Marketing Data & Analytics Foundation

Enterprises are investing in advanced analytics, AI, personalization, and decisioning systems on AWS. Yet many struggle to scale these capabilities because their marketing data environments evolved incrementally rather than being architected intentionally.

Data is distributed across platforms with inconsistent definitions, fragmented governance, and limited interoperability. Analytics initiatives stall, activation systems lack shared context, and performance reporting is debated rather than trusted.

The Marketing Data & Analytics Foundation on AWS is Credera’s end-to-end engagement model for assessing, designing, engineering, and implementing enterprise marketing data architecture and operating alignment.

This offering delivers both the architectural thinking and the hands-on build required to establish a scalable marketing data foundation on AWS.

What We Deliver

Current-State Assessment: We evaluate existing AWS environments, marketing data sources, ingestion methods, governance posture, and activation integrations. This includes reviewing data engineering workflows, pipeline design, storage patterns, identity handling approaches, and measurement workflows.

Deliverables include a current-state architecture view, maturity assessment, gap analysis, and risk summary.

Target-State Architecture & Design: We define a scalable, AWS-aligned marketing data architecture, including data ingestion patterns, storage strategy, modeling standards, governance controls, and activation integration requirements. This includes detailed solution design documentation, data flow diagrams, integration specifications, and operating model definitions.

Implementation & Data Engineering: Credera engineers and deploys the foundational components required to operationalize the architecture. This includes:

• Building and configuring AWS-native data pipelines using services such as AWS Glue, streaming services, or event-based ingestion • Designing and implementing data lake and warehouse structures on Amazon S3 and Amazon Redshift • Implementing transformation logic, data modeling standards, and curated data layers • Configuring governance controls using AWS Lake Formation and related services • Establishing data access patterns and integration endpoints for downstream systems

Activation & Measurement Enablement - We design and implement integration patterns that connect governed marketing data to personalization platforms, decisioning engines, AI workflows, and advanced measurement use cases.

This includes engineering reverse data flows, API integrations, model input pipelines, and structured reporting datasets that support analytics, experimentation, and closed-loop performance management

Operationalization & Capability Enablement - We establish governance processes, monitoring frameworks, documentation standards, and stakeholder enablement to ensure sustainability.

This includes defining operating cadences, data quality monitoring, access management processes, and ongoing architectural oversight

AWS Alignment

The Foundation leverages AWS-native services such as Amazon S3, Amazon Redshift, AWS Glue, AWS Lake Formation, streaming services, and Amazon SageMaker. Service selection, configuration, and implementation are tailored to each client’s technical landscape, regulatory environment, and performance objectives.