Organisations everywhere are amping up their businesses strategies by kitting themselves out with the latest technologies. Artificial intelligence (AI) in particular has taken centre stage as of late. With gung-ho attitudes in tow, businesses everywhere are igniting an AI-driven fire in the hole.
AI algorithms famously necessitate curation of big data sets, but this can often be difficult for businesses to manage.
This begs the question: can less ever be more?
“It’s the little things in life” is a quote you’d likely find on a motivational Instagram account. However, the quote very much has a place in enterprise tech. In particular, the potential of small data actually weighs as much as that of big data in algorithm creation; it just requires a little patience.
What is small data?
As a recap, small data is data that comes in such a volume and format that is easily actionable. In particular, small data is more accessible and and informative than its big data counterpart. By nature, it’s more precise, focusing on only one type of data rather than a larger variety. For example, small data versus big data is like determining the weather in London versus the weather in the UK.
Small data is far easier to handle than big data, so much so that it is not exclusively comprehensible to data scientists. Instead, anyone can utilise it for almost-immediate business intelligence.
So what use is it for AI?
Although we’ve sung small data’s praises, until now, small data has been much too limited to bring anything to the table. What’s more, businesses today are simply inundated with data-related responsibilities to factor it into their strategy. Thus, its easy to overlook.
However, as AI advances, organisations should anticipate a world in which we can create robust algorithms using just small data. AI grows cleverer and more powerful every day, necessitating that businesses get their small data in order in preparation.
Using small data to build AI algorithms will alleviate much of the burden of tackling big data: a mish mash of unstructured and structured data. Most organisations will have invested in big data platforms and solutions to help them handle it, but small data needs nothing of the sort. Although we naturally search for bigger fish to fry, small data will surely take the algorithm world by storm in the near future.
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