Analytics Standardization for a Leading Automotive Supplier

Challenge

A leading automotive supplier was managing its analytics environment through a patchwork of disconnected tools and manual processes. Individual teams relied on Microsoft Access databases, Excel spreadsheets, and MySQL instances to prepare and analyze data, with direct access to source systems rather than a structured ETL layer. Reporting was developed independently across departments. This created data silos and made it impossible to trace how key figures were calculated.

The lack of coordination between analytics outputs and product release cycles had become a concrete business problem. Reports and data products were not aligned with the timing of product launches, so decision-makers lacked current data when they needed it most. Manual data preparation consumed significant effort, and the performance of the existing solutions was a persistent pain point.

When a new head of the data and analytics department took over, the decision was made to invest in a proper analytics infrastructure: consolidate the fragmented data environment, introduce standards, and create a foundation that could keep pace with the business.

Approach

Alligator Company joined with two consultants working alongside four members of the client’s internal team over an eight-month engagement. The goal was to replace the fragmented tooling with a standardized analytics architecture built on Data Vault and Exasol.

The team introduced Data Vault as the modeling methodology using DataVault Builder on Exasol as the target platform. This gave the organization a repeatable, auditable data architecture where business rules and data transformations were documented in the model rather than buried in spreadsheets or Access databases. The Ensemble Logical Modeling (ELM) method structured the requirements gathering and ensured that each data object was traced from its business context through to the technical implementation.

To accelerate development and keep the team productive, Alligator Company set up disposable development environments — lightweight, reproducible instances that developers could spin up and tear down without affecting shared infrastructure. The deployment followed a hybrid model: on-premises for development, cloud-first for production. This balanced the client’s existing infrastructure investments with the scalability advantages of cloud deployment.

Two data sources were integrated as the first phase, replacing the legacy data pipeline that had previously fed the disconnected tools. The rollout to additional sources remains open as the client extends the platform incrementally.

Knowledge transfer was continuous throughout the engagement. The Alligator Company consultants trained the internal team on Data Vault modeling, ELM, development practices, and cloud deployment, so that the client’s staff could operate the platform independently after handover.

Outcome

The new platform aligned data delivery with product release cycles and closed the gap that had previously left decision-makers without current analytics during critical product launches. Manual data preparation effort dropped as the standardized Data Vault architecture replaced ad-hoc processes in Access and Excel.

The client’s internal team gained the skills and tooling to develop and extend the platform independently. Standardized modeling practices and documented data flows replaced the undocumented, siloed reporting that had defined the previous setup. Data quality improved as a direct consequence of consolidation: with a single, governed data platform, discrepancies between departmental reports were eliminated.

• Development cycles aligned with product release cadence, reducing time-to-insight from weeks to days
• Manual data preparation effort reduced through standardized Data Vault pipelines
• Legacy data pipeline replaced; two data sources consolidated on Exasol
• Internal team of four trained to model, develop, and deploy independently