Identifying the Problem
Dataninja, a retail analytics consulting firm, was building powerful analysis and forecasting tools using Excel for suppliers to the world’s largest retailer.
A hand-full manually triggered software scripts for fetching data reports kept their business working, but when a partnership opportunity presented itself to increase their client base by 500%, there simply weren’t enough hours in the day to satisfy demand.
Dataninja had a vision for improvements to their workflow, but needed technical assistance on the leap from a single desktop computer to cloud based software. Executed properly, Dataninja envisioned their tools being expanded to a Software as a Service solution for other firms as a new line of business.
Lofty Labs investigated Dataninja’s workflow and built a distributed application to manage their reporting pipeline, using Microsoft Azure as a cloud provider.
Leveraging open source software tools, Lofty consultants designed an application architecture which allowed RetailLink to be automated by an elastic collection of servers that Dataninja could scale up and down with demand. This platform supported configurable outputs for maximum flexibility on how to post-process reports.
Finally, Lofty consultants implemented a REST API on top of the new data warehouse. The API layer moved significant amounts of non-testable proprietary database logic into testable Python code which could be adapted to any database system.
Ultimately, this resulted in an API interface to data that normally would have been manually requested and downloaded by a human using RetailLink.
Increased Operational Capacity
Dataninja grew their consultancy from less than 10 to over 50 clients on the new application infrastructure, a side effect of which was a reduction of the number of databases managed by Dataninja to one, instead of one per customer. This simplified architecture meant customer on-boarding was reduced from a matter of days to just minutes.
The configurable pipeline output enabled Dataninja to flexibly process data. The firm could push data to their internal data analysis tools directly, or transfer raw data directly to customers who preferred to do their own analysis.
The ability to push reports became the basis for a Software as a Service product, enabling a new type of customer to leverage Dataninja’s RetailLink automation in their proprietary analytics workflows. Dataninja began piloting this product with customers just one month into their engagement with Lofty Labs.