The value of data decays rapidly if not used in real time

Data streaming isn’t about collecting more data—it’s about making smarter use of it. Too many organizations build complex infrastructures but fail to scale effectively. Without high-quality, real-time data, AI models fail, decisions lag, and businesses miss critical opportunities. Scaling isn’t about storage—it’s about activating the right data at the right time.

The Data Journey: From Creation to Monetization

Every data infrastructure follows a maturity curve, evolving from raw data collection to a system that drives growth and revenue. In this first article of the series "From Data Streams to Revenue Streams", we explore the Create stage—the foundation for turning data into business value:

1. Create: Unlocking Hidden Value
   Data is only valuable if it drives action. Real-time activation turns passive data into business intelligence.

2. Scale: Quality Over Quantity
   Growth isn’t about storing more—it’s about accessing high-quality, real-time data when it matters. Coming soon.

3. Monetize: Turn Data Into Revenue
   First-party data is the future. Companies that own and control their data will dominate their industries. Coming soon.

The Hidden Problem: 80% of Your Data is Going to Waste

Let me be blunt: Data has zero value until it’s used. Most enterprises sit on mountains of data that they never touch. Studies suggest that companies only use about 20% of the data they collect. That means 80% of what you're storing is digital landfill—wasted storage, wasted compute, and wasted potential.

If your data isn’t actively driving business decisions or automated processes, it’s not an asset—it’s a liability. Collecting data with no strategy to use it is like stockpiling spare parts with no blueprint. Worse, stale data leads to bad decisions.  

The best organizations don’t just collect data—they activate it in real-time.

Batch Processing is Failing You

The world isn’t running on neatly structured, pre-processed datasets anymore. Data is being generated at an unrelenting pace, and most organizations are drowning in raw, unstructured, and underutilized data—or worse, losing it altogether.

Dark Data: The 80% You’re Ignoring

Dark data is the hidden, unstructured, and siloed information that sits idle—never analyzed, governed, or leveraged for decision-making. Whether buried in legacy systems, scattered across teams, or locked in machine logs, it’s wasted potential. Worse, it leads to redundancy, inefficiency, and compliance risks that businesses can’t afford.

Why Traditional Data Processing Can’t Keep Up

Data Moves Faster Than You Can Handle

Batch processing is too slow for the modern world. Your systems choke on the firehose of real-time data, dumping it into storage without extracting real value. The result? Outdated insights, missed opportunities, and reactive decision-making.

Unstructured Data is a Black Hole

Your most valuable data—Slack messages, IoT streams, event logs, real-time customer interactions—doesn’t fit into structured databases. If you can’t process and govern it in motion, you’re losing critical insights before they even reach your dashboards.

Data Silos Are Killing Your Visibility

Every team, application, and system has its own version of the truth. Without a real-time streaming backbone, you’re stuck with duplicate data, inconsistencies, and blind spots that slow decision-making.

No Governance, No Compliance, No Control

Data privacy laws are tightening, and you’re collecting sensitive data without real-time governance. If your PII, financial transactions, or IoT telemetry isn’t secured as it moves, you’re one breach away from a compliance nightmare.

The Business Case for Real-Time Data

It’s time to rethink data strategies. The era of batch processing, data lakes, and historical reporting as your primary approach is over. Winning companies aren’t waiting to analyze last quarter’s numbers—they’re making decisions as events happen. The value of data decays rapidly if not used in real time. 

Industries like finance, e-commerce, and logistics don’t tolerate delays:

• Banks detect fraud in real time, preventing losses instead of reacting after the fact.

• Retailers optimize pricing instantly based on live demand, not last week’s trends.

• Logistics companies adjust routes on the fly due to weather, traffic, or fuel prices.

Real-Time Data is the Foundation of AI

AI-driven organizations don’t train models on month-old batch reports. They need fresh, clean, exclusive data—in real time. The more up-to-date and high-quality the data, the smarter the AI.

Garbage in, garbage out—AI is only as good as the data you feed it. If you want AI to be a competitive advantage, you need to start with streaming, real-time, actionable data.

More on this topic in Part 2: Scaling Data the Right Way – Quality Over Quantity.

Data Infrastructure Isn’t Enough—You Need Outcomes

Many organizations get lost in the technical side of data streaming. They build a Kafka-based “central nervous system” that looks great on a whiteboard but fails to create real business outcomes.

If all your data is doing is moving between systems without driving decisions, you’re just adding complexity for no reason.

Kafka isn’t just a data pipeline—it’s an activation layer. The real question isn’t how much data you have; it’s how much of your data is being used right now to make better decisions.

As Abraham Thomas says in his article, How to Price Data as an Asset:

“The value of data is the value of the marginal change in actions taken after adding the data to your business process.”

Building a Data-Driven Culture (For Real)

Organizations love to say they’re “data-driven,” but most aren’t. Close to 75% of organizations fail to create a truly data-driven culture (MIT).

Being data-driven isn’t about having dashboards—it’s about ensuring every decision across teams is powered by real-time insights.

That means:

• Marketing reacts to live customer behavior, triggering campaigns instantly instead of relying on outdated segmentation.

• Sales leverages real-time intent signals, moving beyond inefficient cold-calling.

• Operations adapt dynamically to supply chain disruptions rather than reacting after delays.

Your competitors who are truly data-driven? They’re already ahead. And they’re not slowing down.

The First Step: Move From Passive Data Collection to Active Data Use

The companies that dominate their industries in the next decade will be the ones that master real-time data activation. If you’re just collecting data and hoping for the best, it’s time to change your approach.

The good news? The technology is already here.

Step 1: Ditch the mindset that data collection is the goal. The real goal is using data in real-time to drive immediate action.

Next up: How to scale real-time data without drowning in complexity or cost. Stay tuned for our next article, Scaling Data the Right Way: Quality Over Quantity.