Institutional investors are under constant pressure to generate alpha, however many continue to rely on the same structured data sources that have fueled the industry for decades. The problem? Traditional market data alone no longer provides a competitive edge.

While structured datasets, such as price feeds, earnings reports, and economic indicators, remain essential they tell only part of the story. The alternative data market is projected to grow from $20 billion today to $137 billion, according to Deloitte, while traditional data is expected to plateau at $72 billion. The message is clear: Firms that fail to integrate alternative data risk falling behind, while those that embrace AI-powered analytics can gain a decisive advantage.

Unlocking Market Intelligence Beyond Structured Feeds

To extract deeper, more actionable insights, firms should consider alternative data sources, such as the following examples:

  • Social media sentiment: Data from platforms like X (formerly Twitter), Reddit, and LinkedIn can be licensed for use by AI to detect real-time shifts in market sentiment.
  • Satellite imagery and geolocation data: Hedge funds analyze shipping traffic, industrial activity, and retail foot traffic to predict macroeconomic trends.
  • Earnings call transcripts and news analysis: Natural language processing (NLP) models extract hidden sentiment from corporate statements.
  • Internet of things (IoT) sensor data: Firms track supply chain activity to assess potential disruptions before they impact valuations.

When combined with traditional structured data and AI-driven models, these alternative datasets can help investors anticipate market shifts, uncover new investment opportunities, and move faster than the competition.

GPUs and AI Accelerate Market Data Analytics

As alternative data sources continue to grow in complexity and volume, firms need faster, more powerful analytics to process them in real time. GPUs become a game-changer in the following areas:

  • Accelerated model development: GPUs dramatically speed up AI model training and backtesting, reducing timeframes from weeks to hours.
  • Real-time analysis at scale: You can now perform real-time AI-powered sentiment analysis, risk modeling, and NLP-driven analytics.
  • Cost-effective scaling: Cloud-based GPU platforms enable firms to analyze massive datasets without overinvesting in on-premises infrastructure.

However, unlocking AI’s full potential requires more than just technology. It also demands the right cloud strategy and access to specialized expertise.

Closing the AI Talent Gap with the Right Cloud Partner

One of the biggest obstacles to fully utilizing alternative data isn’t just technology—it’s talent. Managing GPU clusters is complex enough, requiring deep expertise in lifecycle operations and capacity scaling. But when you factor in the challenge of integrating and analyzing both structured and unstructured data for AI-driven trading strategies, the need for highly specialized personnel becomes even more critical. These professionals, skilled in AI infrastructure, data engineering, and quantitative research, are in short supply and high demand across industries, making it increasingly difficult for firms to attract and retain them.

But keeping infrastructure available isn’t the goal. Using it effectively to generate alpha is. Partnering with a proven, high-performance cloud service provider (CSP) lowers the operational burden of maintaining and optimizing GPU-based AI solutions. Instead of diverting resources toward managing infrastructure, firms can focus on assembling the right talent to extract actionable insights, refine predictive models, and create real value in the market.

By offloading the complexity of infrastructure management, institutional investors can shift their attention where it matters most: turning data into an edge to achieve alpha.

How OCI Powers AI-Driven Market Intelligence

As alternative data adoption accelerates, cloud infrastructure is a strategic necessity. Oracle Cloud Infrastructure (OCI) offers a purpose-built AI cloud accelerated by NVIDIA for institutional investors and provides the following features and benefits:

  • Bare metal GPU computing accelerated by NVIDIA: High-performance AI with no artificial caps on compute power.
  • Low-latency, high-speed networking: Essential for real-time financial analysis.
  • Cost-effective AI processing: No hidden data egress fees, unlike other providers, reducing unpredictable cloud costs.
  • Multi-cloud flexibility: Avoids vendor lock-in while seamlessly integrating with existing investment technology stacks.
  • End-to-end data science workflows: Accelerate data processing and model training with NVIDIA AI Enterprise on OCI.

With OCI’s AI-ready cloud, firms can process alternative data at scale, run AI models faster, and maintain cost efficiency.

The Future of Market Analytics: Act Now

The shift to AI-powered alternative data analytics is no longer optional. It’s inevitable. The question isn’t whether firms adopt it: It’s how quickly they can integrate it. Stay ahead of the markets, and harness AI and alternative data today.

For more information, see the following resources:

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