Case Study: Data Management

Data Management & Visualization

Supply Chain

The supply chain industry faces inherent challenges when looking for business intelligence to make informed data-driven decisions. These include incomplete, outdated data that is fragmented across dozens or even hundreds of systems, lack of data capabilities, and lack of structured analytics processes.

The Challenge

Our client wanted to deliver enhanced data visuals to customers within the existing application. The initiative, sponsored by the VP of Business Intelligence Services, was to replace and enhance the existing analytical capabilities within the application, which in turn would help the client replace the third-party analytics vendor and create the client-managed data visualization in-house.

Our client also wanted the BI solution to support multi-tenancy and all sizes of customers, including mega customers sizes (250,000 packages a day, 650M record count per year).

The Solution

Our data specialists conducted a thorough assessment of the existing processes and recommended construction and delivery of a three-tier analytics data mart (ADM) to serve as the data foundation for analytics within the existing application. A three-tier data mart, recognized as best practice for abstracting data acquisition from data utilization, was used to achieve dependable, reliable, integration of data into the ADM.

Building an ADM would provide the benefits listed below which would not only meet, but exceed the client’s stated requirements:

Performance – Visuals built on an ADM perform orders of magnitude faster

Resilience – The abstracted architecture ensures that no one layer takes down the entire ADM and if portions of the system become unavailable, the other layers continue to function

Extensibility – Additions to reporting and visualization capabilities require less effort to implement

Maintainability – Changes or fixes within the architecture can be isolated from other layers and minimize the impact on the entire system

Operations – The abstracted architecture allows automation tools to handle the integration between the layers, thus requiring less human intervention to operate

Governance – The layered architecture allows for better control over changes within the layers and more efficient processes by which changes are introduced and managed through the release cycle in the various layers

The Results

  • Increased Analytical Capabilities - The three-tier analytical data mart (ADM) helped the client build analytical capabilities and data visualizations in-house, eliminating the need for a third-party vendor
  • Mega Customers Now Supported– The ADM is able to support all types of customers especially Mega customers with large data
  • Improved visual performance, reduced data storage cost
  • Increased scalability, improved security – The ADM supports multi-tenancy, both on-premises and in shared environments; restricts data access to the appropriate customers and users; and additions to reporting and visualization capabilities require less effort to implement
The objective was to replace and enhance the existing analytical capabilities and create client-managed data visualization in-house
Constructed three – tier analytics data mart and executed ETL processes to achieve dependable, reliable integration of data for visualization
Benefits realized from building an analytics data mart out numbered client’s stated requirements
Tremendous improvement in data visualization performance and reduction in data storage cost