Embracing Complexity: Data Migration on AWS

October 17, 2023

Organizations are continually deploying new data solutions. They’re moving enterprise resource planning (ERP) systems, reporting, data analytics, and other functions and processes to the cloud. Having a well-defined data migration and data conversion strategy from the outset is a must. However, it can be difficult to know what issues to anticipate and how to put all the pieces together to build that strategy.

Embracing Complexity

Data migration can be complex, but taking stock of the challenges before migration is the best way to recognize complexities as opportunities. First, organizations today have information coming from every direction – email, databases, APIs, and other sources. A data migration strategy needs to take account of the number and variety of different data streams, as well as the rising velocity of data flows. Organizations used to process data once per day. That’s ancient history as today’s norm inches toward continuous, real-time streaming data.

Another complexity to consider at the outset is the variety of end users for data. Data analytics are not reserved for the C-suite anymore. We’ve reached the age of data democratization, where everyone in an organization needs access to data of different types and has different purposes and goals in mind. Organizations need to make data available, in more ways, to more kinds of users – from analysts to people in the field. That takes planning.

Recognizing Data Migration Risks

Organizations and their data migration partners need to take stock of an organization’s database and analytics workloads before they start. For this, data mapping is essential. This includes data profiling, understanding data quality, creating metadata, and re-engineering the data lineage.

The best migration strategies work to eliminate or minimize disruptions so users can continue to access application functions during the migration process. Identify any potential hindrances or obstacles users might encounter as the “live” system is migrated to rule out or lessen downtime.

Another key requirement is a test strategy for data migration. Pre-migration testing will help ensure that all new and upgraded applications are compatible with legacy hardware and software. Any new hardware and software platforms should also be verified in advance for compatibility. The compatibility between the servers and software components should be tested to ensure data flow remains intact during migration. The new application and all existing functionalities should work just as they did in the legacy system. The system response time should be the same or faster than it was with the legacy application.

Despite extensive pre-planning, migration can still result in data defects or corruption. Testing needs to be done throughout to identify and fix those issues.

The Art of the Possible with AWS Services

When Adastra begins a data migration project, we hold a series of initial workshops to introduce the customer to various data migration options, so they know what’s involved and understand how the technology functions. Data migration is much more than architecture. We want our customers to dream big and know what’s possible. We build better solutions when we put our heads together.

As an AWS partner, we’re well-versed in AWS tools and services for data migration and data models that are future-proofed for changes and for growth. Instead of creating very specific solutions that only work for a specific workload, it’s more useful to create a modular solution that can migrate other types of data. This is something we always do when we migrate workloads from on-premises to the cloud.

AWS offers a wide variety of purpose-based services for a range of solutions. If you need a data warehousing solution, there’s Amazon Redshift. If you need to set up a relational database, there’s Amazon RDS. If you want to create a database for e-commerce, you can use Amazon DynamoDB. There are 200+ specialized services that address specific use cases. Much like kids’ building blocks, they’re easily integrated, talk to each other, and require no coding. Many can be easily operated by setting and adjusting parameters.

The following are some of the key AWS tools that help customers migrate their data quickly, efficiently securely, and with minimal downtime.

AWS Storage Gateway: enables organizations to continue to use on-premises applications and workflows while storing and accessing data on the AWS Cloud

AWS Direct Connect: provides a connection between on-premises networks to an organization’s virtual private cloud (VPC)

AWS DataSync: a fully secure tool that automates and accelerates the data migration process from on-premises storage to the AWS Cloud or between cloud storage containers

AWS S3 Transfer Acceleration: a tool that speeds up data transfers from distant global locations securely and easily

AWS Snowball: a console tool that makes it easy to migrate large amounts of offline or remote data to the AWS Cloud

AWS Database Migration Service: a managed service that helps organizations move their database and data analytics workloads quickly and securely to the AWS Cloud with minimal interruption

Beyond migration, AWS has tools that help all types of end users visualize and analyze data:

AWS Datazone: a data analytics portal that provides a 360° view of all your trusted business data, wherever it’s stored

AWS Transform: a new AI-powered service that helps organizations quickly update and modernize their old software systems by automating repetitive upgrade and migration tasks, cutting the time and effort needed by up to 80% in many cases.

Migrating for the Right Reasons

Migrating is a shift in priorities, mindset, and technology. It’s crucial to align your business outcomes and priorities with constraints when establishing a migration strategy. The best way to do that is to work with a trusted migration partner.

At the same time, many business leaders are still mired in legacy thinking and don’t realize how much has evolved and where data science, data analytics, machine learning (ML), and artificial intelligence (AI) capabilities are taking us. Some think ML is only for cutting-edge organizations or feel it’s too complicated for their current needs.

Data opens worlds of possibility. We show them how they can use ML and AI to derive new insights, efficiencies, and value. Data migration builds a foundation for the future. We don’t want our customers to come back in a few years or even a few months needing critical changes they could have built in from the very beginning. That’s the value Adastra’s experience and expertise bring.

The Right Data Migration Partner

You need a good partner to help achieve these goals – to listen, to assist, to support, and to guide organizations through the migration process to ensure they achieve the success they’re looking for.

Migration from anything to AWS is something that we help perform seamlessly. Adastra has significant experience deploying AWS services and tools in conjunction with our own methodology for data migration and conversion.

We meet customers with an open mind, a desire to collaborate, and a drive to understand the specific challenges they’re facing. We’re committed to helping our customers achieve their goals for their business and their users. We draw on our deep history of successful data migration projects and propose tailored solutions. The right solution is the right architecture for that customer. It’s ever a “one-size-fits-all” approach. Whether it’s Internet of Things (IoT) solutions, data analytics, or some other data migration challenge, we have specialized teams with the right expertise to prepare and implement the right data migration strategy to meet your needs.