Looking for new ways of growing their business, our client in the fintech space approached CoStrategix to take a look at their byproduct data and frame a comprehensive data strategy with the objective of driving new revenue streams and driving operational efficiencies for their customers.
Business Outcomes
Data And Analytics Strategy
Our client had a multitude of data sources with varying end-business-user requirements. There was an opportunity to directly monetize the data assets and build insights into various SaaS products. CoStrategix worked with the client to analyze data assets, evaluate current technologies, and frame strategic initiatives to drive business growth objectives.
Data Classifier
Like many transactional businesses in the fintech arena, our client had multiple data sources with unique formats. CoStrategix worked with them to implement a model of classification based on text mining and machine learning that could process terabytes of text data. These classification models achieved rates of 98% or higher. Having this automated ability became immediately valuable to their own customer base for growing business.
Data Engineering
The original platform was built around the notion of providing raw data feeds. Today, we recognize that data is a strategic asset and needs to be managed as one. In line with that, we architected and implemented a modern data solution platform on Azure cloud using Cloudera solution components. Data pipeline implementation to source data using python, modeling enterprise data models, data service APIs, and other aspects were part of the data engineering.
The alcoholic beverage industry changes rapidly. New products are added almost daily, and everyone from small brewers to industry giants wants to know how each shift affects their potential revenue.
We worked together to identify the biggest data priorities and develop a comprehensive strategy and modern data cloud system for product cataloging and price measurement. These data points not only show where products are selling and where they are not, but also enable clients to find similar business classes that have had success with alternate products.
Supply chain data can be injected into daily measurements for operational efficiencies. For instance, knowing the rate of sale for a product in various regions means products can be directed exactly where they are needed. Additionally, knowing the rate of sale for a product means sales and marketing can narrowly target their efforts, or create opportunities for dynamic pricing adjustments.
