Making data worth moving before migration

A migration plan built on data nobody trusted

The law firm had made the right decision: move off ageing, out-of-support infrastructure and onto a modern, cloud-based platform. Its core systems - CRM, Practice Management, and Matter Management - were fragmented across a mix of SaaS and on-premise applications that had long since reached the limits of their operational utility. The direction of travel was clear. What wasn't clear was whether the data being carried into the new environment was fit to go.

Discovery revealed a firm operating under significant data debt. More than 3,800 duplicate records - organisations and individuals - sat uncorrected in the CRM. Revenue could not be tracked reliably by work type or service line. Marketing lists couldn't be trusted for prospect engagement. KYC alerts fired inconsistently; AML triggers failed to activate correctly; GDPR compliance markers had no reliable visibility. Analysis and reporting depended on ad-hoc SQL queries run by a single technical individual - creating a fragile, uncontrolled dependency that the firm had no systematic way to replace.

The consequences of migrating in this state would have been severe. A new platform built on unvalidated data would have inherited every one of these constraints, compounding rather than correcting years of accumulated technical debt. The investment case for cloud migration rested on data that the firm's own practitioners did not trust.

Remediate, then migrate

Aptitude's assessment produced a clear strategic recommendation: the planned "lift and shift" migration needed to become a remediation-first programme. Moving data without first fixing it would not resolve the underlying integrity problems — it would institutionalise them in a more expensive and harder-to-change environment. Data cleansing and governance had to precede migration, not follow it.

To execute this, Aptitude deployed a dedicated seed team combining a Business Analyst, a Data Analyst, and an Architect/Engineer — a deliberate structure designed to ensure that user requirements, data controls, and technical pipelines were built in parallel rather than sequentially. This prevented the disconnect between business need and technical delivery that typically derails programmes of this kind.

The target architecture was built within the firm's existing Azure environment. Data from both internal and external sources was routed through a structured ingestion layer into a Generation 2 Storage data lake — profiled, measured, and cleansed through automated pipelines before reaching a SQL Managed Instance for reporting. In place of the firm's uncontrolled ad-hoc reporting, Aptitude blueprinted a formal Reporting Data Warehouse hosted within the firm's primary cloud tenant: a single, governed version of the truth.

A third-party validation service executed a one-off cleanse of contact and address data. Automated KYC and AML triggers replaced the inconsistent manual checks that had created compliance exposure. GDPR markers for Data Subject Access Requests and complaints were integrated, closing a regulatory visibility gap the firm had been carrying without a clear resolution path.

Then came the finding that changed the financial picture. During the discovery process, Aptitude identified a legacy calculation error in which interest had been incorrectly added to capital on migrated matters - requiring manual monthly reconciliations to correct.

Caught pre-migration, the error was remediated before it could be carried permanently into the new platform.

From data debt to a governed foundation

The remediation programme delivered an immediate shift in the firm's operational footing. Duplicate records were resolved, removing the manual effort that had previously been required to detect and correct them. Validated contact data gave the marketing function a reliable base for the first time. Automated compliance triggers replaced a patchwork of manual checks that had left the firm exposed. And the interest calculation error — identified and corrected before migration — prevented a systemic financial inaccuracy from becoming a permanent feature of the new environment.

At the programme level, the discovery phase did something more valuable than clean data: it replaced uncertainty with a validated migration roadmap. By establishing that data quality — not software functionality — was the primary blocker to a successful transition, Aptitude gave the firm's leadership a clear and defensible basis for sequencing the migration. The move to cloud was no longer a high-risk bet on untested foundations. It was a controlled evolution with known parameters.

The Reporting Data Warehouse, the governance framework, and the automated compliance infrastructure together provide the foundation for advanced analytics and automated decision-support — capabilities the new platform was always intended to enable, and that are now, finally, within reach.

The firm now holds something few organisations carry into a major platform migration: data it can rely on.