Five stages of a headache-free data migration
When you consider migrating your data off a legacy system, what comes to mind?
Often, the first thing you think of is the complexities of data ownership and managing the migration process. That’s usually followed by thoughts of risk and security issues, such as unforeseen downtime and business disruptions.
Next is operational readiness, then cost considerations: research from Experian shows that only 36% of data migration projects keep to the forecasted budget, while only 46% were delivered on time.
And this is about the time the headache starts to settle in.
Cost is often the biggest concern: 55% of respondents to a recent Deloitte survey stated one of the key impediments to data modernization projects is the worry of going over budget.
Underpinning that, the same survey also revealed nearly 44% of respondents reported a lack of understanding of critical technologies as an inhibitor. When there are no industry standards that define the processes and tools used for data migration, it’s no wonder that more than half of all data migration projects exceed both time and cost projections.
Why we deal with the data migration headache
There are many significant business reasons to take on a data migration project, including but not limited to:
- Managing technical debt
- Reducing maintenance costs for legacy systems
- Increasing storage capacity
- Improving performance
- Generating business value from your data assets
The secret to success data migrations falls in two key areas: planning and resources. Working against a detailed plan, designed for your environment and business requirements, ensures that everyone involved understands the timeline, activities, dependencies and accountability that impacts moving forward. It also highlights the resources required to do the migration effectively and with minimal risk to the business.
Plan the work, work the plan
Businesses that manage successful migrations know these projects require careful planning and meticulous execution. Planning and execution for a data migration project involves five phases:
- Discovery
- Analysis
- Design & Plan
- Implementation
- Go Live!
Discovery: the fact-finding, confidence-building phase
In Discovery, your data migration team seeks to fully understand and document all the details and dependencies so that the migration solution meets business requirements. Not just from a technology perspective, but also the non-technical items like maintenance windows, blackout dates, change control processes, the elimination of silos, and even organizational structure and priorities.
The Discovery process consists of the following steps:
- Conduct a detailed data discovery of source systems.
- Discover existing third-party products related to legacy storage.
- Discover current data protection solutions for data on source systems.
Analysis: the think and communication phase
Comprehensive analysis and understanding are critical for any successful project plan. Operational needs, such as manageability, monitoring, and any third-party software integration requirements, are explored. The goal in this phase is to document the complexity and compatibility of all operational elements and potential impacts.
The analysis must be shared with all key stakeholders across the organization. They are engaged to ensure every impacted team is onboard and any potential changes, issues, or additional requirements are captured and communicated.
Design and Plan: the prepare for action phase
With all teams on board, it’s now time to dig into the heart of the project and begin to flesh out the project plan. Key components of this phase include:
- Migration schedule
- Migration methodologies, tools, and run books
- Implementation plans
- Operational plans
Once these have been signed off on by all parties, we’re ready to put the carefully laid plans into action. The sign-off by each key stakeholder is important to solidify the commitment for a project of this scope and business impact.
Execution: the action-at-work phase
Putting the plan into action still requires careful consideration and a thoughtful approach. Typical the team will start with a pilot phase that puts the requisite hardware and software in place, and allows them to test the migration plan, checking for problems or unforeseen issues before launching into the full production.
Once the pilot validates the technology and the process, and any new issues or risks are resolved, the full migration takes place.
Go Live: the payoff phase
Once the new system is deployed and the data is migrated, the Go Live phase delivers a smooth transition to the freshly migrated data. This is when the team performs all post-migration activities and updates operational runbooks and resources for the new environment. Documentation is completed and the new data environment is ready to be fully operational.
Seamless, smooth management of the five phases
IT organizations know these project phases but often lack the resources, time, or recent experience to execute them while running their data systems. Technologies like Snowflake and Databricks require deep technical expertise, and often internal teams like this knowledge due to the day-to-day requirements of keeping the current systems running.
This is where a smart professional services team can be your best investment in the data migration process. These teams can bring experience, proven methodologies and proprietary tools to assist IT teams with the planning and execution. Standardized, scalable, end-to-end project management, and closed-loop governance across all phases will help IT organizations successfully migrate off legacy systems and onto new, modern data storage systems.
With the support of an experienced professional services organization, your data migration project can be executed seamlessly, on-time and on-budget.
The headache-free approach to data migrations
Numerous benefits come from successful data migration. Some of these are obvious, such as the increased performance and efficiency enabled by the updated storage system.
In addition, reduced maintenance and support costs that follow the decommissioning of legacy systems helps manage budget concerns and the data cleansing that happens in the process improves the business’ data integrity.
All of this leads to both greater IT efficiency and reduced technical debt. These factors, taken together, lead to a more agile and effective IT organization. Despite the risk and complexity, successful data migrations happen every day. All you need is the right process – and the right professional services partner – to make it work.
