With 90% of enterprises planning to adopt some hybrid cloud strategy or the other, one thing is clear: Hybrid cloud is the business-friendly model for riskless digital transformations. But why are firms preferring hybrid cloud to any other cloud services model? The answer might be effective business data management.

Data regulations have become more complex and stringent than ever before. While storing data on a public cloud, there are some regulatory authorities that need businesses to store their sensitive organizational data such as users and customers’ Personally Identifiable Information (PII) on a private cloud. At the same time, if organizations wish to expand their operations in a different country, they need to comply with that particular country’s data regulations and laws. This is where the hybrid cloud comes to the rescue. IT managers can successfully keep sensitive, highly confidential data on a private cloud with advanced security and access controls. At the same time, they can deploy mission-critical workloads to a public cloud that require high availability and on-demand compute for frictionless functioning 24/7. With such a powerful feature, adopting a hybrid cloud data management approach is a safer bet as it equips organizations with benefits like agility, data protection, greater productivity, and cost-efficiency.

Now comes the important question: How can a company build a successful data management strategy on a hybrid cloud? This blog takes one through this entire data management process, listing the tools, benefits, and complications of the approach. Read along.

Drafting the 4 Tenets of a Successful Hybrid Cloud Data Management Approach

A scalable hybrid cloud data architecture is what every business needs to effortlessly develop new business applications and products. Here are 4 ways to do so:

Building a hybrid data warehouse

Generally, a hybrid data warehouse juxtaposes the scalability of the public clouds with the governance and security of the on-prem environment or private cloud. Meaning, the two cloud infrastructures are treated as a single data unit rather than two separate sources of data. While designing a hybrid cloud data architecture, organizations need to deploy correct hybrid cloud data management tools to automate data storage and process optimization across on-premises and cloud environments. One method can be to harness the potential of a data fabric tool. These tools are specifically built to synchronize data, workflows, and analytics across on-prem databases and cloud data warehouses.

Another approach can be to integrate a data automation tool. Simply put, these tools perform extract, transform, and load or ETL of raw data from multiple data systems and warehouses. Some examples of such hybrid cloud data management tools include Azure Data Factory, Oracle Autonomous Data Warehouse, and more.

A third option can be to implement a data warehouse tool that can work together across the on-premises and cloud data warehouses. The primary objective of a hybrid data warehouse should be to:

  • Lower data storage costs while maintaining uncompromised growth and performance.
  • Offer end-to-end data security and compliance with local and global regulatory standards.
  • Ensure continuous data flow and business continuity across both on-prem environments and clouds.

Leaning in On Data Federation

Data federation refers to the process of sourcing data from multiple sources (databases, data warehouses, and data lakes) into a single, virtual database. Since this decentralized database enables better data integration and analytics, companies get access to unique and powerful market insights and are removed from the burden of managing multiple databases. When running a federated database on a hybrid cloud model, businesses should adopt the Master Data Management (MDM) approach. MDM integrates critical data from different departments, entities, and databases into one common file called the master file which serves as a common point of reference for the organization. Here are a few things enterprises should keep in mind while undertaking this strategy:

  • Defining the master data is a must. Only then will the employees know which type of critical data should be shared across the enterprise.
  • Creating a strong hybrid cloud data governance framework is just the start. IT heads need to align this framework with their core data strategy and ensure it delivers the necessary outputs.
  • Identifying, selecting, and leveraging the right kind of hybrid cloud data management tools and technologies for data integration, management, and stewardship can ensure the effectiveness of the overall MDM approach.

The main objective of the MDM approach is to ensure data consistency and accuracy through a 360-degree view of data across different business units. MDM instills a culture of transparency and collaboration across various departments that helps to streamline business operations and dramatically reduce the chances of data redundancies and discrepancies. With a unified view, companies can garner high-quality, accurate, and real-time insights that motivate them to make reliable and forward-thinking business decisions. In addition, MDM ensures that all the data meets the required security, compliance, and regulatory standards.

By enabling federated or centralized databases, businesses can abstract back-end databases that offer thorough views into data such as Business View, Analytics view, etc. This helps decision-makers leverage data in different ways without having to modify any structure and causing application disruptions.

Fine-tuning Data Security and Compliance

While more and more organizations are opting for private clouds to keep their data safe, the growing necessity to ensure data security and compliance has compelled organizations to reimagine their data security techniques on their hybrid cloud. Here are 7 best practices that IT teams can rely on to toughen up data security in hybrid cloud environments.

Automating Security Measures

For a company’s hybrid cloud to be completely secure, it must enable process automation. This includes coding the infrastructure and keeping track of the security compliances of the hybrid cloud environment. In this way, organizations can keep a check on their databases and get updates on any potential real-time security threats.

Facilitating High-level Data Encryption

With data encryption, security issues like data leakages and unauthorized data access can be nipped in the bud. If the data is in transit or at rest, encrypting the data is a necessity. Based on the company’s security prerequisites, full-disk encryption, hardware encryption, and IPsec can keep the data secured in a hybrid infrastructure.

Managing Data Lifecycle

As and when the datasets are integrated into a common database, protocols like secure classification, compliance, and threat detection should be undertaken. To enable this process, companies need to automate the classification of their data across various sources and systems and ensure unified visibility through a robust monitoring platform.

Deploying Stringent Control Over Data Access Rights

There is some sensitive or exclusive data that is strictly meant to be accessed by special personnel. To exert control over who and who cannot access such data, companies need to carefully redefine their data access rights. Multi-factor authentication is one such method that enables the right person to access the right information and prevents unauthorized access. Read the MFA blog to know more about adopting the best practices for implementing MFA.

Securing Cloud and On-Premises Environment Securely

Just because organizations focus on securing their workloads on the private cloud, it doesn’t mean they should completely neglect their on-prem environments. While the hosted cloud comes with in-built security measures and tools like Identity Access Management (IAM), firewall management, and building security backups, IT teams should ensure that their on-prem environments are configured with the latest security controls.

Auditing the Security Policies

The hybrid cloud centers around the concept of shared responsibility. While the public cloud empowers organizations with scalable and agile environments, private clouds offer greater control over sensitive data. For these reasons only, regular auditing of security frameworks and policies can guarantee the complete security of the hybrid cloud environment. Note that different companies follow different security frameworks like NIST Cybersecurity Framework, ISO27001, and other industry standards. This makes it even more important for them to periodically audit these frameworks to ensure their relevance and effectiveness.

Encrypting Network Sessions

Last but not the least, enterprises should encrypt network sessions to secure their data in motion. Meaning, if the hybrid cloud environment relies on communicating via Internet Protocol (IP), the IT teams can use IP Security (IPSec) to make the communication more cryptic and discreet, ensuring complete protection of the IT environment.

Data Residency

Simply put, data residency refers to the geographical location of the data. While storing data in a different country, businesses need to comply with its specific data laws to meet the twin objectives of data security and privacy. Especially, when it involves cross-border data flows. Since data residency leverages the principle of data mapping, enterprises can get to know:

  • What data are they storing?
  • Their location
  • Specific data residency rules for that location

Hybrid cloud can help organizations in global compliance. With this model, key players can take advantage of its in-built geo-native services and location policies to ensure their data is compliant with the region’s relevant and evolving regulations and standards. This helps businesses expand and diversify their activities into different global markets, leverage new business opportunities, and gain the trust of new customers.

Solidifying Data Governance Frameworks

To facilitate an effective hybrid cloud data governance framework, organizations need to examine the present conditions of data quality and governance. Based on this, they need to highlight the scope, priorities, and objectives of developing a new data governance strategy.

In addition, IT leaders need to build a strong team or a council that consists of owners, stewards, and users with clearly defined roles and responsibilities. This team will help in creating hybrid cloud data governance policies considering the rules, guidelines, and prescribed standards for data quality and governance. Not to mention the usage of hybrid cloud data governance tools that comes with features such as data discovery, cataloging, quality monitoring, security, and integration to streamline cross-collaboration and efficiency. Finally, no data governance strategy is complete without the implementation of database activity monitoring solutions. These solutions will help in measuring the performance and impact of the company’s data governance initiatives and suggest changes, recommendations, and improvements.

Making Sense of the Pros and Cons of Hybrid Cloud Data Management

Hybrid cloud data management comes with its share of pros and cons. This section covers them in-depth.


Seamless Adoption

The best part about utilizing a hybrid cloud model is that companies don’t have to migrate all their data to the cloud. They can keep storing their sensitive data on their already existing on-premises systems. With a hybrid data architecture, organizations can diffuse data silos by collaborating across different departments.

Leveraging Partner Data

To ensure effective decision-making and better analytics, businesses tend to integrate internal data sources with external ones. A hybrid data warehouse is an ideal solution as it helps the data engineers to spend less time on identifying and creating new analytics models.

Need-based Data Segregation

While on-premises databases can be cost-effective, cloud data warehouses enable greater scalability. With a hybrid data management approach, businesses are equipped with the possibility of combining data sets from two environments. Based on their requirements and use cases and harness, they can harness the benefits of each model.


There’s no denying the obvious fact: Hybrid data warehouses are laborious to implement. But that’s not the only roadblock to this exercise. Hybrid data management can be:

Extravagant Maintenance

Usually, managing an on-premises environment makes businesses conscious of the resources and money they need to spend for its upkeep and maintenance. However, that’s not the case with a hybrid cloud infrastructure. Given its easily scalable computing and storage services and often complicated visibility, resource deployments tend to go off the rails, and cloud costs spiral way beyond the estimated budget.

An Unchartered Terrain

What we mean by this is that the employees take time to get acquainted with the hybrid cloud environment and the tools that come along with it. This is why, before even thinking of implementation, it is important to evaluate the tools and technologies that come in-built with the cloud and then craft proper learning and training programs, aligned with the overall goals of the organization.

Get Onboard with Hybrid Cloud Data Management with Cloud4C

A Gartner report points out that 85% of infrastructure strategies will combine on-premises, colocation, cloud, and edge delivery options in the next three years. Hybrid cloud data management solutions play a key role in unifying, gathering, and analyzing data spread across on-premises and cloud environments. This is why implementing the right architecture is critical to address the needs of the present and future. However, as we all know the toll it takes for an average business to adopt hybrid data architecture, choosing the right managed services partner can take away this major load and guide the organization through the process smoothly.

Cloud4C, one of the leading cloud managed service providers, offers next-generation hybrid cloud data management solutions and managed hybrid cloud services that propel organizations to unprecedented digital growth with a highly agile, zero-friction hybrid cloud data architecture. IT teams can effortlessly integrate multiple computing infra, storage, data center assets, servers, backend servers, and storage infrastructure on the hybrid cloud.

With the help of Cloud4C’s SHOP platform, organizations get a single source of truth into all their IT and cloud operations and solutions-apps with pro-active and preventive security management; applicable to any industry, any user IT environment of any cloud. Enterprises can overhaul their core with SHOP’s end-to-end cloud migration, modernization, and managed services till the application login layer.

If you are interested in revamping your data management strategy on a hybrid cloud or adopting hybrid cloud data management solutions and managed services, then get in touch with us today!

author img logo
Team Cloud4C
author img logo
Team Cloud4C

Related Posts

Hybrid vs Multicloud: Which strategy Suits you Best and Why? 21 Jun, 2024
Cloud computing is constantly evolving. Both hybrid and multicloud platforms have the means to…
Best Practices for Hybrid Cloud Automation: A Comprehensive Guide with Top 13 Use Cases 14 Jun, 2024
Table of Contents: What is Hybrid Cloud Automation? 8 Best Practices for Hybrid Cloud…
Powering Intelligent Transformations:  Top 8 Trends in Hybrid Cloud Architecture 14 Jun, 2024
“A pragmatic holistic approach to hybrid cloud can drive immense business value by initiating…