1. / A large container operator implements centralized data warehouse to improve data quality by 30%
Overview

Since 1996, the Client has been the world’s largest container ship and supply vessel operator. As part of a Danish business conglomerate with operations in the transportation, logistics, and energy sectors, the head of clusters required that data from all clusters be compiled and analyzed to identify business trends and performance. The client was having difficulty accurately measuring, collating, and analyzing this data based on the information provided by their team. Our solution was to create a centralized data warehouse that would process and store values from various clusters, allowing for proper analysis and insights.

Problem

Besides the complications involved in streamlining the existing infrastructure without disrupting the flow of data, Apexon specialists have discovered that:

  • The client was having difficulty analyzing the business trends and performance of their cluster based on the shipment cycle and customer service provided by their team.
  • There was no Centralized Data Store collating all these data from different clusters which made it difficult to store and analyze the data.
Solution

To address the customer’s requirements, we implemented a centralized data store with capability to collate and handle data volume efficiently.

  • Built a centralized data warehouse to process and store the values for 32 KPIs
  • Designed data extraction and processing routines to handle the multitude of data types and handle data volume efficiently by applying best practices like application of filters, indexing
  • Designed data models to store the values for 11 KPIs
  • Built dashboard to render the KPIs
Impact

At the close of the project, Apexon was able to deliver the following features and upgrades:

  • 30 percent improvement in job-report consistency and data quality
  • 25 percent increase in contracts from existing customers due to improved relationships
  • 25 percent increase in customer-channel reporting built from new EDW.
  • Geographical channels/areas could be identified to work on to improve logistics-transportation, which resulted in the capture of 39 new agreements-customers in just a fiscal year.

Other Case Studies
A large container operator implements centralized data warehouse to improve data quality by 30%

Case Studies

A large container operator implements centralized data warehouse to improve data quality by 30%

Learn how we assisted a Danish business conglomerate with activities in the transport, logistics and energy sectors to implement a centralized Data warehouse to improve their data quality, analyze the business trend and performance.

A major US bank holding company reduced data anomaly and mismatch errors by 60%.

Case Studies

A major US bank holding company reduced data anomaly and mismatch errors by 60%.

Discover how we aided a leading US bank holding company headquartered in Michigan with capability enhancements that ensure a long-term process that reduces data anomaly and mismatch errors, improves operations, and mitigates risks.

Emergency Department – Coding Improvement

Case Studies

Emergency Department – Coding Improvement

Learn how we assisted a leading revenue cycle management services company in the United States in identifying opportunities to improve documentation while also modifying and automating its reconciliation and quality procedures.

US-based Physicians Group Improves ROI by 6X

Case Studies

Healthcare & Life Sciences
US-based Physicians Group Improves ROI by 6X

Learn how we helped a large physicians group based in the US use deep learning models to improve error identification by 3x and reduce financial leakage by 40%.

Let’s head to the apex

Get in touch and let’s start a conversation!






    banner_side