Friday, June 25, 2021

Data Classification Market Growing at a CAGR 25.4% | Key Player Microsoft, Symantec, Opentext, Boldon James, Minereye

Data Classification Market Growing at a CAGR 25.4% | Key Player Microsoft, Symantec, Opentext, Boldon James, Minereye
IBM (US), Google (US), Microsoft (US), AWS (US), Symantec (US), OpenText (Canada), Covata (Australia), Boldon James (England), Varonis (US), Innovative Routines International (IRI), Informatica (US), Dataguise (US), Spirion (US), Digital Guardian (US), Titus (Canada), Netwrix Corporation (US), PKWARE (US), GTB Technologies (US), Forcepoint (US), Sienna Group (US)
Data Classification Market by Component (Solutions (Standalone and Integrated) and Services), Application (Access Control, GRC, Web, Mobile & Email Protection, and Centralized Management), Methodology, Vertical, and Region - Global Forecast to 2023

MarketsandMarkets expects the global Data Classification Market to grow from USD 536 million in 2018 to USD 1,661 billion by 2023, at a Compound Annual Growth Rate (CAGR) of 25.4% during forecast period. Regulatory compliance, growth in uncontrolled data volumes, and increased security risks are expected to drive the data classification market.

Integrated solutions segment to hold a larger market size during the forecast period

Many vendors offer data classification as an integrated functionality rather than developing a new standalone product. It drives the integrated solutions segment’s growth. Vendors offering data security solutions such as DLP and data discovery prefer to integrate the data classification functionality in these solutions rather than building a standalone capability. Integrated solution providers form partnerships with other standalone solution vendors to integrate data classification capabilities as a part of their wider data security product offering.

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BFSI vertical to hold the largest market size during the forecast period

The BFSI vertical is leading in the adoption of the data classification solutions and services, due to the nature of the data, such as Personally Identifiable Information (PII), Personal Credit Card Information (PCI), intellectual property (IP) related financial systems, authentication and access control information, and company financial information. BFSI companies have to protect personal data to abide by stringent data privacy rules. Data classification enables the BFSI vertical to prioritize sensitive data and raise flags if the data is mishandled.

Data classification refers to the process of sorting and categorizing data into different distinct classes. Data classification enables the separation and classification of data according to data set requirements for various business and individual objectives.

Data classification involves tagging data with the ease of searchability and tractability. It also eliminates multiple duplications of data, which can reduce storage and backup costs while speeding up the search process. Though the classification process may sound highly technical, it is a topic that should be understood by an organization’s leadership.

Major vendors of data classification include IBM (US), Google (US), Microsoft (US), AWS (US), Symantec (US), OpenText (Canada), Covata (Australia), Boldon James (England), Varonis (US), Innovative Routines International (IRI), Informatica (US), Dataguise (US), Spirion (US), Digital Guardian (US), Titus (Canada), Netwrix Corporation (US), PKWARE (US), GTB Technologies (US), Forcepoint (US), Sienna Group (US), MinerEye (Israel), SoftWorks AI (US), Expert TechSource (India), Clearswift (UK), Seclore (US), and Janusnet (Australia). These players have adopted various growth strategies, such as partnerships, agreements, and collaborations; and new product launches, to further expand their presence in the global data classification market. Key players have adopted partnerships and new product launches strategies majorly from 2016 to 2018, which helped them to innovate on their offerings and broaden their customer base.

IBM is a leader in delivering efficient data classification solutions to various industry verticals. IBM’s solutions use Watson’s capability for various applications. The company is focusing on scaling its platforms, delivering productivity through automation, infusing AI into its offerings, and investing to expand its cloud infrastructure. The company uses organic and inorganic growth strategies to improve its market share and increase the annual revenue. As a part of its organic growth strategies, IBM introduced PowerAI, a deep learning software designed to address the challenges faced by data scientists and developers, in May 2017. It simplifies the development experience with tools and data preparation while reducing the time required for AI system training from weeks to hours.

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Google is also one of the leaders in the data classification space by providing solutions to the various industry verticals globally. The company relies heavily on its organic growth strategy and continuously aims for innovative next-gen products. The company is making significant Research and Development (R&D) investments in areas of strategic focus such as advertising, cloud, machine learning, and search, as well as in innovative products and services. The company is adopting an organic growth strategy to gain a competitive edge in the data classification market. For instance, in November 2018, Google updated its Data Loss Prevention (DLP) API, a tool helps users better understand and manage sensitive data. Google added new manipulation techniques in the tool, which include redaction, masking, and tokenization. The DLP API provides programmatic access to a powerful, sensitive data inspection, classification, and de-identification platform.

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