Big Data Set Pricing Analytics

At EnterBridge our pricing analytics technologies rely on buying patterns in data to suggest pricing and margin development strategies to our clients. We have developed our data driven approaches in traditional data integration and business intelligence environments for the past decade.

You know the world revolves around data and we could spend time talking about the variety of buzzwords that fill the air and how our team is dedicated to finding, developing and implementing big data solutions and related technologies. 

But frankly, that is all talk! We would rather seek out demonstrable value. So we challenged ourselves to reinvent some of our own technology and measure the results.


Reinvent the EnterBridge pricing engine to address:

  • Quick and simple visual access to data for our data analysts in business friendly environments
  • Processing data elements and logical views in a timely fashion
  • Parallel processing of models to evaluate optimal outcomes
  • Developing rule-based methods and algorithmic execution
  • Reducing overhead for Extraction, Transformation & Loading (ETL)

We have utilized this Big Data approach and updated our existing pricing analytics process which consists of the following steps:

  1. Loading invoices and supporting data
  2. Executing our pricing algorithms
  3. Visualizing the results

We've evaluated and utilized multiple vendor technologies and solutions to identify best-in-breed tools. Our final implementation in this process demonstrated that innovative technologies can add value to proprietary data sets, existing processes and business activities of many shapes and sizes, all at a valuable Return-on-Investment (ROI).


Our initial reference implementation for our pricing engine, represented by the diagram below, yields the following benefits:

  • Flexibility at scale to manage execution performance 
  • On demand environments that can accommodate concurrent models
  • Significant reductions in traditional ETL processing times
  • Support for timely visualization of big data and and integration of business friendly environments such as Tableau and Excel
  • Statistical and analytical solutions to assist in algorithmic discovery and validation of outcomes
  • Cost efficient processing resources using cloud-based platforms

It is clear that big data has much to offer as an extension to, or replacement of, existing enterprise strategies for data science, analytics and operational data practices.

Let us help you discover the impact modern data architectures can have on your organization!