Cloud migration service enabled the company to streamline data analytics and automation within their corporate platform.
Our client is one of the largest multi-channel retailers for specialized clothing, tools, and accessories.
Detailed information about the client cannot be disclosed under the provisions of the NDA.
The client came to us with a corporate platform characterized by non-scalability and lack of automation. It made our client turn to a cloud solution based on Power BI, which would enable secure data storage, greater opportunities for analytics, and optimization of business processes.
We have implemented full-cycle workflow automation starting from data extracting and ending with data marts and dashboards creating, covering filtering, and mapping. Although data transfer was hindered by data inconsistency and some peculiarities concerning data representation (Germanic umlaut in the spelling), we arranged everything to make all data coming from different sources available within a Power BI platform.
It allows our client to track the shopper’s path from the first appearing at the site (thanks to Google Analytics data) to the purchase history (thanks to the Salesforce data). This is valuable for getting more targeted campaigns based on the characteristics of the shopper’s behavior.
Also, it’s beneficial for the delivery process that covers placing an order on the site, sending the notification to the logistics department to collect the order and send it to the shopper, shopper’s automatic notification, the delivery itself, and sending a form for leaving feedback on the service/ product provided.
What is more, thanks to the automation works we have done, the information on goods, articles, prices, current balances, and availability in stock are synchronized between internal accounting systems and the website in real-time.
As a methodology for the software development lifecycle, we chose Scrum daily rallies in the morning and evening, but no retro and sprints as such. The releases were made immediately after the implementation/fix of the feature. During the project, all communication between our development team and the customer was handled via Teams. Time tracking was carried out in BCS.
Each phase of development was completed with the unit and manual testing so that we could detect and fix even the most minor bugs as early as possible to prevent them from becoming problems.
We have created a fault-tolerant automated system for swift collecting, storing, processing, and analyzing data. In order to guarantee streamlined system operation, we did not skimp on the resources and applied extremely powerful clusters. In order to ensure system fault-tolerance, we provided maximum code cleanness with logs prominently written to immediately understand what is wrong.
The client has gained a handy cloud-powered platform with data analysis and forecasts displayed in dashboards to use this information for efficient data-driven decisions.
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