Transitioning from Legacy Systems to Databricks Lakehouse Architecture

Nordic’s Leading Logistics Company

Use Case

Legacy migration

Geography

Nordic Region

Problem

The Shift from Legacy to Lakehouse

Industry

Logistics

Uncovering Legacy Warehouse Challenges

Client Overview

A leading logistics company in the Nordic region faced challenges with its fragmented data infrastructure. The presence of 13 separate legacy data warehouse systems led to increased operational costs, complex IT landscapes, and extensive maintenance efforts.

30%

Decreased IT costs year on year

80%

Data engineers time saved

25%

Growth on data adoption

Technology

Before Diggibyte:

Our customer’s analytics landscape was burdened by the presence of 13 separate legacy data warehouse systems led to complexities to IT landscape, increased operational costs, and an extensive maintenance.

After Diggibyte:

By harnessing our profound expertise in Databricks and lakehouse architecture, we’ve established a solid groundwork for the migration process, resulting in cost savings and an overall boost in the organization’s data utilization

Business Challenge

The company’s analytics landscape was burdened by multiple legacy data warehouses, resulting in data silos and inefficiencies. An initial pilot analysis of one warehouse revealed its inability to meet current demands, leading to increased costs and hampered performance.

Solution: Implementing Databricks Lakehouse Architecture

To address these challenges, a comprehensive global lakehouse architecture was adopted using Databricks. This approach unified data from diverse warehouses into a single repository, leveraging Databricks’ capabilities in data engineering, data science, and machine learning.

Impact

30% Reduction in IT Costs:The unified architecture led to decreased IT expenses year over year.
80% Time Savings for Data Engineers:Streamlined processes and improved data accessibility resulted in significant time savings.
25% Increase in Data Adoption:Enhanced data utilization across the organization fostered a data-driven culture.

Conclusion

Migrating to the Databricks Lakehouse architecture transformed the company’s data infrastructure, leading to cost savings, increased efficiency, and better data utilization.