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Artificial intelligence and machine learning is a game-changer for data backup

 Manikandan Thangaraj
Manikandan Thangaraj • 4 min read
Artificial intelligence and machine learning is a game-changer for data backup
The rise of AI and ML in data backup has marked a turning point in the field of data resilience. Photo: Unsplash
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As businesses continue to generate more data than ever before, the importance of effective data backup and recovery strategies becomes increasingly critical. Over the past few years, the utilisation of artificial intelligence (AI) and machine learning (ML) has risen as influential instruments in this domain and has revolutionised how enterprises tackle data backup. The International Data Corp predicts AI investment in APAC, excluding Japan, to reach US$49 billion by 2026, with a compound annual growth rate (CAGR) of 24.5% from 2021 to 2026.

The expansion of the AI market within the data backup industry worldwide is propelled by the rising acceptance of cloud-centred backup remedies. These solutions harness AI and ML algorithms to mechanise and refine backup and recovery procedures. According to research, the Asia Pacific region is one of the most lucrative regions for the data and recovery market due to the steep data growth rates of modern workloads.

Traditional backup systems often rely on fixed schedules and predefined rules for data protection, which may not be optimal for ever-changing business environments. AI and ML algorithms, on the other hand, can dynamically adjust the backup frequency and prioritise critical data based on real-time usage patterns. This adaptability ensures that important information is backed up more frequently while reducing the load on the infrastructure during periods of low activity.

AI and ML technologies have made it possible to identify and eliminate duplicate data more effectively while optimising how data is compressed and stored. As a result, organisations can now store their data more efficiently, saving valuable storage space and reducing overall backup times. Redundant data is intelligently identified and stored more efficiently, reducing storage costs and improving overall backup performance. This level of data optimisation is especially beneficial for organizations with massive data sets, enabling them to save both time and money while ensuring the highest level of data protection.

One notable benefit of employing AI and ML in data backup is their capacity to proactively recognise and minimize potential risks of data loss, preempting their occurrence. Through the analysis of historical data patterns and the projection of forthcoming trends, these technologies can take a proactive approach in recognising susceptible areas and initiating preventive measures against data loss.

Furthermore, these technologies offer the advantage of automating mundane backup tasks, thereby freeing up IT personnel to concentrate on more strategic endeavours. AI and ML can also improve the speed and accuracy of data recovery, reducing downtime and minimising the impact of data loss on business operations.

See also: 80% of AI projects are projected to fail. Here's how it doesn't have to be this way

The Singapore government is driving a coordinated society-wide approach to deepening Singapore’s generative AI capabilities across the private and public sectors to advance Singapore’s position as an open and trusted global AI hub through the National AI Strategy. As a region, Singapore is working with other Asean nations to come up with a set of guidelines on the responsible use of artificial intelligence (AI) in the region, which will be released in early 2024. The Asean Guide on AI Governance and Ethics will serve as a practical and implementable step to support the trusted deployment of responsible and innovative AI technologies in the region.

The adoption of AI and ML in data backup is experiencing significant growth in the Southeast Asia region, and this trend brings promising prospects for businesses in the area. As industries across Southeast Asia continue to embrace digital transformation, there has been an exponential increase in data generation, making efficient data backup and recovery strategies more crucial than ever. Recognising the advantages of AI and ML in safeguarding their valuable information, businesses are eagerly adopting these technologies to optimise their backup processes.

In conclusion, the rise of AI and ML in data backup has marked a turning point in the field of data resilience. As businesses continue to navigate the challenges posed by increasing data volumes, these technologies provide a smarter, more automated, and adaptive approach to safeguarding critical information. Embracing AI- and ML-powered backup solutions can empower organisations to stay ahead in an ever-evolving data landscape, reinforcing their ability to recover swiftly from any data-related incidents and secure sustained success in their operations.

Manikandan Thangaraj is the vice president at ManageEngine

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