Data Ingestion
Data Modeling & Transformation
Analytics & Reporting
Data Warehouse Migration
Analytics Platform for External Vendors and Internal Systems
Scalable, Cloud-native Data Engineering Platform
lower latency with Zero ETL ingestion
faster reporting using standardized models
less manual data work
lower warehouse costs after Redshift migration
reliable data with automated dbt tests
As the organization grew, data became one of its most valuable assets and also one of its biggest challenges. Information flowed in from multiple external vendors and internal systems, but differences in structure, quality, and timing made it difficult to trust analytics or scale reporting.
AcmeMinds partnered with the organization to design a modern data engineering platform that brought order, consistency, and scalability to this complex data ecosystem. The result was a reliable analytics foundation that supports confident decision making while keeping costs under control.
When Data Growth Outpaced the Platform
In the early stages, the organization’s analytics needs were manageable. Over time, as more vendors were added and reporting demands increased, several issues began to surface. Data arrived in different formats and at different times. The same metrics were calculated differently across reports. Analytics teams spent more effort fixing data issues than delivering insights.
What was meant to enable better decision making gradually became a bottleneck for both client reporting and internal operations.
Why Data Engineering Became Critical
The core problem was not data availability. The real issue was the absence of a strong data engineering foundation.
Without standardized ingestion, transformation, and modeling, reports produced inconsistent results. Onboarding new vendors required repeated manual effort. Increasing data volumes drove up warehouse costs without delivering proportional business value. The organization needed a platform that could scale smoothly as the business grew rather than slowing it down.
AcmeMinds worked closely with stakeholders to define a clear objective.
The goal was to build a single scalable analytics platform that delivers consistent metrics, supports multiple reporting needs, and remains cost-efficient as data volume increases.
This required designing not just pipelines, but a dependable system that teams could rely on every day.
AcmeMinds implemented a layered, cloud-native data architecture focused on simplicity, reliability, and long-term maintainability.
Operational data from systems such as Amazon Aurora is continuously ingested into Amazon Redshift using Zero ETL replication.
This approach provides near real-time access to source data, reduces operational complexity, and preserves raw data for traceability and audit purposes.
As a result, data is consistently available when teams need it, without fragile ingestion workflows.
Raw data on its own does not create value. The transformation layer is where data engineering delivers meaningful impact.
Using dbt, AcmeMinds implemented structured transformations that move data through clearly defined stages. Incoming vendor data is cleaned and standardized. Shared business logic is applied, and data from multiple sources is combined. Analytics models are then created using fact and dimension tables designed around a star schema.
With dbt, all transformations are version controlled, tested, and documented, making data quality visible and repeatable.
The resulting fact and dimension tables now serve as a single source of truth for the organization.
They support client-facing reports, internal dashboards, and operational analytics. Because metrics are defined once and reused consistently, teams spend less time questioning numbers and more time acting on insights.
Following implementation, teams gained faster access to reliable, consistent data. Manual effort in analytics and reporting was significantly reduced. New vendors could be onboarded more quickly. Data warehouse costs were lowered. Confidence in data driven decision making improved across the organization.
The most significant change was not just a technical improvement, but the trust teams developed in the data they relied on.
It’s rare to find a technology partner like AcmeMinds. Their team adopts a comprehensive, detail-oriented approach to our project. They listen attentively, pose insightful questions, and swiftly understand the business goals and technical environment. This enables them to create solutions that genuinely meet client objectives and produce significant results. It has been a true pleasure collaborating with AcmeMinds. They consist of bright individuals who are truly invested in achieving positive outcomes.
If your data is growing faster than your analytics capabilities, it may be time to strengthen the foundation. AcmeMinds designs and builds data engineering platforms that scale with your business and transform complexity into clarity.
Designing and building web & mobile app experience
