Cloud is the future for every business as it streamlines internal processes and optimizes resources while ensuring control and quality. Here, we’ll discuss the hybrid and multi-cloud strategies technical or IT executives should adopt to implement Azure data engineering in their enterprises.
A growing business requires a robust IT infrastructure that is flexible, scalable, and secure. While on-premises solutions are effective, cloud-based software, platforms, and infrastructure can offer more diverse results and better performance. That said, it is vital to choose the right cloud strategy for your business. That’s why many organizations are shifting to hybrid cloud or multi-cloud solutions, which enable them to strengthen their IT infrastructure and leverage advanced technology to unlock the full potential of data, making data-driven decisions in real-time.
Statistics show that by 2025, 94% of businesses will utilize a cloud service in some form, and the global cloud market is projected to reach $732 billion by the end of the year. AWS and Azure are the top two cloud providers with a combined market share of over 50%.
From startups and small businesses to large enterprises and multinational organizations, every business can benefit by following the cloud-first approach. However, this requires clear objectives and a comprehensive strategy, which is why most organizations partner with third-party offshore service providers to streamline cloud-based data engineering and maintain the systems in the long term.
In this blog, we’ll first look at what hybrid and multi-cloud platforms are and discuss the strategies executives should adopt to implement Azure data engineering in their businesses.
Hybrid and Multi-Cloud Platforms
A hybrid cloud setup is a combination of cloud and on-premises infrastructure. The on-premises infrastructure is private and likely hosts the legacy systems belonging to the business. The cloud is a public service, offering SaaS (Software as a Service) or PaaS (Platform as a Service) solutions, which are integrated with the software/ systems on-premises. This combination ensures that important data is safeguarded internally while eliminating extra overhead costs by relying on public cloud platforms. A hybrid cloud strategy for Azure helps revamp the existing combination to automate recurring tasks, increase data security, and optimize resources for greater ROI.
A multi-cloud setup is a combination of two or more cloud platforms belonging to different vendors. For example, a business may run its IT infrastructure on AWS, Azure, and Google Cloud, with the systems distributed across all three and connected through third-party integrations. This also helps in cost optimization and prevents vendor lock-in. Multi-cloud data integration also allows you to select the exact tools and technologies required for your operations and increase overall efficiency.
Azure data engineering solutions can be implemented on hybrid and multi-cloud systems, based on your specifications, objectives, and budget. The right strategies maximize flexibility, scalability, performance, and cost-effectiveness. However, this shift also comes with certain challenges, which can be overcome with expert support and guidance from experienced data engineering consulting companies. When you hire a certified Microsoft partner, you have access to their expertise, new perspectives, and the extensive ecosystems offered by the cloud provider.
Hybrid & Multi-Cloud Strategies for Azure Data Engineering
Clearly Define the Goals and Objectives
The most important part of any strategy is to know why you want to make the changes or adopt something new. If you want to set up multi-cloud or hybrid cloud AI analytics, first define your goals and objectives. What do you wish to achieve by migrating the IT infrastructure or certain processes to a cloud platform? How will it affect different departments, teams, etc., across the business? What kind of data security measures do you already have, and what additions should be made? By when do you want to see the results of these changes? What ROI do you expect? Top-level executives should also involve middle managers, team leaders, etc., in the discussions to get a realistic picture and understand the practical limitations.
Select Service Providers and Vendors
With many cloud vendors and several service providers to offer end-to-end or consulting solutions, you should take time to select the right partners for your business. For example, the extent of vendor flexibility for cloud services determines whether you can rely on the cloud platform in the long term and if the costs will align with your budget. When selecting a service provider, factors such as experience, industry expertise, certification, project portfolio, pricing, transparency, communication, agreement terms, etc., should be considered. For example, you can hire a data warehousing company with certified partnerships with leading cloud providers like Azure, AWS, Google Cloud, as well as with data security certifications.
Establish KPIs for Hybrid and Multi-Cloud Adoption
It is equally important to determine the metrics for measuring the progress and effectiveness of hybrid and multi-cloud systems. Set three or four KPIs and make them time-bound. This helps in defining success and also highlights areas for change or improvement. Additionally, the KPIs, business objectives, and services should be aligned to get the desired results. For example, if optimizing costs is a top objective, the KPI could be measuring infrastructure utilization. A clear increase in the latter would indicate that the objective is being achieved.
Build a Unified Data Architecture
Azure data engineering gives the best results when there is a unified data architecture with a central repository with the entire business data in a single location. This eliminates data silos and outdated datasets scattered in the enterprise and allows all departments to access the latest and updated information from a centralized location. Data estate unification also simplifies security and governance measures by making it easier to provide authorized access to employees based on their job requirements, titles, etc.
Leverage Cloud-Native Tools
Cloud vendors, especially the top ones like Azure, offer several cloud-native tools, features, apps, frameworks, APIs, etc., to integrate with the data architecture and build robust systems to derive data-driven insights in real-time. The tools help with automation, simplification, optimization, monitoring, scaling, and much more. For example, cloud modernization with Fabric is easier when you work with the tools available in the Azure ecosystem, as both platforms belong to the same vendor, Microsoft. Such aspects are handled by the data engineering company so that you can focus on your core functions and accelerate growth by utilizing these revamped systems.
Prioritize Data Security and Backup
Cloud security is crucial for every business, even if you use a private cloud to run your software applications. Hybrid and multi-cloud infrastructures require multiple security layers to protect data and processes at all stages. From data collection to data visualization, every phase has to be secured to prevent unauthorized access to sensitive data. Data encryption, multi-factor authentication, restricted access, etc., are some ways to achieve this. Additionally, you can use the cloud-native tools to enhance the security of the data architecture. Furthermore, data backup and disaster recovery processes should be implemented to ensure the business data cannot be lost, corrupted, or stolen due to different reasons.
Data Compliance and Governance Framework
Data governance is a collection of processes, policies, roles, metrics, etc., to enable your business to unlock the full potential of its data assets. Data compliance is where you have proper documentation and a framework in place to ensure your data, insights, and processes adhere to the industry standards, regulatory laws, etc. Together, these make sure that your business follows all the rules and reduces the risk of lawsuits or legal complications due to mismanagement or other reasons. That’s why many organizations partner with offshore service providers to take care of these issues and eliminate the risks of unforeseen challenges.
Monitor and Optimize Processes
No strategy is complete without built-in monitoring or tracking systems. That’s because it is vital to evaluate the new processes to make the necessary changes and to measure if it is aligned with your business vision and objectives. Azure data engineers can automate monitoring and set up customized dashboards to share the insights with the executives in real-time. Similarly, optimizing the architecture, resources, tools, etc., will enable you to reduce unwanted costs, free up cloud storage space, and increase the efficiency of the currently running operations. Monitoring and optimization are not one-time solutions but should be continuously implemented. This results in greater transparency and makes the infrastructure more flexible, agile, effective, and sustainable in the long run.
Conclusion
In our ever-changing markets, businesses should stay one step ahead of others by adopting new technologies and implementing powerful solutions. This involves cloud computing solutions to reduce the pressure on on-premises systems and create greater flexibility.
With Azure data engineering consulting services from reputable companies, you can build a hybrid or multi-cloud setup to host the data architecture and deliver real-time insights throughout the enterprise. Achieve success by creating and implementing a powerful data strategy. Accelerate growth and enhance customer experience with proactive decisions.
FAQs
Why should I consider a hybrid or multi-cloud approach for my data strategy?
You should consider a hybrid or multi-cloud approach for your data strategy to build and implement a robust, resilient, flexible, scalable, and efficient data architecture to derive actionable insights in real-time. You will also have more control over the processes while automating time-consuming tasks. Hire tailored Azure data engineering services from DataToBiz to ensure seamless cloud strategies and implementation in your organization.
How does Azure data engineering support compliance in multi-cloud environments?
Azure data engineering supports compliance in multi-cloud environments through tools like Microsoft Purview Compliance Manager and Microsoft Defender for Cloud. Azure Policy ensures standardized regulations are enforced in the business, which allows you to adhere to various data laws. Azure Arc helps in reinforcing the same regulations across other cloud platforms and on-premises systems. Talk to certified Azure experts at DataToBiz for more information.
What are the cost benefits of adopting hybrid cloud strategies in data engineering?
Hybrid cloud strategies offer cost benefits in data engineering through the following ways:
- Alternating between variable workloads and predictive workloads for resource optimization
- Reducing the capital and overhead costs of upgrading and maintaining on-premises infrastructure
- Leveraging pay-as-you-go pricing, enabling you to pay only for the services you use
At DataToBiz, we provide end-to-end Azure data engineering services with long-term maintenance and support services to increase your ROI.
Can Azure integrate seamlessly with other cloud providers in a multi-cloud setup?
Yes, Azure data engineering can be a seamless process as the cloud platform and its solutions can be integrated with numerous third-party tools and technologies. Azure has cross-cloud connectivity, Azure Arc service, networking capabilities, and interoperability through diverse APIs, making it easy to integrate with most cloud providers and their offerings. The DataToBiz team can help you with the process from end to end and build a robust multi-cloud setup.
How do hybrid and multi-cloud strategies reduce vendor lock-in for enterprises?
Hybrid and multi-cloud strategies reduce vendor lock-in by allowing you to distribute the workload across more than one platform. You don’t have to depend on a single vendor or its capabilities to run the business. This gives you more freedom and control over the operations. DataToBiz provides customized AWS and Azure data engineering services to help enterprises leverage competitive pricing, ensure business continuity, and reduce redundancy.
What governance and security measures are critical in a multi-cloud data environment?
Whether it is an Azure data engineering setup or a multi-cloud data environment, the following governance and security measures are critical and should be implemented in every business:
- Centralized visibility
- Automated security and compliance
- Data encryption (when at rest and in transit)
- Identify and access management
- Data backup and disaster recovery
Talk to DataToBiz to know more about crucial security and governance measures to implement in your business.
More in Data Engineering Consulting Services Providers
Data engineering services and end-to-end solutions dealing with data collection, cleaning, transformation, storage, analytics, and visualization. The services are tailored to align with the industry requirements and business objectives to unlock the full potential of large datasets in the establishment and derive meaningful insights for data-driven decision-making. Cloud-based services, such as AWS and Azure data engineering, automate various processes and increase overall efficiency while reducing costs.
Read the following links for more information about how data engineering gives your organization a competitive edge.
Top 12 Azure Data Engineering Companies Driving Innovation in Finance
Building a Scalable Data Infrastructure – CTOs Handbook!
10 Ways Data Lake Consulting Can Save You From a Costly Overhaul
7 Innovative Firms Aiding Data Pipeline Automation in 2025
Fact checked by –
Akansha Rani ~ Content Management Executive
