EverestDx | Success Stories

Case Study

Multinational consumer product group modernizes their dataware house to improve resiliency and reduce cost

About The Customer

A leading multinational consumer product group wanted to move their terradata datawarehouse to a cloud based solution.

Key Challenges

Cost Concerns: Legacy on-prem Data warehouse systems were expensive to support & scale with agility.

Performance Plateau: These systems had already peaked out on their performance with maxed out single cluster creating bottlenecks.

Data Analytics Gaps: Lack of advanced analytics lead to gaps in insights and inconsistent performance hindering prompt, data business descisions.

Resilience Issues: Lack of High Availability & Disaster Recovery strategy led to resiliency issues.

Data Integration Issues: Data Integration was becoming a problem with the current environment making data analysis difficult and time consuming.

Our Approach

EverestDX undertook a phased approach to migrate the data warehouse solution to the cloud.

our approach

Phase 1 :

Data Foundation Lake Ingestion - Existing Data sources are directly connected to Azure Data Lake Storage through an Enterprise Data Foundation Framework

Phase 2 :

Migrate Teradata warehouse App. Layer data to Azure Data Lake

Migrate Teradata app layer tables and views to ADLS gold path.

Initial migration of 2 years data for large tables

Create Presentation layer tables (Presto / BOBJ / Power BI) for reporting & analysis.

Phase 3 :

Data Transformation

Migrate Teradata ACQ layer tables to the Azure Data Lake Storage

ACQ history load, incremental data retrieval from Teradata

Data Transformation through Databricks cluster, Synapse & Py Spark

Achieve 80% efficiency through DataMutationX automation tool to convert tables/Views, DDLs, BTEQs & Schemas

Scalability, Resiliency & Cost effectiveness through modernization

Moving the data warehouse to the cloud helped the client bring in the necessary scalability factor able to meet any performance bottlenecks, while charging cost against consumption. The new architecture was put in place with High availability and an optimal cloud-based disaster recovery strategy improving overall resiliency. The use of Data Lakes & Lakehouse architecture helped make this solution, future ready.


Resiliency improvement from 99% to 99.99%


Lower platform cost


Data Lake Architecture

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