Data Infrastructure Expansion Supports Digital Advertising Growth for U.S. Small Businesses

Bernard Ramirez

Ashmin Ajitav Swain, a Data Engineer at Meta Platforms, has contributed to the development of large-scale data infrastructure designed to improve advertising measurement and interoperability. The data pipelines he invented now drive $6.7 million in new advertising commitments from businesses previously offline, strengthening local economies and expanding employment opportunities from coast to coast.​

As digital marketing becomes increasingly data-dependent, smaller businesses often face challenges accessing sophisticated measurement tools historically available to large corporations. Swain’s engineering efforts addressed gaps in data extraction, transformation, and ingestion processes, helping streamline campaign analytics and reporting workflows.

Building Interoperable Data Systems

Meta required dependable data flows from Salesforce Data Cloud and Marketing Cloud to support campaign performance analysis. In the absence of standardized integration frameworks, Swain designed and implemented scalable pipelines to facilitate structured data exchange across systems.

The resulting infrastructure expanded accessible campaign metadata and reduced reporting gaps, improving visibility across marketing initiatives. Internal teams adopted the framework for experimentation, measurement governance, and analytics standardization. Enhancements in data reliability and latency contributed to faster reporting cycles and more consistent performance evaluation.

During Meta’s 2025 U.S. small business initiatives, improved measurement capabilities supported increased advertiser participation. Businesses engaging with paid advertising for the first time collectively committed $6.7 million in new advertising spend. Mid-sized advertisers recorded higher quarterly platform investment, while broader advertiser segments demonstrated increased average spending, reflecting growing confidence in campaign performance transparency.

Rather than attributing macroeconomic change to a single system, the developments illustrate how improved analytics infrastructure can influence advertiser engagement and platform efficiency.

"While many companies aspire to democratize technology, our job is to actually build the steps—one pipeline, one integration at a time—so that businesses, regardless of size, can climb," Swain explained, summarizing the ethos driving his engineering choices.

Broader Experience in Data Modernization

Prior to his role at Meta, Swain contributed to analytics product development at Gartner Digital Markets. He supported the creation of a Reviews Insights Platform designed to aggregate large volumes of software reviews into structured intelligence for B2B decision-makers. The initiative contributed to recurring revenue growth within the division and provided software vendors with enhanced customer sentiment analysis tools.

At Vanguard, Swain participated in the design of a cloud-based data warehouse supporting the firm’s retail investor group. The transition from legacy systems to automated cloud infrastructure improved reporting efficiency and data accuracy. The project aligned with broader financial sector modernization efforts emphasizing cloud-first strategies and scalable analytics architecture.

Earlier in his career at Infosys, he worked on a digital learning platform serving a global workforce of more than 200,000 employees. The platform focused on standardizing access to training resources and improving internal knowledge distribution across geographies.

​Standardization and Knowledge Transfer

Across roles, Swain’s work has centered on addressing recurring enterprise data challenges, including siloed systems, manual reporting processes, and limited interoperability. By designing reusable data frameworks and automation pipelines, he contributed to improving operational transparency and analytical consistency within large organizations.

In addition to his professional responsibilities, he has participated in mentoring programs, analytics competitions, and technical advisory initiatives aimed at supporting emerging data professionals. These efforts reflect a broader emphasis within the technology sector on knowledge transfer and ecosystem development.

As enterprises continue to expand digital operations, scalable data architecture remains central to improving decision-making, marketing efficiency, and cross-platform integration. Infrastructure-level advancements, while often operating behind the scenes, play a foundational role in enabling measurable growth across digital ecosystems