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Indus­tri­als  - Data as a Ser­vice – BI & Big Data CC

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About

Indus­tri­als

synvert developed an open-source solu­tion for a Ger­man car man­u­fac­turer to make data from over 10,000 sources avail­able to any requester, focus­ing on data avail­ab­il­ity, busi­ness under­stand­ing, tech­nical metadata, and decentralization.

Ini­tial situation

The cli­ent, a Ger­man car man­u­fac­turer, had a lot of dif­fer­ent data sources from dif­fer­ent depart­ments and loc­a­tions (10000+).

The vis­ion has been to design a method through which this data could be made avail­able to any requester by con­sid­er­ing the fol­low­ing points:

  • avail­ab­il­ity of data
  • busi­ness under­stand­ing of data
  • tech­nical metadata understanding/availability
  • decent­ral­iz­a­tion

The goal was to cre­ate a high-level solu­tion of the “Data As a Ser­vice” concept, defin­ing the next steps to accom­plish the below mis­sion statement.

Archi­tec­ture

The entire design has been developed using Apache projects/technologies.

  • Mon­it­or­ing: Elast­ic­search, Solr, Zab­bix, Nagios, Sensu.
  • Data Cata­log: Elast­ic­search,  Neo4j, Ori­entDB, MarkLogic.
  • Cache: Apache Ignite, Mem­cached, Gem­Fire, Hazelcast.
  • Deploy­ment man­age­ment: Kuber­netes, Docker, Apache Mesos.
  • Data Ser­vices: API, JDBC, REST­ful, JBoss, Spring.
  • Fed­er­a­tion: Oracle Big Data SQL.
  • Mes­saging:  Kafka, IBM MQ, RabbitMQ.
  • Secur­ity: Hashicorp Vault, Cus­tom made

Gen­er­ated bene­fits

The cus­tomer achieved its vis­ion through mak­ing all cc in order to get faster, bet­ter, and optim­ized pre­dic­tions for all data-related products.

It was estim­ated that manual effort to build data-related products was reduced by 50%. This was accom­plished by mak­ing it pos­sible to access use­ful data simply by sub­scrib­ing to “Data as a Service”.

Ser­vices accom­plished by synvert 

synvert designed a solu­tion using open-source soft­ware through which the rel­ev­ant data can be made avail­able to any requester by con­sid­er­ing the fol­low­ing points:

  • avail­ab­il­ity of data
  • busi­ness under­stand­ing of data
  • tech­nical metadata understanding/availability
  • decent­ral­iz­a­tion
Categories
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Banking
Communications, Media & Telecom
Consumer Goods & Retail
Energy & Resources
Health & Life Science
Industrials
Insurance
Public Sector
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Driv­ing Inter­na­tional Expan­sion for a Lead­ing Online Car Seller
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Accel­er­at­ing Cloud-Nat­ive Devel­op­ment for a Car Manufacturer
Com­mu­nic­a­tions, Media & Telecom

Retail Com­mis­sion Dia­gnostics Anom­aly Detection
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Set­ting up a Reli­able and Power­ful Platform
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Pre­dic­tion of cus­tomer prob­ab­il­ity to churn
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Early Detec­tion of Mech­an­ical Issues
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NLP​ in Auto­mot­ive Reporting
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Oper­a­tional Data Lake
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Real-Time Mar­ket­ing
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Auto­matic clas­si­fic­a­tion of cars by their model
Pub­lic Sector

Dies­el­tech Program
Com­mu­nic­a­tions, Media & Telecom

Data Recon­cili­ation
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Cent­ral­ized Data Warehouse
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Data as a Ser­vice – BI & Big Data CC
Com­mu­nic­a­tions, Media & Telecom

Oper­a­tional Work/Support in Data Warehousing
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Erosion Detec­tion with Com­puter Vision
Com­mu­nic­a­tions, Media & Telecom

Devel­op­ment and Imple­ment­a­tion of a Fully Auto­mated MLOps Platform
Con­sumer Goods & Retail

Pre­dic­tion and Alloc­a­tion Optim­iz­a­tion for sta­tion­ary Channels
Com­mu­nic­a­tions, Media & Telecom

Build­ing a Near Real-Time Recom­mend­a­tion System
Con­sumer Goods & Retail

Migra­tion AWS data plat­form to Google Cloud
Com­mu­nic­a­tions, Media & Telecom

Design and Devel­op­ment of a Google Cloud-Based Data Platform
Con­sumer Goods & Retail

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

Estab­lish­ment of a Mas­ter Data Man­age­ment Foundation
Indus­tri­als

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
Con­sumer Goods & Retail

Smart Data Catalog

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