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60 mins
Data mesh breaks a centralized data platform into smaller chunks categorized by domains. These decentralized teams are responsible for managing, owning, and serving their domain data as products. Data mesh brings domain-based data ownership that increases accountability, leading to higher data quality and faster use-case implementation. It makes data discoverable and easily accessible across the organization. Data mesh can solve many challenges posed by centralized data architecture. However, does it meet your organizational needs
Knowing and understanding the tradeoff between the efforts of implementation and its benefits is essential. It requires a comprehensive assessment and approach to ingest, process, govern, and consume data. Nagarro has helped multiple customers by performing data mesh assessment and implementation to shift from monolithic to domain-driven implementations.
Data lakehouse combines the best elements of data lakes and data warehouses. It delivers data management and performance of a data warehouse with low-cost, flexible object stores of a data lake. It simplifies the architecture by eliminating data silos that traditionally separated data analysts and data scientists by adopting a multi-layered approach and providing a unified platform with a single source of truth. The advantages include improved data latency, providing a unified platform that brings data scientists, data analysts, and business users on a single platform, facilitating fine-grained data governance, and improving data utilization across the organization.
An end-to-end data management solution that offers a unified architecture with integrated technologies to effectively integrate data from disparate data sources by adopting data virtualization. It allows organizations to build a holistic data view by pulling data from legacy systems, data lakes, warehouses, databases, cloud platforms, apps, and more. Data fabric helps create a unified active metadata repository to explore data characteristics through graphical navigation while implementing data governance and security that assures quality and makes data safely available.
Enabling self-service analytics, improving data scalability, and optimizing operational efficiency
A unified data platform and governed environment to maximize data value.
Building a Data Lakehouse solution on Azure and Databricks for better reporting, visualization, and insights
China 
India 
Japan 
Philippines 
Singapore 
South Africa 
Sri Lanka 
Thailand 
Colombia 
Ecuador 
Mexico 
Austria 
Denmark 
Finland 
France 
Germany 
Hungary 
Norway 
Poland 
Portugal 
Romania 
Spain 
Sweden 
Switzerland 
United Kingdom 
UAE 
Canada 
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