Data Engineering

Data engineering deals with all the processes, paradigms, and tools for designing and implementing solutions for managing the entire lifecycle of data.

Vedi le technologies Data Engineering

Contatti di riferimento

Andrea Gioia

Chief Technology Officer

Pietro La Torre

Strategy & Business Development

he cross-cutting and heterogeneous nature of this discipline implies criticality and complexity for organizations. It requires a wide variety of knowledge of very different tools, typically rapidly and continuously evolving.

Among the aspects to be covered are:

Data movement from source to destination
Access control and segregation of information
Data processing, transformation, and enrichment
Orchestration and automation of data flows
Governance, from the inventory of the meaning of the data to their physical location, from mapping between physical and semantic form to lineage for tracing their diffusion, from data quality to consent management

For the success of the data strategy, it is also crucial to be able to design scalable and reliable data architectures, prioritize polyglotism, and reduce lock-in.

Technologies Data Engineering

Data Engineering

Qlik Replicate emerges as a robust and versatile solution for organizations seeking to maintain a competitive advantage in today's digital landscape. As Quantyca, as an Elite partner, we support our clients in the design and development of architectures that maximize the value derived from using Qlik Replicate, embracing its event-driven approach.

Data Engineering

Data Engineering

Come as a Databricks partner, we follow the design, implementation, testing and release phases of solutions based on the Lakehouse paradigm taking advantage of the flexibility, scalability and reliability of Databricks services

Data Engineering

Data Engineering

Quantyca has been a premium partner of Confluent since 2015, with numerous active solutions in the retail, utilities, industries and FSI sectors

Data Engineering

We have been Select Partner Snowflake since 2018 and follow our customers from the evaluation phases to the design and implementation of data warehousing and data lake solutions

Data Engineering