Case Studies

Challenge
Avove UK required a scalable, robust data pipeline to handle a wide variety of data sources, both structured and unstructured. The company was dealing with diverse formats, which made automation difficult. Additionally, they lacked a clear data infrastructure strategy and faced challenges in collecting the necessary data to support critical business decisions.

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Solution
Using Azure Data Lake, Azure Data Factory and Azure SQL Database, I personally built the entire data pipeline, designed and implemented the database schema, and developed comprehensive data models to support the company’s diverse data needs. I incorporated data quality checks throughout the pipeline to ensure consistency and accuracy, even when dealing with data from varied sources and formats.

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With minimal supervision, I proactively engaged with business stakeholders to develop use cases, gather detailed requirements, and fully understand business processes. This enabled me to ensure that all the necessary data was being collected and appropriately structured for business use. I also conducted a thorough gap analysis of the existing data systems and infrastructure, identifying potential pinch points and recommending practical solutions. This resulted in a clear roadmap for future system improvements and the smooth onboarding of additional clients.

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Outcome

• Successfully built and automated a data pipeline using Azure Data Lake and Azure Data Factory, capable of handling multiple data formats and structures, enabling seamless data integration across the company.

• Designed and implemented a robust database schema using Azure SQL Database to support scalable data storage and retrieval.

• Proactively gathered business requirements and developed use cases, ensuring that the pipeline and data models directly supported business goals.

• Conducted a gap analysis that helped the company identify and address weaknesses in their current data infrastructure, leading to better system performance and a roadmap for future enhancements.

• Delivered the project with minimal oversight, demonstrating the ability to independently manage complex technical challenges and align solutions with business needs.

Challenge
Data 2 Action, a data consultancy, hired me to work on a project for their client, an academy trust of primary and secondary schools in the North of England. The trust needed a unified system to analyse key metrics such as pupil attendance, teacher assessments, and exam results. However, their existing data infrastructure made it difficult to extract meaningful insights, limiting their ability to make data-driven decisions.

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Solution
I designed and implemented a comprehensive Power BI environment that provided detailed insights into pupil attendance, teacher assessment results, and exam performance. The dashboards included row-level security, ensuring that each user—whether a headteacher or the trust CEO—only had access to the data relevant to their role. This approach maintained confidentiality while delivering tailored insights across the organisation.

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Outcome

• The dashboards empowered decision-makers at all levels to pinpoint problem areas, such as correlating attendance with attainment and identifying underperforming regions or schools.

• These insights helped the trust allocate resources more effectively, driving improvements in areas that needed the most attention.

• The Power BI environment is now fully embedded in their operational processes, supporting data-driven decision-making across the academy trust.

Challenge
Rebound Electronics, a global B2B semiconductor supplier with operations in 22 countries, needed to establish a data-driven approach to better understand sales performance, customer behaviour, and proactively identify sales opportunities. Their data infrastructure was underdeveloped, and they lacked the insights necessary to make data-driven decisions across such a vast, complex organisation.

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Solution
I was brought in to build and lead the data team. I started by developing a comprehensive data strategy and roadmap, setting the foundation for a scalable data infrastructure. After scouting for and securing a business partner to support the infrastructure, I negotiated the contract and established a strong working relationship. The partner set up a Snowflake instance, while I personally designed and implemented the data model and data marts.

I worked closely with a data visualisation expert to create Power BI dashboards that provided detailed insights into sales performance and customer behaviour. These dashboards not only tracked performance but also identified new sales opportunities, allowing the company to take proactive actions. I led all workshops with the business, gathering requirements, defining metrics, and designing dashboards to meet the company’s needs.

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Outcome

• The new data infrastructure and dashboards enabled the business to better understand and react to sales trends and customer behaviours.

• Key insights into sales performance and customer interaction patterns helped the company identify previously unseen sales opportunities.

• Strong relationships and collaboration between the data team, business stakeholders, and external partners resulted in a seamless implementation of the data strategy.

Challenge
PureGym needed to modernise their facilities management (FM) data environment to improve cost efficiency and supplier KPIs. Their outdated reporting processes were labour-intensive, and they lacked a unified system for real-time data analysis. This was causing delays in managing facilities operations and preventing the business from optimising its contracts with suppliers.

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Solution
I managed the development of a new data environment specifically tailored to facilities management. This included the creation of a Power BI platform and the implementation of a modern data warehouse using Azure SQL. The data pipelines were restructured to ensure seamless integration and consistent data quality, specifically for FM-related data such as maintenance schedules, supplier performance, and cost tracking. Custom Power BI dashboards were built to monitor supplier KPIs and budget performance, providing real-time insights into the efficiency of facilities management operations.

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Outcome

• Achieved a £250,000 improvement in cost efficiency against the budget in the first year through better data visibility and supplier management.

• Improved supplier KPIs by 80% by leveraging data insights to optimise contracts and streamline supplier performance.

• The new system significantly reduced manual reporting processes, allowing the FM team to focus on strategic decision-making, ultimately improving operational efficiency.

Challenge
BCA’s Logistics department was struggling with outdated reporting methods and a demoralised data team due to recent policy changes. The reliance on Excel reports made it difficult to gain real-time insights, and the data team lacked the motivation to drive meaningful change. Additionally, clients like Volkswagen, BMW, Audi, and Motability needed better visibility into their KPI performance and issue tracking.

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Solution
As the Data Manager, I restructured and rebuilt the data team, managing the recruitment process and mentoring a highly capable team of data analysts. I shifted the department away from Excel-based reports by developing an internal Power BI environment for the logistics planning team and an external QlikView environment, accessible directly by clients.

The internal Power BI dashboards provided near real-time visibility into ongoing jobs in the field, allowing the planning team to proactively address issues before they escalated, resulting in significant cost savings. The external QlikView dashboards enabled clients to monitor daily progress on contractual KPIs and stay updated on known issues, reducing the time BCA’s account managers spent on manual reports and client calls.

I also collaborated with the Data Management team to build a data warehouse, taking charge of the data schema design, mapping, and cleansing from the logistics system. This clean, structured data was essential to the success of both the Power BI and QlikView dashboards. Furthermore, I worked with the Data Science team to develop machine learning models aimed at improving budgeting and workload forecasting.

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Outcome

• The internal Power BI environment improved operational efficiency by providing real-time job tracking, saving the company substantial costs by preventing logistical issues.

• The external QlikView dashboards significantly enhanced client satisfaction, reducing the workload of account managers and improving client relationships.

• The new data warehouse and clean data pipelines formed the foundation of all reporting and analytical efforts, ensuring data quality and consistency.

• The machine learning models I helped develop enabled more accurate budgeting and workload forecasting, improving operational planning across the logistics department.