Your Small Data Is Important too: Here's Why

The amount of data around us is increasing exponentially, and much of it is put into systems that support?organisations in gaining actionable insights. However, humans still need to be able to comprehend and interpret data on their own, and this is where small comes in.

People sometimes think of small data?as the definition of data as we've traditionally understood it: information that is simple for most people to understand, take in, and act upon. However, with the popularity of big data and big data analytics has come a propensity to overlook the value of little data in today's business context.

As trendy (and useful) as big data might be, only small data can actually allow us to make sense of why these trends machines help us see what's happening. As such, while big data technologies can find patterns and correlations, small data helps us understand the context.

What is small data?

What makes small data ‘small’ isn’t the data itself, but the scope of the query. You can think about small data as corresponding to an infographic. This type of visualisation is designed to tell a strictly specific story with an absolute minimum of necessary context.

You’re not expected to dive into the data or pivot it into different dimensions.

Focusing on individual data points can – with a little human intuition and understanding – yield valuable information that’s overlooked by traditional big-data analysis.

In particular, it’s suggested that a customer’s decision-making process can be affected by intangible factors such as the climate, the governmental and religious context or cultural tradition. Ultimately, the goal is not only to predict what customers will do, but to identify the underlying drivers that motivate them. This is the sort of analysis that big data alone could never produce.

Why are businesses turning to small data?

Engaging with big data is a lot more complicated than just pulling up an Excel spreadsheet. A query is likely to involve multiple systems and data sources, and often some sort of fuzzy artificial intelligence (AI)?interpretation.

Although we humans can only process limited amounts of data, we have a natural talent for identifying which items are important, and making actionable decisions on that basis. We can also draw on our wider contextual understanding to interpret information: every big data event starts out as small data, so it certainly doesn’t hurt to have eyes on that end of things.?

There isn’t so much of a backlash against big data, as there is a newfound recognition of its limitations. The point of the “big data” approach is to not get bogged down in details. That’s great as far as it goes, but you can’t run a business wholly on not knowing the finer details.

Big data is great, and it can be a very useful tool. The problem is that anything that makes big data 'big is normally too large and complex for a human to comprehend. It’s great to have machines poring over a huge aggregated mass of data to extrapolate emerging global trends, but staff need to focus on much smaller sets of facts and figures - things we can understand and process for ourselves.

At amarti, we've helped companies like yours merge big and small data into one place. With adequate tools behind your data you can blend multiple data sources into a single source of truth. After that, you can take that information and transform it into beautifully simple, intuitive reporting that will keep you ahead of the competitive curve.

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