Asset Managers Need More Than Fast Data. They Need Trusted Data.
Every investment decision depends on data. Whether evaluating portfolio performance, monitoring market exposure, or managing risk, asset management firms rely on timely market data to make informed decisions.
The challenge is that speed alone is not enough.
A market data platform that delivers information quickly but lacks governance creates risk. A platform that prioritizes governance but cannot keep pace with business demands delays decisions and reduces value. Data leaders need both: market data that keeps pace with intraday decisions, captured continuously rather than on a batch window, and confidence that every number can be trusted, audited, and explained.
Unfortunately, many organizations still struggle with fragmented ingestion pipelines, manual lineage tracking, custom integrations, and data quality issues that consume valuable engineering resources. New data sources often require significant engineering effort, while audit requests trigger time-consuming investigations into data origins and transformations.
Built by Perficient, a Databricks Lakeflow Brickbuilder Specialized partner, Assetflow addresses these challenges with a repeatable, production-ready framework for ingesting, validating, governing, and serving market data on the Databricks Data Intelligence Platform.
Why Asset Managers Care
Assetflow helps organizations:
- Accelerate onboarding of new market data sources
- Reduce operational complexity through managed ingestion and serverless infrastructure
- Improve confidence in analytics through built-in lineage and data quality controls
- Support regulatory and audit requirements with centralized governance
- Deliver analytics-ready market data faster to traders, portfolio managers, and risk teams
Instead of building and maintaining custom pipelines, teams can focus on producing insights and data products that create business value.
What Is Assetflow?
Assetflow is Perficient’s source-agnostic Databricks Lakeflow accelerator for asset management. It ingests intra-day market data from source systems, replicates changes through change data capture (CDC), applies data quality controls, and delivers analytics-ready datasets through a governed medallion architecture.
The accelerator is both configuration-driven and metadata-driven. Pipeline logic is not tied to individual instruments, entities, or vendors. Organizations can therefore adapt the framework to changing business requirements without redesigning core architecture.
More importantly, Assetflow incorporates lessons learned from production implementations, including:
- CDC source handling
- Environment promotion
- Credential governance
- Checkpoint management
- Operational monitoring
These are the factors that determine whether a proof of concept successfully scales into production.
A Governed Path from Source to Insight
Assetflow provides a repeatable framework for moving market data from ingestion to analytics while maintaining governance across every stage.
While client environments differ, the underlying pattern remains consistent. Data may originate from relational databases, APIs, cloud storage platforms, messaging systems, or proprietary market feeds. Assetflow abstracts these differences using Lakeflow ingestion services while preserving a common governance and transformation model.
The architecture includes four core layers:
Ingest
Lakeflow Connect replicates source data into Bronze tables using CDC. Instead of relying on scheduled batch transfers, source changes are continuously captured and reflected in the platform.
Transform
Lakeflow pipelines process data through Silver and Gold layers using a governed medallion architecture. Data is validated, enriched, modeled, and prepared for analytics consumption.
Orchestrate
Lakeflow Jobs manages dependencies and execution sequencing, ensuring reliable pipeline operation across environments.
Govern
Unity Catalog provides centralized governance, including credentials, schemas, column-level lineage, data access controls, row filters, and masking policies. Governance is embedded from ingestion through consumption rather than added later as an afterthought.
A key differentiator is that the architecture is serverless throughout, reducing infrastructure management overhead and allowing engineering teams to focus on delivering value instead of maintaining platforms.
Faster Ingestion with Lakeflow Connect
One of the biggest challenges facing data teams is onboarding and maintaining source integrations.
Assetflow uses Lakeflow Connect to simplify this process through managed ingestion services that handle schema evolution and CDC processing while leveraging Unity Catalog for credential governance.
For data leaders, the business benefit is straightforward: adding new sources becomes a configuration exercise rather than a custom integration project. This reduces ongoing maintenance requirements and accelerates time-to-value for new analytics initiatives.
Built-In Data Quality Before Analytics Begin
One of the most costly data platform failures occurs when poor-quality data reaches downstream analytics and business users.
Assetflow addresses this challenge by validating records before they advance through the pipeline. Quality expectations are enforced during Silver-layer processing, ensuring that malformed records are identified before they can affect reporting, risk calculations, or trading analytics.
Examples include validation of:
- Ticker symbols
- Trade timestamps
- Price values
- OHLC relationships
- Transaction volumes
The result is greater trust in downstream analytics and a more defensible foundation for regulatory and audit requirements.
Production-Ready Governance and Deployment
Many accelerators demonstrate technical concepts. Fewer address the operational realities of enterprise deployments.
Assetflow was designed with production in mind, including:
- Environment promotion
- Pipeline observability
- Infrastructure-as-code deployment
- Lineage visibility
- Restart and recovery handling
- Idempotent pipeline processing
Lakeflow Jobs and Declarative Automation Bundles enable consistent deployment patterns across environments, helping organizations move from experimentation to production more efficiently.
Beyond Asset Management
While Assetflow was built using market data use cases, the underlying pattern is broadly applicable.
Organizations in manufacturing, retail, banking, and other industries face many of the same challenges:
- Data ingestion complexity
- Governance requirements
- Data quality management
- Analytics readiness
The specific source systems may change, but the governed path from ingestion to analytics remains consistent.
Why Perficient
Organizations evaluating Lakeflow initiatives need more than technology. They need proven implementation experience.
Perficient has earned Databricks Brickbuilder Specializations for Lakeflow, Security & Governance, Data Warehouse Migration, and AI. Assetflow represents the practical application of that expertise, packaging proven architecture and implementation patterns into a reusable accelerator designed to help clients accelerate adoption and reduce delivery risk.
Ready to Modernize Market Data Delivery?
When data teams spend more time maintaining ingestion pipelines than delivering insights, the challenge is often not the platform. It’s the pattern.
Assetflow enables asset managers to accelerate market data onboarding, strengthen governance, improve trust in analytics, and deliver analytics-ready data faster on Databricks Lakeflow.
To learn how Assetflow can be adapted to your organization’s market data ecosystem, visit Perficient’s Databricks practice and start the conversation.
