variety, and velocity. To manage various data sources, formats, and data kinds, security systems must adapt.

Regulatory compliance: Organisations are required by law to secure and manage their data in accordance with data protection laws including GDPR, HIPAA, CCPA, and others. Strong security measures must be implemented in big data environments in order to comply with these standards.

Advanced Cyber Threats: As cyber threats get more complex, big data platforms attract the attention of cybercriminals looking to take advantage of holes in the system. Advanced threat detection, prevention, and response techniques are therefore required.

Cloud adoption: As big data activities move to cloud settings, new security problems arise. The importance of ensuring the security of data processed and stored in the cloud forces the development of specialised cloud-based big data security solutions.

Machine learning and artificial intelligence in security: The combination of these technologies improves the capacity to identify patterns and anomalies suggestive of security breaches in massive datasets. These innovations aid in the prevention of threats before they materialise.

Implementing efficient access control and robust authentication techniques is essential given the variety of people who access large data environments. Solutions for identity and access control become essential for limiting unauthorised access.

Insider threats: Internal staff members' malicious or unintentional acts present a serious risk. Big data systems' user activity monitoring aids in spotting and reducing insider threats.

Data masking and encryption: The importance of encrypting data both in transit and at rest cannot be overstated. Sensitive information is shielded from unauthorised access by modern encryption methods and data masking systems.

Vendor landscape and innovation: As security solution vendors work to keep ahead of developing risks, the big data security industry is characterised by constant innovation. The competitive landscape is also altered by new competitors, alliances, and mergers.

Scalability of Resources: As the need for data processing rises, security solutions must be scalable. A fundamental difficulty is ensuring that security controls can grow up with the developing big data infrastructure.

Operational Difficulties: Securing big data settings requires navigating challenging integration issues, complicated architectures, and a variety of data sources. These complications must be accommodated by solutions without interfering with business operations.

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Competitive and Segmentation Analysis:

An extensive segmentation landscape and fierce competition define the big data security market. Numerous market participants are offering a variety of solutions to address the changing problems that organisations are facing as they struggle to secure their enormous and varied datasets. The deployment method (on-premises and cloud-based), component (software and services), organisation size (small and medium-sized companies vs. large enterprises), industry vertical (IT and telecom, healthcare, BFSI, etc.), and location are some of the criteria that can be used to segment the market.

Established cybersecurity firms like IBM, Symantec (now a part of Broadcom), and McAfee use their standing and experience to offer complete big data security solutions in this cutthroat market. While this is going on, cutting-edge companies and up-and-coming competitors like Cloudera, Hortonworks (which is now a part of Cloudera), and Palantir provide fresh viewpoints with flexible and specialised products made specifically for the challenges of safeguarding big data settings. Cloud service providers have entered this market as well, offering big data workloads cloud-native security solutions, including AWS, Microsoft Azure, and Google Cloud. This combination of well-known industry heavyweights, quick-moving startups, and cloud service providers fosters a vibrant competitive environment that propels ongoing innovation and evolution in big data security products.

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