[LOG_01] Info Overload & Meaningful Machines

Hey there👋, this is just me thinking out loud as I dive deeper into software engineering — or really, what it means to work with information. As a student still figuring things out, I don’t claim to be an expert, but here’s something I’ve been reflecting on lately.

When people talk about software engineering, the spotlight is usually on programming — the actual code, frameworks, and the latest tech stacks. And yeah, programming is crucial. But at the core, we’re really managing information. The discipline of Information Technology is all about that “information” part — taking raw data and transforming it into something meaningful that can drive decisions or create value.

Take raw sales data, for example. Without the right processing or context, it’s just numbers sitting in a spreadsheet. It means nothing to the salesforce team until it’s organized, interpreted, and presented in a way that tells a story — like trends, customer preferences, or actionable insights. Software engineering provides the tools and processes to turn that raw data into meaningful information that businesses can actually use.

This idea isn’t new — in fact, it’s central to how we think about data and information in IT. According to Davenport and Prusak in Working Knowledge, “information is data endowed with relevance and purpose” (Davenport & Prusak, 1998). Similarly, in Data and Goliath, Schneier reminds us that how we collect and process data shapes the power and utility of information (Schneier, 2015). And from an engineering perspective, Sommerville’s Software Engineering stresses the importance of understanding user needs and context to ensure software delivers meaningful outputs, not just raw code (Sommerville, 2016).

At the end of the day, software engineering is about more than just writing code — it’s about understanding information and how to transform it into something meaningful for people. And I guess that’s why I find the discipline so fascinating. Still learning, but enjoying the journey.

Would love to hear your thoughts or if you’re also on this learning path!

📑References

• Davenport, T. H., & Prusak, L. (1998). Working Knowledge: How Organizations Manage What They Know. Harvard Business School Press.

• Schneier, B. (2015). Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World. W. W. Norton & Company.

• Sommerville, I. (2016). Software Engineering (10th ed.). Pearson.