Jul 1, 2019
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Data Deduplication Market: Worldwide Industry Analysis and New Market Opportunities Explored

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Data deduplication is an advanced data compression technique used for reducing duplicate copies of the same data. Data deduplication is the process of identifying and eliminating identical information in a batch of stored data. Data deduplication solutions take a broader view to compare the same blocks or files across large storage data sets and remove redundant files. Network data deduplication is used to reduce the amount of bandwidth required to transfer data. This technique is used in an organization to reduce the amount of storage space utilized to save the same data. Data deduplication solutions allow enterprises to save storage and bandwidth cost. Further, data deduplication offers organizations benefits such as reducing hardware cost, increased storage capacity, and network efficiency.

Data deduplication is a trending technology used by organizations to reduce the need to store the same information file in a storage system. It plays an important role in primary storage by reducing the amount of data duplication. Companies operating in the data deduplication market are investing in advanced solutions. Demand for data deduplication solutions is increasing due to organizations’ need for reducing the redundancy of data in their primary storage.

There is a rise in demand for a platform to store data in every industry. Industries such as information & technology; banking, financial services & insurance; oil & gas; and government require data storage solutions. A significant rise in the amount of data and a rise in the need for managing, analyzing, and storing this data are driving the data dedupilcation market. Further, an increase in demand for cloud storage is expected to significantly boost demand for data deduplication in the near future. Increase in demand for innovative time saving technologies to handle the large amount of data generated by enterprises is also anticipated to propel the data deduplication market in the coming years.

However, lack of security in cloud- and server- based services is likely to restrain the data deduplication market during the forecast period. Challenges in data deduplication are numerous, owing to the technological complexity and consistency required in data storage. Development of data storage technology is another challenge for the data deduplication market. Nevertheless, demand for data deduplication solutions from small & medium enterprises is expected to provide an opportunity to the market. The data deduplication market can be segmented based on enterprise size, application, and region. In terms of enterprise size, the data deduplication market can be classified into large enterprises and small & medium enterprises. Based on application, the data deduplication market can be divided into banking and financial services (BFSI), entertainment, digital marketing, education, IT, telecom, government, and others.

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In terms of region, the data deduplication market can be segmented into North America, Europe, Asia Pacific, Middle East & Africa, and South America. North America is a dominant region of the data deduplication market. The market in Asian countries such as China, Japan, and India is expected to expand at a significant rate compared to that in other regions. This is due to the presence of a large number of IT companies in the region. Moreover, companies are investing in the cloud storage model for storing data. This requires the deployment of security solutions for the protection of data and solutions to reduce the redundancy of files. This is likely to propel demand for data deduplication solutions. In data deduplication market, vendors are expanding data deduplication offerings with advancements in solutions as per demand from end-users.

Some of the players offering data deduplication are Oracle Corporation, IBM Corporation, EMC Corporation, FalconStor Software, Quantum Corporation, Symantec Corporation, Hitachi Protection Platform, Sepaton, Dell Inc., and ExaGrid.

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