Enterprise Data Engineering Platform

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For business organizations to thrive in today's market and stay ahead of the competition, data alone isn't enough. To turn data into business insights, it is extremely critical to trust the data, consolidate it and analyze it for actionable insights.  

Adapting to diverse data formats during integration, coping with escalating data volumes for storage, and addressing performance issues pose challenges in enterprise data management. The need for flexible infrastructure to handle evolving data loads further complicates scalability. Moreover, insufficient governance hampers data availability, integrity, usability, and security within organizations. This has led to a growing demand for Data Engineering Platforms that offer centralized and integrated solutions to collect, store, manage, and analyze large-scale data sets.

Nagarro's Data Engineering Platform simplifies data management and enhances data quality through standardized intake, sharing, and storage.  It helps enterprises gain increased data security, integration, control, and allows for more efficient data sharing, internally and externally. By leveraging DEP, organizations can analyze data swiftly and efficiently, enabling data-driven decision-making.

why DEP?

Low code

Ensures swift development of data integration pipelines with intuitive visuals, reducing development costs. Drives fast application development, better productivity, accessibility for non-technical users, scalability, and flexibility

Multi-cloud single codebase

Effortlessly operates in a multi-cloud environment that empowers you to write code once and deploy it across various cloud platforms, eliminating the need for extensive modifications

Cloud agnostic

Migrates seamlessly between multiple cloud platforms without service disruption with architectural design and scales on demand with fully managed and serverless cloud services

PaaS integration

Seamlessly integrates with various PaaS offerings, empowering users to use multiple services and resources. Allows greater customization and optimization of data integration workflows

Imperative to declarative

Describes the programs to be executed by leveraging Declarative programming. Focuses on the desired data outcome by ensuring efficient data processing and seamless transformation

Data mesh design

Utilizes decentralized data ownership, self-serve infrastructure, federated data governance, and data reliability to enable collaborative data exploration. This further promotes scalability, agility, and a decentralized data culture

Declarative AI integration

Enables seamless integration of AI within the platform, focusing on desired outcomes and enhancing flexibility and scalability

Accelerated development and testing

Delivers faster development and testing. Save your workflows and edit them in different engagements. Extend capabilities with your pre-extended workflows

platform features

Data ingestion & transformation

Facilitates seamless integration of various data sources, into a single, standardized format

Data pipeline automation

Enhances efficiency, reliability, and scalability in data processing workflows

Data quality

An in-built data quality framework assesses data quality issues and executes automatic improvements

Pre-processing & real-time processing

Pre-processing ensures data quality and compatibility. Real-time processing enables ingestion, analysis, and transformation of data with minimal latency

Cloud & resource provisioning

Functions and mathematical expressions that plans resources for cost savings and the most optimized cluster spawning

AI integration

AI/ML application in the ETL process and the data ecosystem for improved effectiveness and efficiency, automation, and insights.

featured success story

Higher efficiency & productivity through a unified data platform

Nagarro built a unified data platform that delivered higher efficiency, productivity, increased collaboration, and data standardization.

read success story

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