Insights for Unlocking the Value of Cloud-Based Data




Wissen Team


May 28, 2024

As investments into cloud systems grow, the volume of data in the cloud also increases at an exponential rate. Reports show that 60% of the globe's corporate data is stored in the cloud. An analysis further shows that the volume of data stored in the cloud is expected to exceed 200 zettabytes by 2025. The cloud-native applications market is also expanding at speed, with forecasts indicating a CAGR of 23.7% up until 2028.

As the volume of data in the cloud increases, how this data is stored, secured, managed, and governed across cloud platforms determines how well this data can deliver value to the organization.

What Is Cloud Data Management?

As the cloud and now cloud-native application ecosystem expands across enterprises, the role of cloud-native data management increases in importance. Strong cloud-native data management practices ensure the effective and efficient management of the entire data pipeline, which includes data integration, data quality, and metadata management so that data transforms into information and information into insight easily.

Cloud data management manages all the data that is stored in the cloud or across multiple clouds or on-premise using cloud-based solutions. Such a solution helps enterprises with disaster recovery and backup, file and object services, data archiving, data analytics, etc. However, unlike on-premise solutions, cloud data management takes advantage of underlying cloud services such as cloud storage. These solutions are also designed to address specific concerns around data security and data integrity and other such enterprise requirements.

The Need for Cloud Data Management

Since data is the lifeblood of businesses today, effective data management becomes the key to ensuring that this data delivers value. However, there are several challenges in managing this data effectively in the absence of a robust cloud data management solution. The key ones emerge from:

  • The proliferation of secondary data across a host of locations, infrastructure silos, and management systems
  • The increasing complexity of hybrid cloud infrastructures, which makes it hard to control and harness the complete value of data with legacy tools
  • Complex operations owing to data silos and less granular control, especially in a hybrid environment

Cloud-native data management eliminates data silos, simplifies operations, and provides a centralized point to manage a hybrid environment to generate greater value and provide more granular control to enterprises. It becomes crucial for forward-thinking organizations operating in a cloud or hybrid environment.

Robust cloud-native data management capabilities are also becoming critical because the cloud-native application portfolio and containerized application ecosystem are expanding. In these applications, microservices use multiple data services and storage technologies. Hypervisor or legacy-based solutions do not work for these environments and need cloud-native data management for deep and clear insights and to get full value from the data.

Besides, robust data management practices become imperative as stringent regulations like PCI DDS and GDPR compliance become more stringent and demand greater data security, transparency, and traceability.

Challenges with Cloud-Data Management

While cloud data management is essential, it is imperative to look at some of the challenges that organizations encounter.

  • Clear visibility into the data assets residing in the cloud is one of the most common challenges faced by IT teams. This mainly transpires during the lift-and-shift phase of cloud migration. Along with assets and databases that move to the cloud exist some dark data systems in the form of unmanaged devices etc., which can create security vulnerabilities.
  • Lack of visibility into the sensitive data and losing sight of business-critical sensitive data can lead to cybersecurity breaches, insider threats, or regulatory fines because of non-compliance.
  • Adherence to data privacy laws demand proper storage and management of personal and sensitive personal data for prolonged periods. This increases storage expenses and can also invite regulatory fines when not done adequately. Robust access management controls also become imperative to ensure security and prevent unauthorized access or data leaks.
  • The absence of the right strategies to control the growing volume of data stored in data lakes and data warehouses increases cloud costs and leads to unnecessary expenses.
  • Cloud data management processes also need to be scalable to meet the growing regulatory and compliance obligations. Setting the right controls to establish robust governance, as such, become non-negotiable but need domain knowledge along with technical expertise.

One of the biggest challenges that enterprises encounter in their cloud-native data management journey is to navigate the limited scale of legacy products in their application portfolio. Identifying cloud readiness and modernization opportunities for these products and creating a scalable cloud-native data management solution can pose a challenge.

This is especially the case for industries such as banking and healthcare, which are heavily regulated and also have legacy systems managing business-critical workloads and processes.

Unlocking the Value of Cloud-Native Data Management

The main benefits of robust cloud-based data management come in the form of increased agility, greater scalability, improved planning and forecasting, cost savings, and complete visibility of all the cloud data and how much it costs.

Along with this, enterprises also gain greater clarity on how to increase efficiency and capably consolidate a plethora of use cases that include disaster recovery, backup, air-gap security and ransomware recovery, development and testing, analytics, etc., while also removing the complexity of managing multiple data silos.

To unlock the true value offered by cloud-native data management, enterprises need a robust cloud-native data management strategy to manage all the data that lies fragmented across multiple clouds as well as local data storage. To get to this point, enterprises must:

  • Take a cloud readiness test assessment to evaluate their level of cloud maturity.
  • Create a cloud migration roadmap that identifies the best possible route to make the cloud move.
  • Create a security roadmap to maintain operational security and data integrity.
  • Unify backup data across hybrid and multi-cloud.
  • Curate data feeds to analytics or data warehouse apps for more visibility.
  • Enable tiering, archival, and replication between public and private clouds.
  • Build scalability and responsiveness into the data management platform for automatic response to spikes in usage and auto-scaling based on utilization.

Winning with Cloud-Native Data Management

Cloud-native data management employs cutting-edge technologies and services to deliver high business agility and allow enterprises to easily onboard diverse data sources from multiple systems and efficiently handle both analytical as well as operational use cases.

Given the complexities at work, how you manage and deploy cloud data management plays a pivotal role in determining successful outcomes. So, it's critical to ensure:

  • Effective data engineering capabilities for effective design, testing, and monitoring of data and knowledge of modern data engineering tools and services
  • Expertise in designing strategies for seamless cloud migration

Apart from this, domain expertise becomes a critical selection criterion, especially for heavily regulated industries. This expertise provides insights and best practices to engineer cloud-native data management platforms that optimize performance, increase organizational agility and responsiveness, and elevate business outcomes by accelerating innovation. At Wissen, we help enterprises make the most of their cloud initiatives. Get in touch with us to learn more.