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AI Use Cases
synvert Accel­er­at­ors
Modern Architecture at waterfront
Suc­cess stories

Com­mu­nic­a­tions, Media & Telecom  - Oper­a­tional Work/Support in Data Warehousing

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About

Com­mu­nic­a­tions, Media & Telecom

synvert provided oper­a­tional sup­port to the cus­tomer in expand­ing and improv­ing the data ware­house, which led to a reduc­tion in errors, a decrease in the time required for ana­lysis and report­ing, and addi­tional insights from new data sources.

Ini­tial situation

The cus­tomer needed oper­a­tional sup­port to expand a data ware­house (DWH) and provide data for stake­hold­ers. The goal was to reduce errors, shorten the time to ana­lysis and report­ing, and gain addi­tional busi­ness insights from the expan­ded DWH.

The exist­ing Amazon Red­shift data ware­house needed to be expan­ded with addi­tional data sources, but the cus­tomer lacked suf­fi­cient tech­nical capacity.

Archi­tec­ture

The data ware­house is built with Amazon Red­shift, using tech­no­lo­gies such as Air­flow, SQL Alchemy, Alem­bic, Git­flow, and Amazon S3.

Gen­er­ated bene­fits

By redu­cing bugs and sta­bil­iz­ing the data ware­house, synvert was able to sig­ni­fic­antly shorten the time for ana­lysis and report­ing, as well as gain addi­tional insights from the newly avail­able data sources.

Ser­vices accom­plished by synvert 

synvert worked oper­a­tion­ally on expand­ing and improv­ing the data ware­house, includ­ing extract­ing, trans­form­ing, and clean­ing data from new sources into the DWH. These sources mainly came from the cus­tom­er’s sales sys­tems. Addi­tion­ally, synvert expan­ded or cre­ated addi­tional data exports accord­ing to the cus­tom­er’s require­ments. The synvert team optim­ized tables for SQL quer­ies and revised the data ware­house accord­ing to soft­ware devel­op­ment best practices.

Categories
All
Tech
Banking
Communications, Media & Telecom
Consumer Goods & Retail
Energy & Resources
Health & Life Science
Industrials
Insurance
Public Sector

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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