Sold by: Mactores Cognition Inc
Mactores Data Platform Modernization helps enterprises retire legacy data warehouses, Hadoop clusters, and unstable cloud migrations by re-architecting them into secure, governed, cloud-native data platforms on AWS. Using Aedeon, our proprietary agent platform, and forward-deployed engineers, Mactores accelerates discovery, schema mapping, code conversion, parity validation, cutover, and Day-1 operations across services such as Amazon EMR, Amazon Redshift, Amazon S3, AWS Glue, AWS Lake Formation, Amazon Athena, Amazon SageMaker, and Amazon QuickSight. Customers use this offering to reduce analytics cost, improve performance, modernize data pipelines, and build an AI-ready AWS data foundation.
Overview
Mactores Data Platform Modernization helps enterprises move from legacy data warehouses, Hadoop platforms, inefficient cloud migrations, and fragmented data estates to secure, governed, AI-ready data platforms on AWS. We combine Aedeon, Mactores’ proprietary agent platform for modernization assessment, code transformation, and validation, with experienced AWS data engineers who support architecture, migration, cutover, and operational readiness.
Many modernization programs stall between strategy and implementation. Others complete a pilot but never reach production. Mactores focuses on production outcomes: modernized workloads, validated data parity, operational runbooks, cost controls, governance, and measurable business impact.
Why Data Platform Modernization on AWS
Common triggers include Oracle EDW modernization, Hadoop retirement, Databricks cost optimization, unstable Amazon EMR migrations, fragmented data lakes, limited scalability, slow batch processing, and the need to build governed AI-ready data foundations on AWS.
Mactores helps customers re-architect around cloud-native AWS services instead of simply lifting and shifting legacy inefficiencies. The result is a modern data platform designed for scalable analytics, lower operating cost, improved performance, stronger governance, and future AI and machine learning use cases.
Our Approach
Discovery and Alignment Workshop: Mactores maps the current environment, identifies dependencies and technical debt, reviews data flows and workloads, and aligns stakeholders on the target AWS architecture. The output is a phased modernization plan with risks, effort, cost drivers, and migration priorities.
Proof of Concept: A focused 4-week PoC validates the technical approach in your environment, demonstrates quick wins, and creates stakeholder buy-in before full-scale execution.
Agent-Native Delivery: Aedeon, our proprietary agent platform, absorbs 60–70% of engagement work, discovery, schema mapping, code conversion, parity test generation, and validation that traditional consulting bills against human hours. Forward-deployed engineers own architecture, judgment, and cutover, embedding with your team and carrying the delivery commitment personally.
Parity-Tested Cutover: Migrated workloads are validated before cutover to reduce the risk of data drift, failed jobs, performance gaps, or production surprises.
Day-1 Operational Readiness: Mactores helps customer teams operate the new AWS-native platform with runbooks, monitoring, cost controls, observability, governance, and knowledge transfer in place.
AWS Services We Build On
Mactores designs and implements modern data platforms using AWS services across the data lifecycle, including Amazon EMR, Amazon EMR on EKS, AWS Glue, Amazon Athena, AWS Lambda, Amazon Redshift, Amazon S3, AWS Lake Formation, Amazon Kinesis, Amazon MSK, AWS Database Migration Service, AWS Snowball, Amazon SageMaker, Amazon QuickSight, AWS IAM, AWS KMS, AWS CloudTrail, Amazon CloudWatch, Amazon VPC, and AWS Config.
Architectures may also include open data and lakehouse technologies such as Apache Spark, Apache Iceberg, Delta Lake on Amazon S3, and Presto, depending on customer requirements.
Proven Outcomes
Telecom SaaS modernization: 58% cost reduction across 20 Databricks workspaces migrated to Amazon EMR on EKS, AWS Lake Formation, and Amazon SageMaker Unified Studio in 18 weeks. Six-month run-rate dropped from $1.51M to $635K. Zero rollbacks. Customer owned EMR ops Day 1 post-cutover. Manufacturing modernization: A 180 TB Oracle EDW and Hadoop platform re-architected onto Amazon EMR, Amazon Redshift, and Amazon S3. Annual operating cost reduced from $2.4M to $900K ($1.5M annual savings) with 10x faster query performance supporting 2,000+ analysts and 2–3M daily queries. Engineering effort dropped from 21,000 to 4,500 hours.
Healthcare analytics modernization: Real-time analytics platform built on AWS Glue, Amazon S3, Amazon Redshift, and Amazon QuickSight to power decisions across operational and financial workflows.
Who This Is For
This offering is designed for CTOs, CDOs, data platform leaders, data architects, analytics leaders, and IT executives who need to retire legacy data warehouses, modernize Hadoop or Databricks workloads, stabilize cloud data platforms, consolidate data lakes, improve analytics performance, reduce cost, or build governed AI-ready data foundations on AWS.
Engagement Model
Mactores supports fixed-scope and phased modernization engagements, beginning with assessment and roadmap development and expanding into proof of concept, implementation, validation, cutover, and operational readiness. Final scope, timeline, deliverables, and pricing are defined through a private offer and statement of work based on source systems, workload complexity, data volume, integrations, governance requirements, and target AWS architecture.
Highlights
- Agent-Native AWS Modernization. Aedeon, our proprietary agent platform, absorbs 60–70% of engagement work — discovery, schema mapping, code conversion, parity test generation, and validation — while forward-deployed engineers own architecture, cutover, and Day-1 operations. The result: production data platforms shipped in weeks at a fraction of traditional consulting cost, with fixed-date delivery and Mactores absorbing overage cost for delays within our control.
- Proven outcomes include 50%+ analytics cost reduction, $1M+ annual savings from Oracle EDW and Hadoop modernization, 10x faster query performance, and production cutovers with parity-tested workloads across Amazon EMR, Amazon Redshift, Amazon S3, AWS Glue, and Lake Formation.
- End-to-end AWS-native modernization across ingestion, storage, lakehouse, compute, analytics, ML, security, and governance using services such as AWS Glue, Amazon S3, Lake Formation, Amazon EMR, Amazon Redshift, Athena, SageMaker, QuickSight, IAM, KMS, and CloudWatch.
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For support, contact Mactores at info@mactores.com or visit https://mactores.com/lets-talk . Mactores provides engagement support through assigned delivery leadership, project governance meetings, technical workshops, and post-cutover knowledge transfer. Support scope, response expectations, and escalation paths are defined in the customer’s private offer and statement of work.