How Renson tackled their Data Warehouse Migration

Organization & context

Renson is a Belgian manufacturing company internationally active and committed to “Creating healthy spaces”. With a central focus on R&D and innovation within this market, Renson has a broad range of product categories including ventilation systems, sun blinds & a variety of outdoor solutions (e.g. terrace coverings).

The Renson Group consists of various companies including Renson, eSafe, ARLU, and Corradi. Together, they form an international enterprise dedicated to innovation and excellence in their respective fields. This collective strength allows Renson Group to deliver comprehensive solutions that enhance the quality of indoor and outdoor environments.

The challenge

Renson’s primary challenge was transforming data into actionable insights. With a growing ecosystem of business units and a growing business overall, their traditional Business Intelligence (BI) Data Warehouse setup struggled to deliver. The existing system had multiple limitations including:

• Complex legacy code: Driven by growth in the last decade, the architecture was undocumented and resembled a “spaghetti” structure, complicating maintenance and updates.
• Underutilized reports: Despite having more than 300 SSRS and Power BI reports, only 30% were viewed more than once a day.
• Data source limitations: There were restrictions on the types of data sources that could be integrated (e.g. cloud-based APIs), hindering comprehensive data analysis
• Limited collaboration and version control: The current legacy system lacks proper Git integration, making it challenging for engineers to collaborate effectively. Without a controlled versioning system, developing new features or dashboards becomes slower and prone to errors. Additionally, there is no streamlined process for testing and releasing updates, leading to delays and inconsistent rollouts.
• Future use-case constraints: The existing setup was not equipped to handle future requirements, like the integration of SAP S4 HANA which went live in January 2024.

Figure 1 – Through growth in the last decade & iterative development, the traditional data warehouse didn’t represent the original clean structure and set-up it once envisioned

To address these challenges, Renson needed a clean restart with a Modern Data Platform that could handle real-time data flows, support diverse data sources, and facilitate self-service reporting truly. The goal was to create a streamlined, efficient system that could deliver minimal effort and maximal insights, driving data-driven decision-making throughout the organization.

Approach taken in the migration

With a clear vision & mission set on what to tackle, Renson and element61 jointly worked together to deliver this project step-by-step. nine guidelines where used to guide this project towards success.

1. Pick the Right Architecture Fit for Purpose

Based on the analysis done by element61 and outlying the various options forward, Renson chose a Data Lakehouse approach to best fit their future needs. Leveraging Azure Data Factory for structured data ingestion and orchestration, Dataverse for data entry and master data management, Azure Data Lake Gen2 as the data warehouse layer, and Databricks for all data engineering and transformation, their architecture was purposefully designed for efficiency and scalability.

This to-be architecture was chosen to leverage both proven architecture (with thus minimal risk) while being truly future-proof for both modernized data warehousing as well as future non-classical BI use cases.

2. Work from the LEFT to the RIGHT

The team adopted a domain-first migration approach rather than a use-case-first approach. This meant that when a domain was tackled it was tackled in its entirety incl. reviewing all related requirements & scope.

Rather than migrating the most important reports, domains were migrated completely, delivering a bundle of reports. This approach prevents staying stuck in the past (often a risk in a use-case-first approach).

3. Aim for one Enterprise Data Model – Star Scheme

Renson aimed for simplicity and ease of understanding by using a clear & full star schema for their enterprise data model. By establishing one version of the truth through a clean enterprise data model combining the various end-to-end business domains, they ensured consistency.

Crucial in this approach was to integrate the various systems (e.g. various ERPs in use: SAP, Navision, and customized legacy systems) into a single data model, making it future-proof and easy to digest. This Enterprise Data Model enables a single, unified version of the truth for each business domain, regardless of the underlying data sources.

Figure 2 – Illustrative example: how a star schema looks like for Sales Orders

4. Accelerate the process

Proposed by element61 and after a thorough fit-gap analysis, Renson leveraged the Power BI “Out-of-the-box” modules of element61 to accelerate development.
The Power BI “Out-of-the-box” modules of element61 provide pre-packaged tools to expedite the development process by integrating various systems into a unified data model. These modules include ETL bundles, structured data lakes, recommended data lakehouse layers, and pre-defined Power BI semantic models and dashboards, ensuring standard components are quickly implemented. This approach allows teams to focus more on customized elements and achieve consistency through a future-proof architecture.
For Renson, the fit-gap analysis showed that 66% of all reporting requirements could be covered by leveraging Power BI “Out-of-the-box”, allowing the project to accelerate on 2/3rd of the scope and to focus on the remaining 1/3rd  of custom requirements.

(Sidestep: read more about our Power BI “Out-of-the-box” modules)

Together with Renson, element61 was able to tackle the below business domains and accelerate them by using “Out-of-the-box”.

“Investing time in rethinking, redefining, or redeveloping customized elements is more valuable than reinventing the wheel for standard components.” – Maxime Bernaert, Data Manager Renson

5. Get the Right Team Members and Make Sure Everybody Is in the Same Boat

To deliver this migration project, Renson assembled a team of specialists, including Business Data Stewards, BI Program Leads, Executive Sponsors, Data Architects, and Data Engineers. Regular alignment in steering committees ensured everyone was focused on the same goals.

For the actual build, element61 took the lead & worked in a coaching & co-development set-up thus training the internal team on the job.

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6. Scope Realistically and Work Agile in Short Iterations

While from the start the technological choices were clear & fairly certain, the requirements kept changing throughout the project making the project & approach more & more complex. Therefore, the project was quite fast broken down into manageable pieces to adapt to changing requirements.

The project was transitioned from a waterfall approach to agile/scrum methodologies with bi-weekly sprints in DevOps allowed the team to hit moving targets efficiently. This allowed us to deliver.

7. Get Knowledge from Coaching & Co-development Combined with Academy Training

To ensure a fast learning curve, the team participated in coaching, co-development, and academy training. This not only accelerated their understanding of technology but also ingrained best practices, leading to increased involvement and commitment.

Renson leveraged actively the element61 Academy courses incl. Azure Fundamentals and Data Lake development.

8. Policies & Standards: Relevance & KISS & Reuse

The principle of “Keep It Simple, Stupid” (KISS) was adopted to ensure that the architecture remained understandable and easy to fix. The team emphasized the importance of relevance and reusability before resorting to building anew.

Renson takes the principle to only build something custom in last resort. Reuse first – e.g. by leveraging the element61 Power BI “Out-of-the-box” modules.

9. Reporting is Not the Goal, It’s a Goal – Data Platform as an Enabler

The ultimate aim was to create a data platform that enables impactful actions rather than just reporting for the sake of it. By focusing on use cases and dreams, Renson turned their data-driven aspirations into tangible business outcomes.

Next to the reporting deliverables as part of the migration, a parallel first GenAI use-case was piloted to leverage the same data & platform for a broader purpose.

Solutions & results

This data warehouse migration project aimed to translate a decade of traditional SSIS BI development connected to various ERPs and a wide set of other data sources/excels into a modern data platform in Azure Databricks while a new SAP S/4HANA ERP went live for the first business entities mid-project.

With the migration kickstarted in Q2 2023, the migrated data warehouse (including domains such as procurement, sales, service, etc.) was developed less than 12 months later and ready to onboard the users. The data platform didn’t only contain all historical data but also contained the new SAP S/4HANA ERP and harmonized all data in a new best-practice enterprise data model.

Today, Renson has set up a best-practice Modern Data Platform in the Microsoft Azure Cloud (architecture diagram below) as a basis for the BI reporting & the first GenAI use cases.

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Role of element61

Partnering for many years, element61 played a role as facilitator & accelerator in this data warehouse migration.

First, element61 helped define the vision forward. Kickstarted by a Data Optimization Assessment, element61 analyzed the as-is, clarified the current state, outlined the options forward & defined a purpose-fit architecture.

Once the direction was confirmed, second, element61 ensured the right internal team setup with coaching, co-development, and academy training. Working hands-on with the internal team, element61 helped with the migration work”. Leveraging our Power BI “Out-of-the-box” modules as well as the experience & expertise from earlier projects & similar projects, element61 stuck around from day 0 all the way to post-go-live support. After nine months, SAP S/4HANA went live, followed by the successive go-lives of all business domains and reports.

Forward-looking, element61 remains there to help Renson in further accelerations. Supporting both architectures as well as overall analytics strategy, element61 is there as a sounding board, long-term partner and coach.