Big Data Architecture

Big Data Architecture That Turns D2C Data into Competitive Intelligence.

D2C brands generating millions of events daily need big data architecture that can ingest, store, process, and serve all that data reliably and cost-efficiently. We design modern data architectures — data lakes, lakehouses, and data mesh — that scale with your D2C growth and enable analytics at any scale.

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Data LakeLakehouseData WarehouseData MeshStreaming IngestionBatch ProcessingData CatalogueGovernanceCost OptimisationQuery PerformanceData LakeLakehouseData WarehouseData MeshStreaming IngestionBatch ProcessingData CatalogueGovernanceCost OptimisationQuery Performance
Big Data Architecture

Scalable Data Infrastructure for Every D2C Analytics Need

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Data Architecture Design
Target-state big data architecture design — choosing between data lake, lakehouse (Databricks, Iceberg), and data warehouse (Snowflake, BigQuery) based on your D2C query patterns and team capabilities.
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Data Ingestion Pipeline
Scalable ingestion pipelines handling D2C event streams, batch loads, and CDC feeds — using Kafka, Kinesis, or Pub/Sub for real-time and Airflow for batch orchestration.
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Data Lake & Lakehouse
Data lake design on S3, GCS, or ADLS with open table formats (Apache Iceberg, Delta Lake) for ACID-compliant, time-travel-capable storage of all D2C historical data.
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Data Warehouse Optimisation
Data warehouse implementation and optimisation on Snowflake, BigQuery, or Redshift — clustering, partitioning, and materialised views for sub-second D2C analytics queries.
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Data Catalogue & Governance
Data catalogue implementation — Apache Atlas, Collibra, or DataHub — providing discoverability, lineage, and governance for your entire D2C data estate.
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Cost Engineering
Big data cost optimisation — query optimisation, storage tiering, compute auto-scaling, and reserved capacity planning to minimise data infrastructure costs at D2C scale.
Petabyte-scale
Architecture handling any D2C data volume without redesign
Sub-second
Query performance on billions of D2C events with proper architecture
Unified
All D2C data in one platform — no siloed data sources
Governed
Data quality, lineage, and access control built into architecture

Frequently Asked Questions

Scale D2C provides Big Data Architecture consulting, architecture, implementation, and managed services tailored for D2C and ecommerce businesses. We design cloud-native solutions that scale with your brand's growth and reduce infrastructure cost as transaction volume increases.

Big Data Architecture moves D2C brands from fixed to variable infrastructure cost, enables auto-scaling during peak trading periods (Black Friday, product launches), and eliminates expensive on-premise hardware. Scale D2C clients typically reduce infrastructure costs by 25–40% within 12 months of Big Data Architecture adoption.

Scale D2C builds Big Data Architecture with security by design — identity and access management, encryption at rest and in transit, network segmentation, vulnerability scanning, and compliance with GDPR, PCI-DSS, and SOC 2 frameworks. Compliance controls are architected in at day one, not retrofitted.

A Big Data Architecture assessment and architecture design takes 2–4 weeks. Full implementation or migration runs 8–20 weeks depending on complexity. Scale D2C uses a phased approach — assess, plan, migrate, optimise — with zero-downtime go-live strategies as standard.

Yes. Scale D2C provides 24/7 Big Data Architecture monitoring, incident response, cost optimisation reviews, security patching, and architectural evolution planning. Our DevOps engineers integrate with your team and take full ownership of Big Data Architecture uptime and performance SLAs.

Scale D2C

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150+ D2C brands scaled. $2B+ in tracked revenue. Since 2004.

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