Too Big to Ignore: The Business Case for Big Data

Imagine a world where data was scarce, carefully recorded by hand in thick ledgers, where each entry was a deliberate act of human effort. Errors using inadequate data are much less than those using no data at all. This was the dawn of data in business—structured, orderly, and limited. For decades, companies relied on structured data stored in neat tables within relational databases powering ERP and CRM systems. These systems could process customer records, sales transactions, and employee information with precision. Yet, this was only the beginning.

As the 21st century dawned, a tidal wave of new data forms emerged. The rise of Web 2.0, social media platforms, and smartphones transformed passive consumers into active data creators. Suddenly, photos, tweets, videos, and location check-ins flooded the digital landscape. Unstructured data, once a negligible fraction, now comprises over 80% of organizational data. This data was messy, vast, and fast-moving—far beyond the capabilities of traditional systems.

Consider the City of Boston’s innovative approach to potholes: an app called Street Bump uses smartphones’ accelerometers and GPS to automatically detect road hazards, sending data to city officials without any manual reporting. This example illustrates how new data sources can revolutionize even mundane public services.

Yet, many organizations remain anchored in the old world, struggling with siloed data, poor quality, and inadequate governance. The challenge is not merely technological but cultural. To thrive, companies must embrace the new data reality, recognizing that data now flows from countless sources, in varied forms, at unprecedented speeds.

This shift sets the stage for understanding Big Data’s defining characteristics and the techniques needed to harness its power. Let us now explore these defining traits and the methods that transform raw data into insight.