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Data Architecture

Your data is your most valuable asset. We help you use it.

We design and implement modern data architectures on the cloud that enable ingest, transform and analyze information at scale—enabling data-driven decisions and AI use cases.

Data Architecture

Many organizations have data but they cannot access them in real-time, they do not trust their quality, or they do not know how to convert them into insights. Data Architecture Nublit we build the infrastructure that transforms raw data into reliable, available, and actionable information. 

What is included?

Data Lake and Data Warehouse Design

  • Cloud Storage Layered Architecture (raw, curated, consumption).
  • Using services like S3, AWS Glue, Athena, Redshift, or Synapse Analytics, as appropriate for the use case.

Ingestion and transformation pipelines (ETL/ELT)

  • Design and implementation of ingestion processes from multiple sources.
  • Integration with databases, APIs, files, and real-time events.
  • Data transformation, partitioning, and cataloging for efficient analysis.

Data Catalog and Governance

  • Implementation of AWS Glue Data Catalog or equivalent tools
  • Documentation, classification, and access control for data.
  • Data retention, quality, and lineage policies.

Integration with BI and Analytics Tools

  • Connection with tools like Amazon QuickSight, Power BI, Tableau, or others.
  • Enabling dashboards, reports, and ad hoc analysis.

Data Modeling

  • Design of relational, columnar, or semi-structured models.
  • Adaptation based on the volume, frequency, and type of expected inquiries.

Enabling AI and advanced analytics

  • Data architecture preparation for artificial intelligence use cases.
  • Implementation of text-to-SQL, predictive models, and natural language processing (NLP) analytics.
  • Using embeddings with Amazon Bedrock or other services.

Value proposition

Who is this service for?

Organizations that want to stop making decisions blindly and build real analytical capabilities.

Companies looking to enable AI projects but lack the necessary data infrastructure as a starting point.

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