TL;DR;
Freight Logistics Solutions needed help to modernise its data warehousing capabilities to run more effecient operations and gain a competitive advantage. The aim for the cargo transport provider was to improve their digital position and scale their business.
Approach
We consolidated data into a centralised reporting database to eliminate manual work and provide more timely insights into the business and its customers. Collaborating closely with the management and technical team to deliver a build a scalable and cost-effective data warehousing and data integration process. Utilising a mix of scheduled and real-time data feeds to provide an up-to-the-minute view of the business performance.
Objectives
- Consolidate data from multiple sources into one centralised reporting system
- Deliver a cost-effective solution in terms of maintenance and scalability for the business
- Train staff so that key digital capabilities are developed and sustained within the firm
- Support data warehousing competencies in order to help leverage a distinct competitive advantage in the market.
Achievements
- Aligned prioritised technical requirements with business objectives in business modelling workshops
- Delivered one central database using Azure SQL that consolidated multiple data sources.
- Delivered real-time data from APIs using Azure Functions. Real-time analytics support better business decision making
- Provided a cost-effective solution using Platform as a Service (PaaS) and Serverless solutions with no ongoing maintenance burden and the ability to scale easily
- Supporting ongoing data warehousing service in order to ensure database optimisation and backup maintenance.
Nightingale have been a joy to work with, they got to grips with our brief quickly and understood our business goals. Technology moves quickly and we were after an agile solution that had plenty of future flex, that would really add value to our customers experience of using us and our insight. Looking forward to the next project.
Chris Sourbutts – Director of Data & Technology, FLS