AI Use Cases

GenAI Accelerator

Future-ori­ented data ana­lysis with ana­lyt­ical data lakes


Scal­able data ana­lysis gives com­pan­ies a com­pet­it­ive advant­age by enabling fast, data-based decisions. An ana­lyt­ical data lake com­bines struc­tured and unstruc­tured data from vari­ous sources and enables power­ful ana­lyses of large volumes of data.

Descrip­tion


Scal­able data ana­lysis gives com­pan­ies a com­pet­it­ive advant­age by enabling fast, data-based decisions. An ana­lyt­ical data lake com­bines struc­tured and unstruc­tured data from vari­ous sources and enables power­ful ana­lyses of large volumes of data.

Ser­vices

Data-driven decisions




The ana­lyt­ical data lake forms the basis for future-proof, scal­able data ana­lyses. By integ­rat­ing struc­tured and unstruc­tured data from sources such as data­bases, IoT devices and social media, com­pre­hens­ive ana­lyses can be car­ried out. Tech­no­lo­gies such as Apache Hadoop, Apache Spark, Presto and Delta Lake ensure flex­ib­il­ity, auto­ma­tion and scalab­il­ity. Our focus is on real-time data ana­lyt­ics with Apache Kafka, self-ser­vice ana­lyt­ics and ensur­ing data qual­ity through data gov­ernance models. 


synvert sup­ports com­pan­ies in imple­ment­ing cus­tom­ized ana­lyt­ical data lakes that are tailored to their require­ments and use cases. The goal is a power­ful data plat­form that accel­er­ates data-driven decisions and secures long-term com­pet­it­ive advantages.

Com­pon­ents

Ana­lyt­ical Data Lake redefined


synvert integ­rates the ana­lyt­ical data lake seam­lessly into your data strategy. From data import, stor­age and ana­lysis to ensur­ing data qual­ity, the entire data life­cycle is covered. Through self-ser­vice ana­lysis and real-time data pro­cessing, we offer a flex­ible, scal­able strategy that enables data-driven decisions and meets both cur­rent and future requirements.


Scal­able Data Archi­tec­ture – devel­op­ment of a robust ana­lyt­ical data lake with Amazon S3, Google Cloud Stor­age or Microsoft Azure Data Lake to cent­ral­ize and ana­lyze struc­tured and unstruc­tured data.

Data integ­ra­tion and pre­par­a­tion ‑iIn­teg­ra­tion of het­ero­gen­eous data sources (SQL, NoSQL, CSV, JSON) for in-depth ana­lyses in the data lake.

Self-ser­vice ana­lyt­ics – provid­ing a user-friendly plat­form for data-driven decisions with tools such as Tableau, Power BI or Looker.

Auto­ma­tion and orches­tra­tion – imple­ment­a­tion of auto­mated pipelines for data integ­ra­tion with Apache NiFi, data cleans­ing and trans­form­a­tion with Apache Air­flow or dbt.

Mod­ern ana­lysis tools – integ­ra­tion of advanced tools for machine learn­ing (Tensor­Flow, PyT­orch) and arti­fi­cial intel­li­gence (Google AI Plat­form, AWS SageMaker).

Data Qual­ity – ensur­ing data qual­ity through auto­mated tests and con­tinu­ous monitoring.

Advant­ages

Our main advant­ages




Future-proof archi­tec­ture


synvert devel­ops scal­able ana­lyt­ical data lake archi­tec­tures that respond to future require­ments and can be exten­ded with tech­no­lo­gies such as Apache Hadoop and Delta Lake.


High Data Quality


Ensur­ing data qual­ity through auto­mated pipelines and data gov­ernance mod­els for con­tinu­ous mon­it­or­ing and ensur­ing data standards.


Smooth integ­ra­tion


Integ­ra­tion of the ana­lyt­ical data lake into exist­ing envir­on­ments – on-premises, hybrid or in the cloud (e.g. Amazon S3, Azure Data Lake).


Real-time cap­ab­il­ity


Imple­ment­a­tion of stream­ing func­tions with tech­no­lo­gies such as Apache Kafka for real-time data ana­lysis and integration.


Com­plex plat­form perspective 


Cov­er­ing the entire data life­cycle from extrac­tion to final ana­lysis for an end-to-end solution.


Self-ser­vice optimization


Pro­vi­sion of plat­forms that enable self-ser­vice ana­lysis with tools such as Tableau and Power BI.


Scalab­il­ity and flexibility


Ana­lyt­ical data lakes, which offer high scalab­il­ity thanks to flex­ible cloud solu­tions to keep pace with grow­ing data volumes and chan­ging busi­ness requirements.


Mod­ern ana­lysis tools and AI integration


Use of advanced ana­lysis tools and AI tech­no­lo­gies such as Tensor­Flow and AWS Sage­Maker to gain deeper insights from the data and integ­rate machine learn­ing mod­els dir­ectly into the data lake.


Cost effi­ciency


With flex­ible cloud solu­tions such as Amazon S3, Google Cloud Stor­age or Microsoft Azure Data Lake, com­pan­ies only pay for the capa­city they actu­ally use and can scale as required.

Tools

Our tools




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