BI Tool Migration: Is It Right for Your Organisation

Migrating from one business intelligence (BI) tool to another is a complex process that brings both opportunities and challenges. While a new tool may promise advanced features, cost savings or improved data governance, a successful migration requires careful planning and strategic thinking. Before diving into the technical aspects of migration, it is crucial to ask: Should we be migrating in the first place? Do we need to migrate every piece of content?

In this blog, we’ll explore both the practical challenges of BI tool migration, from data management to user adoption, and the strategic considerations that should guide your decision-making process. By balancing these perspectives, organisations can make informed decisions that benefit everyone.

High-level considerations before migrating

High level considerations before migrating

Before embarking on a migration journey, it is essential to consider the following:

1. What is your reason for migrating?

Understanding the primary drivers behind your decision to migrate is critical for setting the scope, objectives, and expectations for the migration process.

Common Reasons for Migration:

Cost efficiency: Are you migrating to reduce licensing or infrastructure costs? Some tools offer more cost-effective pricing models, especially at scale, while others may provide a lower total cost of ownership through cloud-based services.
Advanced features: Are you seeking to leverage advanced analytics capabilities, such as AI-driven insights or machine learning integrations?
Standardisation: Are you looking to standardise BI tools across the organisation for consistency and easier management? Migrating to a single tool can simplify maintenance, training, and data governance.
Integration with existing ecosystem: Does the new tool offer better integration with your existing technology stack (e.g., ETL, data warehouses)?
Improved performance: Are performance issues with your current tool affecting the speed and reliability of your analytics? A new tool may offer better performance through advanced data processing engines or in-memory analytics.
Evaluate the ROI: Before migrating, conduct a cost-benefit analysis to ensure the expected benefits outweigh the costs and risks of migration. Consider not only the immediate costs but also long-term factors such as maintenance, training, and scalability.

2. Should you be migrating?

Not every organisation needs to migrate, even if there are compelling reasons to consider it. Carefully assess whether a full migration aligns with your overall data strategy.

Tool optimisation: If performance or feature limitations are the primary drivers for migration, consider optimising your current tool. Often, poor performance or dissatisfaction arises from suboptimal use, outdated configurations, or lack of training rather than tool limitations. If this is a topic of interest for you or your business, be sure to have a read of our BI optimisation blog!
Assess organisational readiness: Evaluate whether your organisation is ready for a migration. Consider factors like user readiness, the availability of internal or external expertise, and the maturity of your data governance practices. If your organisation lacks a strong data culture or governance framework, migrating could create more problems than it solves.

3. Should you migrate all of your content?

Migrating all existing content is rarely the best approach. A selective migration strategy can help reduce costs, complexity, and risks.

Content Audit and Prioritisation:

Challenge: BI environments often contain a vast number of reports, dashboards, and data models, many of which may be redundant, outdated, or infrequently used. Migrating everything can be overwhelming and costly.
Solution: Trim the fat! Conduct a thorough audit of all existing content to identify what should be migrated, archived, or retired. Prioritise high value reports and dashboards that are actively used and align with current business objectives. Consider eliminating low-usage or outdated content that no longer adds value.

Phased migration:

Challenge: Migrating everything at once can lead to business disruptions and overload both the IT and business teams.
Solution: Use a phased approach to migration, starting with a pilot phase involving a small subset of reports or user groups. Learn from the pilot and refine the migration process before scaling up. This approach minimises risk and allows for iterative improvement.

Practical challenges of BI tool migration

Practical challenges of BI Tool Migration

Once you’ve determined that migration is the right way to go, and have identified which content to migrate, you’ll need to address several practical challenges including cloud data migration challenges.

1. Data management and integration

BI tools often manage data differently, and these differences can complicate migration.

Data source compatibility: Assess compatibility with all of your current data sources and prepare for potential issues where the new tool does not natively support a data source.
Data modelling alignment: If you compare 2 leading tools, like Tableau and Power BI , their data modelling capabilities are very different. How easily are your existing data models going to align your new tool?

2. Visualisation and reporting differences

Each BI tool has unique visualisation capabilities that may impact the migration.

Rebuilding visualisations: Identify which visualisations are critical and require recreation.
Performance optimisation: Conduct early performance testing to identify and resolve potential bottlenecks related to how data is processed or rendered.

We spoke to Senior BI & Analytics Consultant Dan Beeley about the impact that migration can have on end users:

“There’s often a battle between your end users and your data team when it comes to replicating your legacy reporting in your newly adopted tool. A change in visualisation can often be seen as a feature loss, but often, it will simply be visualised in a different way. Fostering a mutual understanding between these 2 key memberships can really ease the pain of migration. So, if you need to make a change to how something looks, make sure it’s efficient, digestible and tells the same, or even better, story than what it supersedes.”

3. Security, governance, and compliance

Security is handled differently across BI tools, requiring careful planning to maintain governance standards.

Role mapping and security policies: Re-create user roles and permissions within the new tool’s security framework, and leverage its features to enhance data security.
Data governance enhancements: Use the migration as an opportunity to improve data governance policies, such as data lineage tracking and data quality management.

4. User training and change management

User adoption is crucial for migration success and overcoming resistance is often a key challenge.

Change management plan: Develop a comprehensive plan that includes communication, training, and ongoing support to ease the transition and maximise user engagement.
Training on advanced features: Encourage adoption of advanced features by providing targeted training and creating environments for users to experiment safely.

Conclusion

Migrating from one BI tool to another is not a decision to be taken lightly, and from what we’ve covered in this blog, it’s clear to see that there’s a lot involved in doing so. It requires careful consideration of both the strategic drivers and the practical challenges involved. By asking the right questions upfront, should we be migrating in the first place? Do we need to migrate every piece of content?, organisations can make informed decisions that align with their overall data strategy.

Want to know more?

Watch our new 4-part webinar series, where BI experts Colin Gresham and Megan Livadas share practical tips and strategies to help you take control of your data.