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Success stories

Consumer Goods & Retail - Migration AWS data platform to Google Cloud

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About

Consumer Goods & Retail

With the expertise of synvert, a leading retail and e‑commerce company migrated its existing data platform from AWS and Cloudera to Google Cloud to optimize costs and leverage modern cloud-native technologies. By developing a data lake in Google Cloud and implementing best practices in software and data development, synvert achieved faster data access and more efficient data aggregation for analysis. This led to significant time savings and an increased frequency of regular business reports, enabling timely business decisions.

Initial situation

The infrastructure and several existing data products need to be shifted from AWS and Cloudera to Google Cloud.

Solution

The goal is to shift a data platform from AWS to Google Cloud. Infrastructure is built up via Infrastructure as Code by terraform / terragrunt. Several data products have been shifted to Google Cloud native services: Data Pipelines based on Apache Spark, SQL-Workloads, Cloudera Pipelines which now are available within Google BigQuery.

Architecture

The architecture is built on Google Cloud using technologies such as Google BigQuery, Google Cloud Composer, Google Cloud IAM, Google Cloud SQL, Google Cloud Storage, Google Compute Engine, Google DataProc, git, GitLab, CI / CD, Scala, Python, Docker, SQL, and IaC (Terraform, Terragrunt).

Generated benefits

The AWS solution could be decomissioned after 1 year.

Vehicle Data Store

SoftwareFactory at a leading automotive software company

DevX Impact at a HR-Tech Company

Driving International Expansion for a Leading E‑Commerce Company

Accelerating Cloud-Native Development in the Automotive Industry

Retail Commission Diagnostics Anomaly Detection

Setting up a Reliable and Powerful Platform

Prediction of customer probability to churn

Early Detection of Mechanical Issues

NLP in Automotive Reporting

Operational Data Lake

Real-Time Marketing

Automatic classification of cars by their model

Dieseltech Program

Data Reconciliation

Centralized Data Warehouse

Data as a Service – BI & Big Data CC

Operational Work/Support in Data Warehousing

Erosion Detection with Computer Vision

Development and Implementation of a Fully Automated MLOps Platform

Prediction and Allocation Optimization for stationary Channels

Building a Near Real-Time Recommendation System

Migration AWS data platform to Google Cloud

Design and Development of a Google Cloud-Based Data Platform

Refactoring, shift and new development of Data Services in Google Cloud

Establishment of a Master Data Management Foundation

Central Data Lake

Replacement of a complex IBM Datastage structure

CRM analytics and lead management

Standardization of evaluation processes

Development of an ERP data hub

Establishment and further development of a DWH

Development of a group-wide BI platform

Establishment of a new sales reporting system

Source data migration with automation of the source data connection

Cloud self-service BI for data-driven corporate management

Development of various ML use cases with AWS

Replacement of an in-house software development

Company-wide data integration

Implementation of real-time data links

Smart Data Catalog

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About

Ini­tial situation

Solu­tion

Archi­tec­ture

Gen­er­ated bene­fits

Vehicle Data Store

Soft­ware­Fact­ory at a lead­ing auto­mot­ive soft­ware company

DevX Impact at a HR-Tech Company

Driv­ing Inter­na­tional Expan­sion for a Lead­ing E‑Commerce Company

Accel­er­at­ing Cloud-Nat­ive Devel­op­ment in the Auto­mot­ive Industry

Retail Com­mis­sion Dia­gnostics Anom­aly Detection

Set­ting up a Reli­able and Power­ful Platform

Pre­dic­tion of cus­tomer prob­ab­il­ity to churn

Early Detec­tion of Mech­an­ical Issues

NLP​ in Auto­mot­ive Reporting

Oper­a­tional Data Lake

Real-Time Mar­ket­ing

Auto­matic clas­si­fic­a­tion of cars by their model

Dies­el­tech Program

Data Recon­cili­ation

Cent­ral­ized Data Warehouse

Data as a Ser­vice – BI & Big Data CC

Oper­a­tional Work/Support in Data Warehousing

Erosion Detec­tion with Com­puter Vision

Devel­op­ment and Imple­ment­a­tion of a Fully Auto­mated MLOps Platform

Pre­dic­tion and Alloc­a­tion Optim­iz­a­tion for sta­tion­ary Channels

Build­ing a Near Real-Time Recom­mend­a­tion System

Migra­tion AWS data plat­form to Google Cloud

Design and Devel­op­ment of a Google Cloud-Based Data Platform

Refact­or­ing, shift and new devel­op­ment of Data Ser­vices in Google Cloud

Estab­lish­ment of a Mas­ter Data Man­age­ment Foundation

Cent­ral Data Lake

Replace­ment of a com­plex IBM Data­stage structure

CRM ana­lyt­ics and lead management

Stand­ard­iz­a­tion of eval­u­ation processes

Devel­op­ment of an ERP data hub

Estab­lish­ment and fur­ther devel­op­ment of a DWH

Devel­op­ment of a group-wide BI platform

Estab­lish­ment of a new sales report­ing system

Source data migra­tion with auto­ma­tion of the source data connection

Cloud self-ser­vice BI for data-driven cor­por­ate management

Devel­op­ment of vari­ous ML use cases with AWS

Replace­ment of an in-house soft­ware development

Com­pany-wide data integration

Imple­ment­a­tion of real-time data links