Put your data cloud migration journey
on track from the start

Setting your data cloud migration journey on the right track from the start is crucial. This initial phase lays the groundwork for a smooth transition, ensuring strategic alignment and effective execution throughout the migration process. Follow these four key pillars to ensure a smooth, strategic transition to the cloud:

Get organizational buy-in
Build a comprehensive migration plan
Establish an effective change management plan
Create a well-defined operating model and policy strategy

Gaining organizational buy-in

Embracing data cloud migration is a pivotal step towards digital transformation that requires organizational buy-in to unlock its full potential. Without it, the journey toward data cloud migration risks stalling, potentially leaving you and your business falling behind the competition.

Think about the characteristics that are most important
for executive and stakeholder alignment.

For executive leadership

Ensures alignment with strategic initiatives of the business
Gains commitment for resources and funds
Supports top-down communication to drive action and priority
Helps identify executive sponsorship to provide credibility, gather cross-functional support, communicate goals, and act as an advocate

For business and technical stakeholders

Be open to being an early adopter and acting as an evangelist for the project
Have right level of subject matter expertise or willingness to dig and learn
Have the time to dedicate to the project

Establishing effective change management

At the heart of every successful data cloud migration lies effective change management. This strategy is critical not just for the technical shift, but for ensuring user adoption and maximizing the return on investment (ROI) of the project. Understanding how stakeholders currently accomplish their tasks and how this will transform post-migration is key to a seamless transition.

How will people be trained on the new technology as well as new or changing processes?

Online training
Train the trainer
Demonstrations
Job Aids
Certifications

How will you promote/communicate the value
of the change?

Internal newsletters
Email communications
Video testimonials
Presentations at team and leadership meetings

How will you monitor progress and adoption?

Benchmark time spent on various activities before and after the migration

Looking for data
Understanding data
Gaining access to data
Monitoring data quality

User satisfaction surveys

Ease of use
Roll-out strategy
Training programs and materials
Communications

Usage analytics

Number of unique logins
Number of logins
Number of business users vs technical users
Number of data access requests

Building a comprehensive data migration plan in 4 steps

In this phase, you’ll define your data migration approach, setting priorities, roles, and a realistic roadmap with contingency plans.
Remember to focus on clear communication in this phase to ensure a smooth transition and successful post-migration audit.

1. Define the scope

Decide if you’ll take a big bang approach, an iterative or agile approach,
or a hybrid approach
Prioritize the migration use cases you identified at the beginning of the journey
Identify the required connections to sources and tables for each use case

3. Determine required contingency plans, such as:

Unexpected loss of critical skills and subject matter expertise (e.g. cross-training, consultants, etc.)
Migration rollback in the event of data loss, unanticipated changes to the data, errors encountered during the migration, or other similar situations

2. Set clear expectations for all stakeholders

Develop a RACI (Responsible, Accountable, Consulted, Informed) chart to ensure everyone understands their roles and responsibilities. Check out our sample RACI in the appendix to help get you started.
Create a roadmap and rollout plan for each use case and data source
Set realistic timelines and milestones for each phase of the migration project
Define standards for data migration readiness
Communicate the change management plan
Confirm stakeholder agreement on expectations

4. Create a post-migration audit plan

Before retiring the source system
To confirm that data was migrated successfully
To ensure policies are accurately applied

Ready to start your plan?

To make the migration process easier and more efficient, we’ve developed a comprehensive checklist tailored to guide you through each step of your plan.

Get our helpful checklist for building your data migration plan.

Defining the operating model and guidelines for policy strategy

An operating model and policy strategy are blueprints for achieving your organizational goals. So it’s important to decide on the type of data governance operating model that will work for your organization.

Consider the range of unique needs for your organization and balance them against the need for standardization and consistency. The three main types of organizational models are:

Centralized - central authority determines the rules of how to govern and individuals and teams executing data governance must adhere to centrally defined processes

Introduces consistency and reduces confusion
Less risk of duplication of effort – increasing productivity
May be appropriate for highly regulated organizations
May not account for unique data governance needs for different parts of the organization
Bottlenecks to gain access can delay access of business insights

Decentralized - multiple groups of authority; most often adopted if different teams with different data governance needs

Puts data governance policy and definitions closer to the subject matter experts, but could result in a disconnect from business objectives
Improved representation from the business
Runs the risk of duplication of data and inconsistencies around policies

Federated - balances the restrictiveness of a central governance authority that may not account for the unique needs of various groups while also providing best practices and standards that provide consistency and reduce complexity.

Defining clear roles and responsibilities for your chosen operating model is essential for driving accountability and aligning data governance with your business objectives. In addition, establishing robust data standards and usage guidelines is critical for maintaining the integrity and trustworthiness of your data, forming the foundation for your approach to data sharing, reusability and comprehensive governance.

Defining the operating model and guidelines for policy strategy

Efficient and effective policy development is anchored in an understanding of your unique access standards and stewardship model. Focus on the following critical areas as you craft your policy strategy.stency. Themthree main types of organizational models are:

Policy strategy

Establish standards for access policies based on applicable regulations and best practices. Ask yourself

Who can access each table?
Who should be able to see sensitive data?
Are there data residency restrictions?
What are the data retention policies?
Can the data be shared outside of the organization?

Decide on the stewardship model:

Subject area (for example - products, customers, financials)
Function (for example - marketing, sales, customer support)
Business Process (for example - campaigns, procurement, sales)
Systems (for example - CRM, project management, human resources)