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Cloud Data Management and its Importance in 2023

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Cloud data management is the basic implementation of data management tools, policies and systems that allow organizations to take control of their business data in the cloud and in places where data is stored or collected in a mix of on-premises and cloud applications. After the pandemic changed how the world operates, organizations realise the value of migrating the world load to a cloud. With the agility demonstrated by the cloud to optimise new products and services, the need for cloud-centric data management has been felt more than ever.

In this blog, we enlighten our readers on cloud database management, its growing importance, and the various developments in this domain to look out for in 2023.

Why Cloud Database Management System:

With organizations reworking their data architecture strategy for changing business requirements, a cloud database is their primary consideration. We list the capabilities of cloud database management systems that will highlight their importance.

Integration: With a cloud database, organizations can drive innovation, increase their efficiency, and redefine business. These advantages are only possible when the cloud architecture permits integration and synchronization of all data, applications, and processes in a multi-cloud environment. The use cases for using cloud databases may vary on business requirements, for example, if businesses are aiming for fast-running automated business processes that span across applications, they can integrate applications with orchestration and APIs to keep data synchronized.

Quality and Governance: With data being the heart of business processes, the most successful running business understands the significance of high-quality data for its data transformation strategy. Research has shown that companies that encourage their employees to use data for decision-making are more likely to reach data and analytics objectives. With strict regulations on quality, organizations must ensure that employees are able to conveniently locate, access and use the data. With automated cloud-based data, governance and quality are ensured and clean, and high-quality data is provided for businesses and IT to optimise their business potential.

Privacy and Security: With an increase in the transition to cloud databases, data, in general, is prone to attacks and abuse. Hence, protecting data, allowing for safe access, and enforcing compliance with regulations are necessary to reduce the risk of security breaches and corporate abuse. With the assurance of privacy, data can be used safely, and cloud workload migration quickly comes into effect which finally helps build customer trust. With cloud protection and privacy, users can:

  • Completely make the discovery and classification of sensitive data automated.
  • Help map clear ownership of identity and supports data access regulations.
  • Make privacy policies operational.
  • Analyse data risk exposure across various data locations.

Data Management: With a large volume of data generated across businesses, organizations need a complete view of the domain and data in the cloud. With hype for intelligent data stewardship and data visualization, there comes data management in the picture. Here, cloud master data management can synchronize the critical data across various organizations in a single and well-validated record, hence enabling the analytics team to derive deep insights that provide value to businesses.

Metadata Management and Data Cataloguing: With a combination of technical, business andoperational data and metadata, cataloguing helps build a strong data foundation that helps modernise the cloud, increase data governance and engage in other business priorities. An extensive enterprise data catalogue is made using machine learning-based data that scan and catalogue for analysts, data scientists and IT users with systematic search, data lineage, statistics profiling, data quality scorecards and much more.

AI-Driven Intelligence: With modern and improved cloud data management using AI, users can:

  • Helps automatically discover and catalogue data across various systems.
  • Automatically discover the connections between customer data to provide insight for specific people.
  • Automate data integration with quality tasks, policy management etc.

Benefits of Cloud Database Management:

 As organizations are becoming increasingly cloud-centred, and new data is coming every passing day, the correct tools are needed to handle the data. When we talk about data management in the cloud, it is an end-to-end process from data creation to data retirement. With management, there is a linear progression of data through each stage of its lifecycle. This helps reduce the risk of getting into regulation non-compliance.

With cloud database management, these benefits can be realised:

  • Improved integration and ingestion with enhanced analytics.
  • Increased data security and data governance.
  • Enhanced metadata management with rapid data discovery.
  • Optimum record management and maintenance.

Future of Cloud Database Management:

With the increasing maturity of cloud data management, the future of cloud computing looks promising and holds importance for organizations in their decision-making process. However, a few points need to be kept in mind with the increasing reliance on Cloud Data Management are:

  • Improvement of AI and Machine Learning efficiency.
  • Assistance with service models and key performance indicators.
  • Integration and data exchange between internal and external applications.
  • Improvement in cloud computing.

Trends to look out for in 2023:

Organizations are becoming more aware of the necessity to become decentralized, and they are prioritizing applications that make collaboration easier and an increased number of people can work at the same time. With the new year upon us, let’s look at the trends in the cloud data management domain that are taking over the industry.

  • Data mesh and data fabric.
  • AI driven DQ.
  • Modern data stack.
  • Data and analytics governance platforms.
  • Cloud native technologies.
  • Automation.

Author

Shinjini Sarkar , Senior Content Specialist