While all businesses operate in an uncertain environment to a certain degree, the level of uncertainty brought about by the Covid-19 pandemic was unprecedented. But despite the seismic shifts taking place in industries across the globe, many organizations quickly noticed the opportunities and formulated a clear cloud migration strategy for their organizations.
Data-driven organizations rely on analytics for business decision-making. However, standard analytics isn’t enough to guide an organization in extreme uncertainty during a pandemic. To cope, organizations quickly enhanced their analytics capabilities to better predict economic and behavioral shifts.
A modern data warehouse that is scalable, elastic, and powerful is needed for these advanced analytics. Backed by powerful cloud-native platforms like Snowflake and Amazon Redshift, organizations can build a data architecture that delivers high-speed analytics and BI to core decision-makers across their enterprise.
Prerequisites of an Optimal Cloud Migration Strategy
Insights from McKinsey revealed that Fortune 500 companies could unlock as much as $1 trillion in business value through cloud adoption. While most organizations are now mindful of the enormous value lying in cloud migration, actually implementing these initiatives is another matter.
Timelines for cloud migration have truncated substantially. Companies like Netflix took seven years to move to the cloud. With so much competition, enterprises now have to carry out this feat in a year.
Various strategies can be deployed to engineer these moves from wholesale rip-and-replace to hybrid data centers. Deciding on an approach and architecture that works best for your business, finding the expertise and technologies to support cloud computing, and finally coming up with an implementation plan that meets the needs of all stakeholders is easier said than done.
Let us look at the elements that should define an effective cloud migration strategy.
Elements of a Cloud Migration Plan
Determine Your Use Case for Data Warehouse Modernization
Determining the business case that warrants modernizing your data warehouse will be one of the first steps to consider as part of your cloud migration strategy. Once you’ve established your objectives for migration, aligning resources and timelines becomes a lot more straightforward.
Will it be used for real-time cloud analytics or disaster recovery? Will it be used to unify financial software across multiple systems or to transfer archival data to the cloud?
Regardless of the use case, it is critical to realize what the most efficient path to the cloud looks like. This includes identifying non-critical data, for example, email archives, which can move in the first phase. The requirements also include:
- Determining the level of the organization’s dependency on its data, for example, whether there is data that will need to be resynced
- Determining whether specific compliance requirements need to be met, for example, complying with HIPAA when moving patient medical history
- Identifying if the data needs to be cleaned first
Identify the Best Platform
Your cloud migration strategy should be able to address the vendor lock-in problem. The ability to lift and shift data and IT workloads freely is invaluable for businesses. However, cutthroat competition, regulatory restrictions, and proprietary technologies and software mean that extending some of the services offered by the existing cloud service provider to another cloud platform is not possible. Therefore, most enterprises are committed to a single service provider for long periods.
Hence, conducting thorough research before embracing a cloud platform is essential. Some best practices to safeguard your organization against the vendor lock-in problem are provided below.
- Identify all your business and technology requirements
- Identify the commonalities and complex dependencies
- Assess the cloud platform vendor market thoroughly
- The cost associated with migrating to a competing platform can quickly turn out to be the single biggest obstacle; ensure you have done your homework on this front
- Consider upgrading before migrating
- Ensure your choice of platform does not lead to interoperability issues between systems
Evaluate Associated Cost Requirements
While modernizing your data warehouse reduces costs in the long run, the process can require a substantial initial investment. Therefore, your cloud migration strategy must highlight potential avenues for cost optimization along the entire modernization process. Once the data warehouse modernization plan is in place and you have identified all the requirements, you should be able to make a reliable cloud migration cost projection.
The cost structure of a legacy data warehouse is different from that of a cloud data warehouse. The most important metric to consider when comparing costs associated with an on-premises data warehouse with costs associated with a cloud data warehouse is TCO (total cost of ownership).
Consider the following direct and indirect costs associated when migrating your data warehouse to the cloud:
- The cost associated with the volume of data/storage costs
For example, Snowflake charges separately for virtual warehouses, data storage, and cloud services. Typically, minimum monthly charges stand at $25, and storage charges are set at $40 per TB.
- Initial investment when migrating from a legacy data warehouse
Depending upon the current architecture and desired end-state, the initial investment can include costs associated with establishing new security standards, third-party migration platforms, and hiring and training additional staff. According to a study by Forrester, labor costs can make up as much as 50% of this investment.
- Consultation fees
While the right technology stack can mitigate roadblocks, it is necessary to have the right expertise on board to guide the migration journey. Consultants are hired to assess the organization’s overall preparedness for cloud migration and play an important role in strategizing and creating a solid roadmap.
Another essential cost associated with data warehouse modernization is the opportunity cost incurred whenever business operations are disrupted during the migration process.
As far as the cloud migration market is concerned, there are various cloud migration calculators to estimate costs based on realistic assumptions. Moreover, it is a good idea to coordinate with the cloud platform vendors to identify cost reduction opportunities, both during the migration process and once the cloud data warehouse is set up.
Ensure Good Data Governance Practices
One of the biggest business concerns regarding cloud data warehouse migration is security and compliance. Typically, cloud platforms operate on a shared operational model as far as responsibility is concerned, which means that the vendor is responsible for the security of the infrastructure. At the same time, the organization, or the customer, has to secure its data and workloads independently.
Furthermore, the data warehouse modernization process itself is risky when it comes to sensitive data. Although several cloud platform vendors provide state-of-the-art security controls backed by certifications, such as SOC 2, it is still the organization’s responsibility to ensure they are configured as per requirements.
It is worth highlighting that completing the modernization process does not mean businesses should take data security and compliance lightly. Instead, it is the responsibility of the businesses to ensure that they continue to comply with regulatory laws such as GDPR and HIPAA.
GDPR has several principles that keep every cloud service provider on its toes. For example, if a migration process results in data loss exposing someone’s personal information, the organization will find itself in hot water. This is not to say that cloud data warehouse migration tools and/or vendors aren’t well-suited to supporting governance and compliance. In fact, this is to emphasize that compliance with regulatory laws is a key part of your cloud migration strategy.
The Importance of Cloud Migration in Accelerating Data Warehouse Modernization Efforts
So far, we have talked about dealing with the prerequisites to formulate an efficient cloud migration strategy. Let us now see how a data warehouse strategy powered by automation plays its role in accelerating the data warehouse modernization process.
Leveraging an Automation-First Data Warehouse Modernization Strategy
As part of this strategy, emphasis is laid on data warehouse automation. Automation accelerates the entire process, whether dealing with a greenfield cloud data warehouse migration project or modernizing your existing legacy systems.
The modernization project essentially starts with tools that facilitate modernization by automating specific processes throughout the migration process. In this case, enterprises leverage end-to-end platforms to accelerate every aspect of their data warehouse modernization effort, from data ingestion to migrating to the cloud.
Improving Data Quality
It is crucial to understand that businesses should improve data and not just move it to the cloud; otherwise, unhealthy data brings problems to the new platform. The solution to this problem lies in automation. Automating the data cleansing process improves the data quality and ensures that only healthy data reaches the new platform.
Integrating On-Premises Systems
Connecting to existing legacy systems and applications and integrating them into the cloud is effortless with automation. Instead of having to custom code data pipelines for each source system, this is accomplished via built-in connectors offered by data warehouse modernization tools.
Preventing Vendor Lock-In
Modern automation tools are platform-agnostic, which means that they work equally well across different cloud environments. This capability protects businesses from the vendor lock-in problem since these modern tools allow them to modernize their data warehouses by deploying them on the platform of their choice without worrying about recoding data pipelines or losing critical data.
Supporting Different Cloud Migration Approaches
Automated cloud migration tools play a major role in different migration approaches. For example, automation allows you to either lift-and-shift (via infrastructure-as-a-service model), rip-and-replace (re-platforming), or employ a hybrid cloud architecture with some systems on-premises and some in the cloud.
Moreover, a migration process powered by automation is immune to human errors and protects from data loss and downtime. All of this leads to significantly reduced migration time, lower overall migration costs, and, most importantly, minimal disruption in business operations.
Lowering Costs and Empowering Data Users
Finally, modern data warehouse automation tools take away the need to code and provide an intuitive, point-and-click interface empowering the end-user to take charge of their BI initiatives. This offers guaranteed cost savings because a unified migration platform allows end-users to create a custom migration journey based on their current data architecture and future requirements without relying on technical teams and consultants.
The end result is a truly modern data warehouse architecture that is scalable and agile and delivers on the promise of advanced analytics.
Plan Your Cloud Migration Strategy with Astera
Astera is a no-code, automated data management platform that empowers businesses to seamlessly migrate their data to the cloud. The freedom of deploying the data warehouse to the platform of choice safeguards businesses against the vendor lock-in problem.
If you have decided to modernize your data warehouse by migrating your data to the cloud, you now know the prerequisites to account for to avoid common migration pitfalls.
Schedule a demo and take your business to the cloud with Astera today!