HomeData EngineeringData NewsUsing Big Data in business decisions

Using Big Data in business decisions

Big data – alongside sustainability, the “Internet of Things” and crypto – is arguably the buzzword of the decade.

It’s a term that describes the large volume of data that inundates a business on a day-to-day basis – and represents the potential means to an end for businesses with respect to some of the most complex and burdensome organisational procedures.

But having big data alone won’t help an organisation: it is what’s done with that data that truly matters. With the right tools, businesses can achieve anything, but only if they choose to fully embrace those tools.

Big data encompasses a huge range of analytics and data-gathering strategies, all of which enable a business or organisation to make more informed business decisions. If used correctly and effectively, big data can be analysed for insights that lead to better decisions and more informed strategic business moves. This is no new revelation: the more a business or organisation knows about their operations, the better decisions it can make and the more appropriate solutions it can find to problems.

Big data itself was born out of the need to more fully understand and comprehend trends and patterns in huge databases to transcend countries, cultures, and time. Take McDonalds, for example. With a presence in hundreds of countries worldwide, in vastly different places of different cultures, social behaviours and eating habits, it is next to impossible to launch a new burger or meal without fully taking into account customer preferences.

With big data on the cloud, that kind of data can be created and shared instantaneously, allowing a Bangledeshi-based innovation team to create a burger for Swedish McDonald chains based on factual information. Another example is that of real time traffic data. Big data enables provincial and city governments to optimise traffic flows based on real time traffic data that reveals where and who is travelling in what direction in a city, as well as at what time of day, so as to better plan out road networks.

The opportunities big data brings are endless. Especially when it comes to businesses, big data can help a brand improve its customer retention and acquisition, produce targeted campaigns, innovate products and manage complex supplier networks. Particularly with respect to understanding customer needs and preferences, big data can help in a big way, enabling businesses to anticipate demand well in advance and then ensure there is sufficient stock to satisfy that demand.

With the advent of “the cloud” – which refers to the software and services that run on the Internet, instead of locally on your computer – comes even more possibilities. Ten, twenty years ago businesses were forced to create complicated tables and input each item of data manually to analyse patterns and trends; a very time consuming, cumbersome, expensive task and one which was almost redundant by the time the job was complete, in that the efforts provided insights from out-of-date data.

Today, cloud technologies allow companies to analyse data almost immediately to figure out if a new product, service or idea will be a success or failure. They’re also usually more cost effective, thus improving the ROI on big data technology. Think about it: With the cloud, companies can quickly gather data from multiple sources including sales, web analytics, call centers, and inventory sources. Using big data, companies then compile the data before analysing it, turn it into a presentation immediately, and then act on it. This entire process would have taken weeks if not months prior to big data, while now – thanks to that beautiful thing known as the Cloud – it can happen instantaneously.

When it comes to cost prediction, big data – and many of the best cloud storage solutions that make use of that data – can allow for near real time cost prediction, alongside modeling, visualization, and optimisation. This is particularly game changing for businesses in that having the ability to estimate future cost levels based on historical cost behaviour characteristics is now available to the masses via cloud technology, and virtually for free too. This allows businesses and organisations to forecast future costs for managerial decision-making purposes.

Using such statistical techniques as linear regression, it helps companies undertake a whole host of burdensome tasks, from determining stop-loss calculations to performing risk analyses, to redeveloping products and creating new revenue streams. Instead of outsourcing freelance data analysts, and spending big bucks on doing so, big data and the cloud can help unskilled individuals do the same free-of-charge.

Big data has now become integral to many leading companies outperforming their competition, with new entrants and established competitors now using data-driven strategies to compete and innovate. Particularly when it comes to observing customer behaviour to identify customer-related patterns and trends, big data can provide organisations and brands with the data they need to understand their target demographic and customer base.

But again, none of this matters if a company does not use that data correctly. The ideal big data strategy is all about maximising the data at your disposal to achieve whatever organisational or business goals have been set.

This article has been published from a wire agency feed without modifications to the text. Only the headline has been changed. 

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