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Glossary Term

Cloud Data Management

Cloud data management empowers organizations to focus on managing data instead of infrastructure. A cloud data management platform is a powerful tool for businesses operating in cloud or hybrid environments, offering agility, scalability, and cost savings that streamline controlling and harnessing data’s full value.

What is Cloud Data Management?

Data management is the practices and methodologies organizations use to help them better leverage their data. Its main goal is to ensure that organizational data remains secure, private, and accessible, generating actionable insights for growth and sustainability.

Typical data management practices include:

  • Data collection that integrates multiple data sources in an organized manner, enabling an organization to derive its data’s value.
  • Data access strategies that enable enterprises to create, update, and access data across various data tiers, including archives.
  • Data storage policies that implement as many data storage types as needed, including private, public, and multi-clouds, as well as on-premise storage.
  • Data availability tools for backup and disaster and recovery (DAR) plans that ensure business continuity during a disaster or breach.
  • Data security and privacy procedures that continually enforce security and privacy policies.

Managing data in public cloud infrastructures such as AWS or Microsoft Azure provides automated back, professional support, and ease of access from any location without the need to manage physical data centers.

Principles of Cloud Data Management

Cloud-based data management’s fundamental principles include:

  1. Data Security and Privacy. The implementation of robust security measures and compliance practices to protect data.
  2. Scalability and Elasticity. System designs that can scale resources up or down based on demand.
  3. Data Governance and Quality. Established policies for managing data throughout its lifecycle to ensure its accuracy, consistency, and usability.
  4. Integration and Interoperability. Seamless integration with other systems and ease of data movement across platforms.
  5. Data Lifecycle Management. Data management from creation to deletion, including storage, archiving, and disposal according to policies.
  6. Compliance and Regulatory Adherence. Compliance with laws and regulations applying to data management practices.

By following these principles of cloud data management, organizations realize benefits that include:

  • Increased security. Over 90% of organizations adopting cloud data management report security improvements due to decreased risk of data loss from device damage or hardware failure. Cloud hosting and data management providers also tend to have more advanced security tools, measures, and practices than companies with on-premises equipment and software.
  • Scalability and savings. With cloud data management, companies can scale services up or down as needed to accommodate changing workloads.
  • Governed access. Improved security leads to greater peace of mind. End users can access the data they need from wherever they are, and in-house teams can easily collaborate, sharing insights and more.
  • Automated backups and disaster recovery. Cloud data management platforms manage and automate data backups, freeing organizations to focus on more strategic initiatives like new products and services and customer support improvements. They also speed up the disaster recovery process, mitigating ransomware attacks and other breaches.
  • Improved data quality. Well-governed cloud data management solutions help organizations eliminate data silos and create a “single source of truth” for every data point. Data remains consistent, accessible, and up-to-date for multiple use cases, including real-time data analytics, external sharing, and machine learning apps.
  • Automated updates. When cloud applications need updating, a cloud-based system runs the updates automatically, meaning people can continue their tasks uninterrupted.
  • Sustainability. Brands dedicated to decreasing their environmental impact can use cloud-based solutions to reduce their carbon footprints and offer remote work options to their teams.

Challenges in Cloud Data Management

Top challenges in cloud data management, particularly when using it with legacy tools or solutions, are:

  • It’s time-consuming. Manually configuring multiple solutions, including cloud gateways and media servers, requires substantial implementation time.
  • Limited scale. Patching together legacy products makes it difficult for IT teams to leverage the cloud’s ability to scale up and down.
  • It’s costly. Organizations are often surprised by the hidden costs of operating legacy products for the cloud, raising the total cost of ownership (TCO). Cloud data management simplifies the process, decreasing capital and operation costs.

While a well-structured data management plan saves organizations money over time, developing it requires an upfront investment covering data management software, the hiring of experienced data engineers to launch the solution, and the addition of IT operations teams to monitor data collection, use, and sharing.

Balancing initial and ongoing cloud expenses to achieve cost savings requires a well-crafted cloud data management strategy that considers immediate and long-term financial impacts, ensuring the investment supports current data management needs while scaling efficiently with an organization’s growth and evolving data governance requirements. Many companies achieve such a balance by spreading data across multi-cloud platforms.

Strategies for Effective Cloud Data Management

A strategic approach to cloud data management includes developing practices that optimize performance, ensure security, and manage costs effectively.

  • Adopting a multi-cloud approach by distributing workloads across different cloud providers enhances resilience and avoids vendor lock-in. It allows organizations to choose the services that are the best fit for their unique needs and ensures continuous availability, mitigating the risk of provider outages.
  • Data governance establishes clear policies for data access, quality, security, and compliance. It helps maintain data integrity and privacy across the cloud ecosystem, ensuring data consistency, reliability, and ethical use while maintaining regulatory compliance.
  • Cost management through careful resource allocation and monitoring helps companies avoid overspending on cloud solutions without compromising service quality.
  • Security measures like encryption, access controls, and security assessments protect sensitive information from breaches and unauthorized access.
  • Leveraging cloud-native services for data analytics and machine learning unlocks valuable insights and drives innovation. Designed to process and analyze vast amounts of data efficiently, organizations can use these tools and features to make informed decisions and stay competitive.Cloud data management is changing how organizations think about data, providing the versatility, security, and data management assistance they need to deliver healthy data, whether it lives on-premises or in a multi-cloud or hybrid cloud environment. AI-powered Velotix helps companies secure data in the cloud while aligning with industry best practices and keeping ahead of potential threats.