The Age of Data
Machine Learning. Artificial Intelligence. Data protection. The Age of Data. Probably all terms that keep coming across everyone´s news feeds, work environment, conferences, research studies and many other domains of our lives — even love life can get influenced through the algorithms of the several dating applications available in the market. Data and quantitative methods have been applied and essential for centuries in the most diverse core fields of Science. But, these days, its importance jumped into our daily lives and many businesses, being far from being “merely” a Science discipline or Science little helper.
Indeed, data became a hot topic, dividing some opinions across the globe. Whereas we fully embrace it or not, we keep creating data every day. But how many of us deeply understand the implications of the data burst in the world? Perhaps not enough people can read data to enhance its application to worldwide well-being, improve actions, evaluate ideas and forecast beneficial strategies — neither to understand its negative implications.
Tackling one of the causes behind it, we never had so much access to data as we do today. We never had so much storage of data as nowadays, and we probably never cared about it so actively as much as today. Addressing its importance per se in our everyday lives is predominantly a millennial`s approach.
Sometimes a controversial topic due to information privacy and data usage ethics, it is undoubtedly true that corporations use and should use (some) data for their decision making. The amount of data that is collected, analysed, and employed in decision making seems to start playing a crucial role in the development of any businesses. Data decisions and strategies get also reflected in the most mundane or methodic activities. For instance, it is enough to think about any smartwatch or fit bands and quickly come to a realisation that they have been tracking daily activities worldwide of millions of people. They might state several mathematical indicators as the quality of sleep; the distance walked and many other data points — probably the number of datasets available will be positively correlated with their price though! Perhaps some people cannot relate to sports or any of these fancy devices but for sure (to be a bit more accurate and nerdy, I should claim a probability of approximately 100%) listen to music from time to time and get a few new suggestions. Suggestions that, if followed, might blow their minds because they are most likely very similar to their musical taste! Some of them might think it is a big funny coincidence, but thinking attentively about it instead of just going with the flow, might bring up other conclusions. And if some people might still think it is a coincidence, data connoisseurs will argue that they might be following a fallacious path.
But what are the implications at a slightly more macro level?
At a corporate level, I would boldly dare to say that any thriving company, at least, recognises the potential of data. Data can be broadly used for strategy making, giving objective and quantitative goals to most corporations. The maths are simple: with the amount of data collected growing at a fast rate, more insights get collected and analysed, the samples better reflect the population, which should mean theoretically more accurate and measurable reasoning, better decision-making, superior strategies, improved forecasting models, etc. All in one, it should support and benefit the corporations significantly. The active collection and interpretation of data, being such a “new” sphere of interests, it is a domain with nearly infinite possibilities and a growing “business”.
The advantages of data in a money-making business are numerous. In a few seconds only, it is possible to consider a few measuring attributes connected to the most diverse teams and backgrounds, from human resources to sales, from marketing to expansion strategies and product teams, to enumerate a few. They can be employee performance mapping, marketing campaigns performance, customer experience, product quality assurance, websites and applications creation, company growth, optimal budget spent, cost management, market competition performance, customer targeting and even forecasting models and strategies. And, of course, implementing those models and evaluating their execution and results. The ways of manoeuvring data for profit are several as described beforehand- and many others could be thought and considered.
Data also gives insights for future trends, which stimulates another hot word: innovation. In general terms, data analysis connects past, present and future. It helps to look at what happened and what to take from it. It pushes the perception of situations. It helps to store and share information. It helps to make inferences, in the short and long-term, into an existing given model or creating something from scratch.
But data is for a fact as relevant to non-profit organisations as it is to for-profit corporations . Especially for the data sceptics that might care about socio-environmental causes above anything else, I would like to point out what motivates me the most about numbers. Despite the excitement of my left brain (sometimes right) while facing some mathematical challenge, of course. It is how data can be used for good, from helping the smallest cool project out there to bloom until dictating the course of an entire nation. Data has been helping forecasting pollution levels, giving warnings about when to stop as a nation. Data has been helping to understand the fight against global warming through measurable insights from past, present and future predictions. Even the concept of global warming per se would be inexistent without any historical data — although the constant increase of heat, fires and other climate issues snapping across the globe would probably ring some bells. Still, some upwards or downwards curves in the graphics align with accurate numbers might be a bit more explanatory than a constant need to get some freshwater under the sun, facing a heatwave. As a side but relevant note, the greenhouse effect was first referred to back in 1896 by the Swedish scientist Svante Arrhenius (note). His mind wondered what would be the effects on the global climate if atmospheric carbon dioxide doubled — a great example of how numbers have been relevant for long in Science.
The data gathered can also help predict disease outbreaks — it is not a coincidence that some scientists predicted a new pandemic most likely. Data can assist in mapping poverty areas and pushing tailored strategies to fight the social issue. Data can help to weigh the number of endangered species, delineate strategies and model pro-conservation methodologies. Data can support the optimisation of car routes and have an impact on pollution decrease. Data can be collected to assist transportation routes optimisation, cutting costs and improving people´s lives. Data can get gathered to help to spot the gender pay gap and improve this inequality. Data can further track where food waste is higher and connect it to where food shortage is the highest. Data can create and shape several symbiotic relationships between many vectors of our planet, in the present and the future.
It is relevant to demystify the importance and impact of data and how it goes much further than a hot topic in social media. It helps in understanding matters as important as our existence. It has been explored for long by the wisest minds and, fairly more recently, its importance extended to ordinary activities. Perhaps the more governments gather relevant data, the better worldwide policymaking will be. At a macro level, data is as pertinent to companies as it should be to governmental analysis — and in a utopian world, we could all benefit actively and individually from it.
In short, whereas the focus is individual, corporate, profit or non-profit, governmental, societal or global, the impact of data should be irrefutable already, and it can be maximised in the future — hopefully as data for good.
