We might not consider 10 years ago a huge amount of time. But in 2008, the world's biggest technologies were confined to the early rise of smartphones and DVDs being superseded by Blu-Ray, while 3D televisions and AI were innovations confined to the future. How businesses utilise technology has also undergone a drastic transformation in the last decade, particularly when concerning data analytics. Though some technologies used ten years ago are still in use today, data analytics has grown into brand-new territories, particularly concerning the internet and the collection of data from consumers to improve marketing strategies and generate business trends.
Over the last decade, we have seen the emergence of 'big data' in almost every industry. So many more people now rely on the internet to purchase products or services, or even to use social media and other forms of online commentary such as posting reviews and blogging, that the data being captured has grown at such a breadth and speed it has left ordinary technologies struggling to keep up with it. This data can glean information on everything from consumer demographics to interests and preferences, affording businesses tremendous scope to learn more about their customers and better serve them.
The potential for rich analysis earned it the term 'big data'. It's too vast to be analysed by humans, and so requires computational input. Thus, technology had to develop alongside the growth in input. It is not only big companies who have been able to utilise this technology to understand business-to-consumer data; the rapid spread of these methods has also allowed smaller businesses to invest in data analytics, facilitated either by their own or third-party software.
Data analytics has also begun to be used in cognitive technology and artificial intelligence to facilitate machine learning, enabling AI to make decisions or take actions. Previously, these trends were designed by humans, but with AI working at faster speeds and more efficiently, actions can be taken on at a much quicker pace. This significantly reduces the time between analysis and implemented action, something that could not have been done by humans alone.
A lot of the original data analytics methodologies are still at work, but it's clear that many companies are now investing in analytics that can handle the huge amount of data that they are receiving. Such changes in data analysis have been quick and far-reaching, so much so that we are now seeing the repercussions of certain companies taking liberties in how they handle and use this data. But regardless of a few negative headlines, there's no denying that analytics have grown in importance over the last decade, and more companies than ever before are beginning to see the benefits that these new technologies are presenting.
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