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.
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.
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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.
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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