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Big Data & Data Warehouse Solutions

End-to-end data warehouse, data lake, and big data platforms — including cloud integration, data modeling, and migration.

Capabilities

What Big Data & Data Warehouse Solutions Actually Does

Modern Data Lakehouse & Cloud Warehousing Architecture

Scalable cloud-native data lakehouse blueprints (Snowflake, Databricks, BigQuery) to unify structured and unstructured enterprise workloads.

High-Throughput Big Data Ingestion & ETL/ELT Pipelines

Automated batch and real-time streaming ingestion pipelines aggregating data from multi-cloud, ERP and API sources.

Dimensional Data Modeling & Enterprise Data Marts

Star/snowflake schema designs and semantic data marts to accelerate analytical querying and support self-service BI.

Multi-Cloud Data Migration & Platform Modernization

Data platform migrations from legacy on-premises databases to cloud data warehouses, designed to minimize downtime.

Real-Time Data Streaming & Storage Query Optimization

Storage partitioning, indexing and stream processing engines (Kafka, Spark) tuned for query performance at scale.

Under the hood

Technical Details

Lakehouse platforms
Snowflake, Databricks and BigQuery
Stream processing engines
Kafka and Spark
Ingestion
Automated batch and real-time streaming pipelines, ETL/ELT
Sources
Multi-cloud, ERP and API sources
Data modeling
Star/snowflake schema designs and semantic data marts
Storage
Storage partitioning and indexing

Fact Sheet

Covers
Data warehouse, data lake and big data platforms
Architecture
Cloud-native data lakehouse blueprints for structured and unstructured workloads
Ingestion
Batch and real-time streaming pipelines from multi-cloud, ERP and API sources
Modeling
Star/snowflake schema designs and semantic data marts
Migration
From legacy on-premises databases to cloud data warehouses
Optimization
Storage partitioning, indexing and stream processing tuned for query performance at scale
Technologies
Snowflake, Databricks, BigQuery, Kafka and Spark

Frequently Asked Questions

  • Which data platforms does the work use?

    The lakehouse blueprints cover Snowflake, Databricks and BigQuery. The stream processing engines the work tunes are Kafka and Spark.

  • Can a legacy on-premises database be migrated to the cloud?

    Yes. The service migrates data platforms from legacy on-premises databases to cloud data warehouses, in a way designed to minimize downtime.

  • Does the work cover both batch and streaming data?

    Yes. Ingestion pipelines are automated for batch and real-time streaming, aggregating data from multi-cloud, ERP and API sources.

  • Will the warehouse support self-service BI?

    Star/snowflake schema designs and semantic data marts are built to accelerate analytical querying and support self-service BI.

Who Delivers It

Cleo System delivers it, and is your single point of contact and accountability.

How an Engagement Starts

  1. 01

    An inquiry, not a commitment

    Telling us what you are trying to solve commits you to nothing.

  2. 02

    A conversation first

    Someone from Cleo System comes back to you directly to understand the requirement and its constraints.

  3. 03

    Terms in writing

    Any commercial terms are set out in a signed agreement between you and Cleo System.

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