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How Companies Can Master Data Management With DaaS 

How Companies Can Master Data Management With DaaS 

SUMMARY

India's DaaS market is set to grow at a CAGR of 10% in the next five years, making data management a game-changer for businesses integrating technology and upgrading infrastructure

The adoption of AI and ML in the DaaS segment is on the rise, enabling more efficient data management processes and insights for businesses

Hybrid cloud models and increased emphasis on data privacy are driving the growth of DaaS, offering seamless data management across various environments and ensuring secure and transparent data sharing

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As cloud computing takes centre stage for businesses across industry verticals, data has become one of the most valuable resources globally. With more organisations integrating technology into their operations and upgrading their infrastructure, Data-as-a-Service (DaaS) is a concept that has gained significant traction. 

India’s DaaS market is on track to grow at a compound annual growth rate (CAGR) of 10% over the next five years, so it’s essential to know what this service entails and how data management can be a game-changer. 

What Exactly Is DaaS?

DaaS has become one of the most sought-after solutions for data integration, management, storage and analytics. In the simplest terms, DaaS is a data management strategy that leverages the cloud to deliver data storage, integration, cleansing, processing, enrichment and analytics services through a network connection. Similar to SaaS (Software-as-a-Service), DaaS outsources most of these functions to the cloud.

Users can access data through cloud-based applications over the network rather than storing it on-site. As a result, DaaS is a seamless solution for organisations to easily analyse large amounts of data without investing heavily in hardware or software. 

 What can we expect to see in the DaaS segment in the coming months?

Greater Adoption Of AI And ML In DaaS

Artificial intelligence (AI) and machine learning (ML) have infiltrated nearly every business function to facilitate seamlessness, convenience, and cost optimisation, making them some of the most popular technologies among businesses. With the increasing integration of AI and ML in the DaaS segment, companies can drive insights and automate data management processes more efficiently.

Data management has become crucial for most companies, especially given the large volumes of data generated every day. However, manual data management is inherently tedious and inefficient. It is labour-intensive and involves ingestion, cleaning, extraction, tagging and manipulation. AI helps overcome these challenges by streamlining the cataloguing, cleaning and classifying of processes, making data management more efficient, secure, and resource-optimised.

AI In Edge Computing Brings Data Processing Closer To The Source

Integrating AI into devices is on the rise. AI computation is done at the very edge of the network, closer to where the data is, rather than in a centralised cloud computing scenario. Such an environment ensures that AI is close to its end users and can solve real-world problems efficiently. 

Deploying AI in edge computing is possible in a number of industries, including manufacturing, hospital management, retail, and even street traffic management. 

The Rise Of Hybrid Cloud Models

Hybrid cloud models enable seamless data management across various cloud and on-site environments. 

For example, a hybrid data warehouse can enable data teams to combine third-party data with internal data sources to gain in-depth insights for informed decision-making. Data backup and recovery options are plentiful in a hybrid model, making it a plausible option for companies.

Increased Adoption Of Daas And The Significance Of Data Privacy

The demand for real-time data processing and analytics in DaaS is growing quickly. There is also greater adoption of DaaS in various industries (such as healthcare, finance, and retail) as more organisations leverage data insights for enhanced customer experiences and operational efficiency.

We are witnessing the emergence of new DaaS delivery models, including serverless computing, to simplify user data management, making it a frictionless process. With businesses increasingly understanding the significance of data privacy and security, blockchain-based DaaS is also becoming more popular, allowing companies to provide secure and transparent data sharing.

The Bottom Line

DaaS offers numerous benefits, from easier setup, use-to-cost optimisation and operational efficiency. Organisations that understand the significance and benefits of DaaS can gain an edge over their peers in the market and grow their businesses sustainably. A DaaS strategy saves time, money, and resources, making it the ideal option for organisations. 

It is the future, and it’s already here.

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