Solis Data Manager

• BPMSoft
• Colvir Software Solutions

Solis Data Manager (SDM) is a data management platform built on the DAMA-DMBOK framework to solve data quality, ownership and accessibility problems at Solis Investimentos. Using big data technology, SDM delivers trusted, near real-time information to business teams, enabling faster and more reliable decisions in a regulated financial environment.

SDM creates a single, governed foundation for corporate data. It applies DAMA-DMBOK practices, including [data governance, data quality, metadata management], with clear ownership by business domain and governance built into data delivery rather than added afterwards.

The platform is designed to scale across domains and use cases, laying the groundwork for advanced analytics and responsible AI adoption.

Since its launch, SDM has transformed how Solis uses data. Report delivery time dropped from 5 days to 30 minutes, while 10% of critical data elements now have a defined owner and business definition. Automated quality rules cover [N] datasets, raising data quality scores from 10% to 20% and cutting manual reconciliation effort by 100 hours per month. 10 business areas and 100 users now access governed data through a single platform, and 100 dashboards and APIs run on SDM data. Decisions that once relied on end-of-day or end-of-week reports are now supported by information refreshed every 30 minutes. Beyond efficiency, SDM strengthened regulatory readiness through [lineage and audit traceability for LGPD/CVM/BACEN reporting] and prepared Solis for responsible AI adoption, with 10 use cases already planned or in development.

SDM runs on a cloud-based big data architecture organized in four layers. Ingestion: Apache Kafka and Debezium (change data capture) stream data from core systems, portfolio management platforms, CRM and ERP. Storage and processing: Databricks (Delta Lake and Apache Spark) on [Azure/AWS], following a lakehouse model. Governance and quality: Microsoft Purview (catalog, lineage and metadata) and Great Expectations (automated data quality rules) support the DAMA-DMBOK practices of [data governance, data quality, metadata management]. Consumption: Power BI and REST APIs deliver trusted data to business users. Security: Microsoft Entra ID for identity and access management, encryption at rest and in transit, and audit logging, aligned with LGPD. No specialized hardware is required: the platform is fully cloud-based and operated by a team of 100 people.

SDM’s complexity came from three fronts. Technical: consolidating data from 20 heterogeneous systems, including legacy platforms with inconsistent formats and definitions, into a single architecture with low-latency delivery. Organizational: adopting DAMA-DMBOK required defining data owners and stewards across business areas, agreeing on shared definitions, and moving data from an IT concern to a business responsibility. Regulatory: every design decision had to meet LGPD and the security requirements of a regulated financial institution, with traceability and access control from day one.

To manage this, delivery was phased, starting with [priority domains] to prove value before scaling, and governance and technology advanced in parallel, so ownership and quality rules were in place as each source was onboarded. Main challenges overcome: [e.g., legacy integration, data quality remediation, stakeholder alignment]. Delivered by a team of 20 in 2 months.

Solis Data Manager (SDM) is Solis Investimentos’ enterprise data management platform, built on the DAMA-DMBOK framework to solve long-standing data problems: inconsistent definitions, unclear ownership, uneven quality and slow access to information. Its goal is to give business teams trusted, near real-time data using big data technology.

SDM consolidates data from core systems, portfolio management platforms, CRM and ERP into a single governed foundation. Data is organized by business domain, each with defined owners and stewards, and quality rules, metadata and lineage are managed as part of data delivery. Business areas consume the data through dashboards, APIs and self-service analytics, with latency of minutes.

The platform is in phased rollout and covers priority domains such as clients, investment products and portfolios, and financial operations. It also creates the foundation for advanced analytics and responsible AI adoption, supporting faster, more confident decisions in a regulated financial environment.

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