If you’re looking to support digital transformation, futureproof your business with the latest technology and infrastructure, and leverage advanced analytics and artificial intelligence, then migrating your traditional databases to Google Cloud should be a consideration.
Not only will you transition to a consumption pricing model, you can turn your databases into cloud-based powerhouses, with benefits such as improved performance, scalability, agility, and speed. Integration with advanced AI tools can also serve to create a foundation for innovation.
But the march of technology is also driving the need for database modernization. For example, by 2025, embedded AI functionality will be included in at least 90% of new enterprise application releases. And by 2026, four in five (82%) of organizations want to ensure all capabilities supporting the AI workflow are tightly integrated in their cloud data platform.
Common data migration challenges
While migrating to the cloud offers new opportunities, it comes with its share of challenges, such as exceeding timelines and budgets—and many projects fail.
Historically, most data migration projects have had significant data quality problems in new systems. That’s because a major challenge in migrating traditional databases is data complexity—due, in part, to the sheer volume and complexity of data (structured, semi-structured and unstructured), which might be housed in different formats in disparate databases.
If existing data formats aren’t compatible with the cloud, there’s a risk of data loss or corrupted files. And if there isn’t a clear migration path for that data, it may not transfer over properly; it could also lead to inaccurate or incomplete data. There’s also the issue of migrating data sets that don’t actually need to be migrated, which ends up slowing down the testing phase and adds extra cost into the process. Data security is another concern, and if data isn’t safeguarded during the migration process, it could be exposed to security threats or compliance infractions.
A step-by-step approach to migration
Before migrating traditional databases to the cloud, it’s important to have a migration strategy in place that can help you overcome these common challenges. That strategy should also consider budget, timelines, and testing, and whether you’ll work with a partner.
In the Google Cloud ecosystem, there are several free migration tools that address many of these challenges. For example, Database Migration Service (DMS) is a fully managed service that automates migration tasks such as data replication, validation, and synchronization without requiring significant downtime. By providing continuous data replication, it can accelerate the migration process while reducing the risk of data loss or corruption. Plus, it supports various database types including MySQL, PostgreSQL, and SQL Server.
Here are a few considerations for a migration strategy:
Thorough planning and assessment: Conduct a detailed assessment of the traditional database and plan the migration process step-by-step.
Take advantage of automated tools and services: Leverage Google Cloud’s migration tools to benefit from automation in reducing errors and speeding up the migration process.
Take an incremental migration approach: Adopt a phased migration strategy to minimize downtime and disruption.
Ensure data security and compliance: Implement robust security measures and ensure compliance throughout the migration process.
Partner with experts: By working with experienced partners like Pythian, you’ll have access to specialized knowledge and resources to ease the migration process.
Wayfair’s successful migration to Google Cloud
With 18 fulfillment centers, 20,000 global suppliers, and a catalog of more than 30 million items, Wayfair—a global eCommerce giant—was in need of a transformation to remain agile. The company had thousands of applications built in a monolithic architecture, which prevented it from being able to rapidly deploy new features to customers and suppliers.
Pythian helped the global eCommerce giant migrate its monolith database to Google Cloud, so Wayfair can now release new features to customers and suppliers in a day—a process that used to take years. The company is also saving millions of dollars, increasing developer velocity, and making better use of data to improve the customer experience.
Read the full success story >>
Why Pythian?
Another challenge many organizations face is a lack of in-house expertise or resources. While automated tools can help, transitioning from complex, traditional infrastructure to the cloud requires specialized skills to complete projects on time and on budget. That’s where a partner can help.
Our team has migrated hundreds of critical workloads to, from, and within public, private, hybrid, and multi-cloud environments. We’re also a Google Cloud Partner with 200-plus Google Cloud certifications and 25+ years of experience in consulting, databases, DevOps, and analytics.
Our roadmap assessment services include an analysis of your current estate to determine the technical difficulty of the migration, the creation of a migration roadmap (which includes future state architecture, risk, timelines, and estimated cloud consumption costs), and recommendations for next steps. Plus, we can help you continuously optimize your environment.
Ready to take the first steps towards turning traditional databases into cloud masterpieces with Google Cloud? Get started today by taking part in a free workshop to learn more.
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