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Overview
An investment management firm runs on data that has to be available and protected: trade information, positions, and investor records. For a firm that trades actively, the daily data feeds its reporting depends on cannot quietly fail. The firm partnered with Davis Powers to modernize and automate the pipeline that moves its trade data every day. We built the database behind its trade blotter in Azure SQL, then built an automated Azure Data Factory pipeline to feed it, replacing a set of fragile on-premises scripts. The data a trading desk relies on now moves itself, on secure infrastructure Davis Powers builds and manages.
The Challenge
Trade Data on Fragile, Manual Plumbing
Before our engagement, the firm’s trade data moved on infrastructure that was never designed for an always-available trading operation. The daily trade blotter export was pulled down and loaded by on-premises scripts running on a workstation and a scheduled task, quietly, with no monitoring and no alert when something broke. The firm faced several specific pressures:
- Business-critical trade data moving through brittle on-premises scripts, a WinSCP batch job and a scheduled PowerShell task, each a single point of failure.
- No visibility when a load failed, and no alert to catch it before it reached reporting.
- A trade blotter database that needed to be modernized without disrupting the trading day.
- No durable record of what had already been processed, so a rerun risked duplicate or missing data.
The firm needed a partner who understood both the technology and the reality that a trading operation has no tolerance for a data feed nobody is watching.
The Solution
An Automated, Governed Azure Data Pipeline
Our team designed and built an automated data pipeline in Microsoft Azure to replace the manual scripts.
Azure Data Factory Pipeline
- Built an Azure Data Factory pipeline that runs on a schedule and ingests the daily trade blotter export automatically.
- Deduplicates against files already processed, lands the raw data in Azure Blob Storage as a durable checkpoint, then loads it into Azure SQL.
- Archives each processed file by date with storage lifecycle policies, and sends success and failure notifications, so a failed load is caught immediately rather than discovered later.
Secure by Design
- Held every credential in Azure Key Vault rather than in scripts on a workstation.
- Authenticated the pipeline with a managed identity, so there are no passwords to leak or rotate by hand.
- Scoped access and monitoring across the environment.
The Data Layer
- Built and migrated the database behind the trade blotter into Azure SQL, with a staging, production, and reporting layer.
- Decommissioned the legacy on-premises scripts once the automated pipeline was proven in production.
The Results
Trade Data That Moves Itself, and Is Watched
Following the build, the firm’s core trade-data workflow moved from manual and unmonitored to automated and governed:
- Automated Daily Pipeline: the trade blotter feed loads into Azure SQL on a schedule, with no one running a script.
- Caught Before It Hurts: every run reports success or failure, so a broken load is known immediately.
- Secure by Configuration: credentials live in Key Vault and the pipeline authenticates with a managed identity.
- Durable and Repeatable: raw files are checkpointed and archived, so a rerun never doubles or drops data.
- No Trading Disruption: cut over without interrupting a session, and the legacy scripts were retired only after the new pipeline was proven.
The firm replaced fragile, unwatched plumbing with an automated data workflow it can trust, on infrastructure that is secure, monitored, and managed.
Conclusion
The Secure Azure Foundation Your Workflows Run On
For an investment management firm, the data behind the trading day cannot move on scripts nobody is watching. This engagement shows what Davis Powers builds: not just a migration, but an automated, monitored, secure data workflow hosted in Azure, with the database and the pipeline built and managed by one team. It is the same foundation we use to build and govern AI workflows for financial services, with secrets in Key Vault, identity-based access, and monitoring built in from the start. For firms that want their data and AI workflows built to run themselves and prove they are secure, Davis Powers designs, builds, and manages them in Azure.
About Davis Powers, Inc.
Davis Powers, Inc. is a Chicago-based managed service provider delivering managed IT, cloud, cybersecurity, and networking solutions. As a Microsoft Solutions Partner with specializations in Data & AI, Modern Work, and Azure Infrastructure, we build and manage secure cloud data pipelines, automated workflows, and AI governance for financial services firms, commercial real estate operators, and multi-location retailers. With more than 24 years of executing complex IT solutions, Davis Powers builds the accountability layer that lets clients operate with confidence.