Why We Built Awaken Analytics: The Data Pipeline Problem

Every trading platform, every quantitative strategy, and every market research tool starts with the same problem: data. Not just any data, but clean, reliable, pre-calculated technical indicators delivered at scale. And if you've ever tried to build this yourself, you know it's one of the most frustrating parts of the entire stack.

This is the story of why we built Awaken Analytics, and why we believe this problem deserves a dedicated solution.

The Problem We Faced

Before Awaken Analytics existed, our team was building trading tools for the Turkish market. We needed historical and real-time data for every stock on Borsa Istanbul (BIST), complete with dozens of technical indicators. Simple enough in theory.

In practice, here's what happened:

• Week 1-2: Building data pipelines to fetch price data from multiple sources, handling API rate limits, dealing with missing data points, and managing storage.
• Week 3-4: Implementing technical indicators from scratch. RSI, MACD, Bollinger Bands, Ichimoku Cloud, ADX, and dozens more. Each one needs to be calculated correctly, tested, and validated.
• Week 5+: Debugging. Our RSI values didn't match what traders expected. Our MACD had edge cases with insufficient data. Bollinger Band width calculations had floating-point issues. Every indicator had its own set of gotchas.

We spent weeks on data infrastructure before we could write a single line of actual strategy logic. And we weren't alone.

Why Not Use Existing Solutions?

The obvious question: why not just use an existing data provider? We tried. Here's what we found:

• Global providers had limited BIST coverage. Most focus on US and European markets, with Turkish data either missing or incomplete.
• Raw data APIs give you OHLCV data but no indicators. You're still implementing 70+ calculations yourself.
• Charting platforms have indicators built in, but their data isn't accessible programmatically for custom applications.
• Pricing for institutional-grade data was designed for hedge funds, not startups and independent developers.

There was a clear gap: no one was offering pre-calculated technical indicators at scale, specifically covering emerging markets like BIST, at a price point that makes sense for developers.

What We Built

Awaken Analytics is the infrastructure layer we wished existed. Instead of building data pipelines, you get plug-and-play access to production-ready financial data.

Here's what that looks like in practice:

Every data point comes with 70+ pre-calculated indicators, validated and ready to use. No pipelines to build. No calculations to debug. No infrastructure to maintain.

The Technical Decisions

Building this wasn't trivial. Here are some of the key decisions we made:

• Hourly updates: Daily data isn't enough for active traders. We process and update every ticker hourly during market hours.
• 10+ years of history: Backtesting requires depth. We maintain over a decade of historical data with all indicators retroactively calculated.
• Consistent calculations: We use industry-standard formulas for every indicator, documented in our public codebook. No black boxes.
• Multiple output formats: CSV, JSON, and API access. Use whatever fits your stack.

Who Is This For?

We built Awaken Analytics for anyone who needs financial data without the overhead of building data infrastructure:

• Developers building trading platforms, screeners, or portfolio tools who want to focus on features, not data pipelines.
• Quantitative researchers who need clean, consistent historical data for backtesting strategies.
• Fintech startups that want to launch fast without spending months on data engineering.
• Individual traders who want programmatic access to technical analysis without building it themselves.

What's Next

We launched with comprehensive BIST coverage because that's where we saw the biggest gap. But the vision is broader:

• Global markets: NASDAQ, NYSE, and European exchanges are in active development.
• Cryptocurrency: 24/7 crypto data with adapted indicators is on our roadmap.
• More indicators: We're continuously expanding our indicator library based on user feedback.

Our goal is simple: make financial data infrastructure a solved problem so builders can focus on what makes their product unique.