AI Use Cases

GenAI Accelerator

Trans­form­ing raw data into know­ledge through data engineering


Data engin­eer­ing in data man­age­ment ensures that data is seam­lessly integ­rated, pro­cessed and made access­ible for valu­able ana­lyses and busi­ness insights. 

Descrip­tion


Data engin­eer­ing in data man­age­ment ensures that data is seam­lessly integ­rated, pro­cessed and made access­ible for valu­able ana­lyses and busi­ness insights. 

Ser­vices

Effi­cient data man­age­ment for max­imum insights 




Data engin­eer­ing is at the core of any data-driven busi­ness and involves the design, devel­op­ment and optim­iz­a­tion of data pipelines that effi­ciently col­lect, trans­form, store and deliver data. It forms the basis for ana­lyt­ics, machine learn­ing and busi­ness intel­li­gence by ensur­ing that data is of high qual­ity, con­sist­ent and avail­able in real time.


synvert helps com­pan­ies to build robust and scal­able data infra­struc­tures that can be oper­ated on-premises, hybrid or in the cloud. With a focus on mod­ern tech­no­lo­gies, best prac­tices and the integ­ra­tion of stand­ard tools such as Apache Kafka, Air­flow, Spark, Snow­flake or dbt, high-per­form­ance and flex­ible data solu­tions are developed. The aim is to optim­ize data pro­cessing, reduce oper­at­ing costs and enable data-driven innovation. 

Com­pon­ents

Core com­pon­ents of data engineering


The indi­vidual build­ing blocks of Data Engin­eer­ing cover all key areas of Data Pro­cessing – from integ­ra­tion and trans­form­a­tion to stor­age and monitoring.


Data Integ­ra­tion and Extrac­tion – devel­op­ment of ETL and ELT pipelines that seam­lessly integ­rate data from internal and external sources. Typ­ical tools: Talend, Fiv­etran, Inform­at­ica, AWS Glue.

Stream pro­cessing and real-time Data Pro­cessing – devel­op­ment of stream­ing solu­tions for real-time data ana­lysis and event-based sys­tems. Typ­ical tools: Apache Kafka, Apache Flink, AWS Kin­esis, Google Dataflow.

Data Pro­cessing and trans­form­a­tion – use of power­ful frame­works to pro­cess raw data and pre­pare it for ana­lysis or machine learn­ing. Typ­ical tools: Apache Spark, dbt, Azure Data Fact­ory, Pandas.

Data Archi­tec­ture and stor­age – design of data archi­tec­tures (data lake, data ware­house, data mesh) and selec­tion of suit­able stor­age solu­tions. Typ­ical tools: Snow­flake, Google BigQuery, AWS S3, Azure Syn­apse Ana­lyt­ics, Delta Lake.

Mon­it­or­ing and qual­ity assur­ance – imple­ment­a­tion of sys­tems to mon­itor data qual­ity and pipeline per­form­ance. Typ­ical tools: Great Expect­a­tions, Monte Carlo, Datadog, Prometheus.

Orches­tra­tion and auto­ma­tion – set up auto­mated work­flows to effi­ciently orches­trate and mon­itor data pipelines. Typ­ical tools: Apache Air­flow, Pre­fect, Luigi, Dagster.

Advant­ages

Our main advant­ages


Thanks to our com­pre­hens­ive expert­ise and state-of-the-art tech­no­lo­gies, synvert guar­an­tees high-per­form­ance, future-proof and cost-effi­cient data engin­eer­ing solu­tions. The bene­fits range from flex­ible scalab­il­ity to ensur­ing high Data Quality. 



Scal­able data pipelines


synvert devel­ops data pipelines that are flex­ible and robust to cope with grow­ing data volumes and chan­ging require­ments – regard­less of whether batch or real-time pro­cessing is involved. 


Cus­tom­ized tool selection


With a broad tech­no­logy port­fo­lio, synvert selects the optimal tools for the use case, e.g. Spark for big data trans­form­a­tions or Kafka for event streaming.


Optim­iz­a­tion of Data Quality


The use of mon­it­or­ing and test­ing tools such as Great Expect­a­tions or Datadog ensures the con­sist­ency and reli­ab­il­ity of the data – a decis­ive factor for ana­lyses and decisions.


Cloud-nat­ive solutions


synvert integ­rates state-of-the-art cloud tech­no­lo­gies to build flex­ible and cost-effect­ive data plat­forms that work with AWS, Azure or Google Cloud. These plat­forms can be eas­ily scaled and seam­lessly expanded. 


Future-proof archi­tec­ture


The devel­op­ment of mod­u­lar archi­tec­tures that can be flex­ibly adap­ted to new tech­no­lo­gies, data sources and busi­ness require­ments guar­an­tees long-term invest­ment security. 


End-to-end approach


synvert accom­pan­ies you through the entire pro­cess – from require­ments ana­lysis and tool selec­tion to pipeline devel­op­ment, mon­it­or­ing and con­tinu­ous optimization. 

Tools

Our tools




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