Build a modern market and reference data platform on Snowflake
Investment firms depend on market and reference data to price instruments, support portfolio construction, manage operations, satisfy downstream consumers and meet audit expectations. Yet in many organizations, the operating model behind that data remains fragmented. Vendor files arrive in different formats. Critical processing still sits inside aging platforms. Coverage gaps are hard to spot. Business logic is buried in scripts or specialist knowledge. And by the time data reaches consumers across the firm, transparency into quality, lineage and usage has often been lost.
Publicis Sapient helps investment managers replace that complexity with a modern, cloud-based reference data platform on Snowflake—designed to improve both speed and control. The goal is not simply to migrate data from one warehouse to another. It is to create a platform that makes vendor onboarding faster, quality checks more visible, lineage more traceable and data consumption far easier across the enterprise.
Why legacy reference-data processes break down
For many investment firms, reference-data operations have evolved through years of point fixes. New vendors were added one at a time. Validation rules grew around individual feeds. Downstream systems built their own extracts and workarounds. Over time, that creates a familiar set of problems:
Poor transparency into data lineage and utilization across the firm
Restricted data coverage that makes it harder to support expanding business needs
Complex and inconsistent consumption patterns for downstream users and applications
Limited visibility into data quality back to the original vendor file
Heavy auditing requirements that are difficult to satisfy when processes are fragmented
Dependency on legacy platforms and third-party tooling that slow change and increase cost
These challenges are more than operational annoyances. They affect trust in the data itself. If portfolio teams, operations teams and downstream applications cannot easily understand where vendor data came from, what rules were applied and whether it passed validation, every consumer ends up recreating controls of their own. That increases duplication, slows onboarding and weakens enterprise consistency.
A better model: one governed platform for ingestion, processing and consumption
Publicis Sapient helps firms build a next-generation market and reference data platform using Snowflake together with AWS services. This approach brings ingestion, storage, processing, quality validation and access into a more unified operating model.
At the core is a cloud-native platform designed to:
- ingest external vendor datasets at scale
- support Snowpipe-enabled real-time ingestion where speed matters
- remove vendor data processing from legacy environments and store vendor data in Snowflake
- apply transformation and quality checks in a governed, repeatable way
- expose vendor data in a query-accessible source for consumers across the firm
- improve understanding of lineage, utilization and auditability
This matters because a modern platform changes how reference data is operated, not just where it is stored. Instead of managing vendor onboarding, validation and distribution through disconnected tools and manual interventions, firms can create a more controlled, configurable and transparent process from file arrival through enterprise consumption.
Faster vendor onboarding without the usual bottlenecks
Vendor onboarding is often where reference-data programs slow down first. Every new provider can bring a different file structure, delivery schedule, mapping requirement and exception-handling need. In legacy environments, that typically translates into custom development work, long lead times and growing dependency on specialist teams.
Publicis Sapient helps firms address this by building highly configurable onboarding capabilities directly into the platform. In one investment management reference-data program, Publicis Sapient partnered with the client to create an in-house vendor data onboarding application that replaced legacy third-party tools. The result was faster onboarding of new vendor data while reducing licensing dependency.
That kind of capability is important because onboarding should not require a full platform redesign every time a new source is added. A modern platform should allow firms to absorb a broad range of external datasets while maintaining consistency in how those feeds are configured, validated and operationalized.
Metadata-driven processing that reduces dependency on developers
Reference data becomes difficult to scale when business logic is hidden in code and every change must wait for engineering capacity. Publicis Sapient helps firms modernize that model with metadata-based processing.
In the same next-generation platform program, Publicis Sapient built a metadata-based data processing application that enabled analysts to write business logic for vendor data processing and transformation without developer involvement. That changes the operating model in a powerful way. Instead of routing every adjustment through custom code changes, firms can make more of the process configurable, transparent and easier to evolve.
For investment managers, this means faster response to vendor changes, new instruments or updated business rules. It also means the platform can keep pace with business demand without creating the same engineering bottlenecks that constrained legacy reference-data estates.
Data quality that is visible, traceable and trusted
Data quality is one of the biggest pain points in reference-data operations. Firms need confidence that vendor data has been validated before it is used across pricing, security master, reporting or downstream analytics. They also need transparency back to the original file when issues appear.
Publicis Sapient’s approach emphasizes stronger quality validation and clearer transparency into those checks. On Snowflake, quality controls can be embedded into the processing lifecycle so validation becomes part of the platform’s standard behavior rather than an afterthought. That helps firms ensure vendor data has been checked before consumption and makes it easier to trace quality issues back to source.
The benefit is not just better control. It is also faster resolution. When users can see what failed, where it originated and how it moved through the platform, they spend less time chasing issues across siloed systems and more time acting on trusted data.
Lineage and auditability built into the platform
Investment firms operate under constant pressure to explain how data was acquired, transformed and used. That is especially difficult when lineage is incomplete or scattered across multiple tools.
Publicis Sapient helps firms design governed platforms with lineage, access controls and auditability built in from the start. For reference data, that means a clearer understanding of how vendor datasets move from ingestion through transformation and out to consumers. It also means stronger support for auditing needs, since firms can more easily demonstrate what rules were applied and how data was prepared for enterprise use.
This focus on control extends beyond pipelines alone. Publicis Sapient has also helped investment firms build governance capabilities around Snowflake, including role-based access control, monitoring, security, auditing and automation tools for managing platform usage. That combination of platform engineering and governance discipline is critical in regulated environments where speed only matters if it comes with trust.
Consumption that is easier across the firm
Many legacy reference-data environments make downstream consumption unnecessarily difficult. Different teams access different versions. Extracts proliferate. Querying data requires specialist knowledge or custom interfaces. Over time, the consumption layer becomes just as fragmented as ingestion.
A modern Snowflake-based platform addresses that by exposing vendor data in a query-accessible source for consumers across the firm. Instead of forcing every downstream user or application into bespoke retrieval patterns, the platform can provide a more robust and consistent consumption layer. That supports broader enterprise access while preserving the controls investment firms need around entitlements, governance and quality.
The result is a reference-data foundation that serves more than one operational team. It becomes a shared platform for portfolio construction, operations, reporting, analytics and other consumers who need governed access to trusted market and reference data.
How Publicis Sapient delivers the transformation
Publicis Sapient brings together cross-functional teams across engineering, product, quality engineering and experience design to modernize complex data platforms in an agile way. In the investment management reference-data program described in our experience, a 30-member team worked across five tracks to build the next-generation platform.
That delivery model matters because reference-data transformation is not only a technical exercise. It requires product thinking around onboarding and operations, engineering rigor around ingestion and processing, and quality discipline to accelerate releases without compromising control. Publicis Sapient’s teams have also automated testing and release processes to improve the speed at which new features can move into production.
From fragmented process to strategic data platform
For investment firms, the real value of a modern market and reference data platform is not simply modernization for its own sake. It is the ability to onboard new vendors faster, validate data more transparently, understand lineage more clearly and make consumption easier across the enterprise.
Publicis Sapient helps firms turn reference data from a patchwork of legacy processes into a modern cloud platform on Snowflake—one that supports external vendor ingestion, real-time feeds, metadata-driven processing, configurable onboarding, embedded quality controls and governed enterprise access. The outcome is a platform that improves operational efficiency while giving the business stronger transparency, better control and greater confidence in the data it depends on every day.