Over the past decade, the term ‘Big Data’ has gone from being a tech sector buzzword to one that appears regularly in job ads and turns up thousands of news items in online searches. So what exactly does ‘Big Data’ mean and what kind of opportunities has it brought to the market?
What makes Big Data different from ordinary data?
On its website, international cloud computing leader Oracle Corporation says the term refers to data sets too “voluminous” for traditional software to handle, but which still offer useful applications. That’s a start.
IBM offers a similar working definition, characterising it as a data set too complex for a traditional database and featuring at least one of three essential traits: “high volume, high velocity or high variety”.
To round things off, data analytics firm SAS adds nuance to the previous two definitions by attributing the complicated nature of ‘Big Data’ to its mix of “structured and unstructured” digital information.
Combining these views, one may safely conclude a few things about the nature of Big Data. First of all, it isn’t one single thing – in fact, quite the opposite. It’s the result of huge streams of irregular data flowing out of any number of different sources: web traffic, financial transactions, audio, video, step counters, GPS pings – literally anything being recorded digitally.
Top jobs in Big Data
The job market for folks competent in harnessing, organising and interpreting that vast ocean of information is growing quickly, as companies large and small look for talent and services related to everything from machine learning to fraud detection and optimising retail sales.
In a white paper released earlier this year, Oracle estimated that Big Data applications could represent $300 billion in value in the health care sector alone each year, by streamlining services and cutting patient stays in hospitals.
With the exponential roll-out of digital devices, apps and data-heavy activity around the world is generating an exponentially larger and deeper pool of global data – which, 20 years ago, would’ve been an insurmountable task for a single analyst working in Excel. Fortunately, it’s not the late ’90s and individual programmers have affordable tools at their disposal these days.
For established companies looking to buy software suites, the multi-billion dollar tech firms offer a range of products scalable to large businesses. However, for independent programmers and startups working in data analytics: your skills are in very high demand. And good news: two of the most popular languages in the growing Big Data sector – Python and R – are both open-source and free to download.
Reflecting the soaring demand for these skills, the job title of ‘data scientist’ topped LinkedIn’s list of Most Promising Professions in the US for 2019 – thanks, in part, to an average reported base salary of $130,000 and the appearance of over 50% more employment listings compared to a year earlier. Among the key skills desirable for those positions: Python.
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