Data is all around us. With consumers generating around 1.7MB of data every second (2020), is it any wonder that companies seem to be riding a wave of data and analytical insights? Well, maybe ‘drown’ is a better word to use.
Consider for a moment the following statistics:
- Google gets over 3.5 billion searches daily.
- WhatsApp users exchange up to 65 billion messages daily.
- It is estimated there were around 40 trillion gigabytes of data (40 zettabytes) created in 2020. By 2025, it is estimated that the global datasphere will grow to 175 zettabytes.
- Based on available speed and bandwidth, it would take a person approximately 181 million years to download all the data from the Internet.
The statistics around data creation and what it means to the bottom line of a business is staggering. Over the past decade, big data and analytics has become the centre of insight for businesses as they harness the massive volume of data to align strategy, help teams collaborate, uncover new opportunities and compete in the global marketplace.
So, it is a pretty fair statement to say that we live in an age of big data. It is being used to harvest and improve everything from industrial processes, to keeping shelves stacked, to accurately targeting digital ads.
As such, it is equally fair to say that data literacy is going to become one of the most important skills to master, across all professions, going forward. No longer confined to the ‘techies’ – people across all vocations will need to be able to use data to make the best decisions.
Whether at a personal level, or a business level, data availability and the ability to tease accurate and valuable insight from that data is going to become a skill everyone will have to master to some degree.
However, what if you are eager to take your skills to the next level and explore a career in data analytics, data science, marketing, etc?
It may seem a bit daunting to try and pick one particular role within the datasphere. Data scientist, data analyst, machine leaning specialist, data visualisation specialist, software engineer, technical business analyst – it is a lot. The thing to remember though is that you do not have to be an expert in all of the possible spaces instantly.
If interested in data, pick a role and see if you can find someone to mentor you. Whether it be data analyst or data scientist – many of the skills you will gain in any of the chosen roles will be universal to a greater or lesser degree.
The statistics around data creation and what it means to the bottom line of a business is staggering.
Pick a programming language and do whatever you need to in order to qualify or become proficient in it. Some of the most powerful analytics tools available are free to use, or crowdfunded.
Pick a course either through a university/college or via an in-house graduate programme and slowly learn the concepts and ideas. Due to businesses worldwide fully embracing the power that lies in the massive amounts of data that is available, many of them have developed in-house graduate programmes that will teach you all of the above and supply you with a mentor to help make your journey easier.
Focus on the practical applications of data. Knowing how to sift through disparate data looking for patterns, anomalies and insight is perhaps the most useful skill you can have as a data professional. The programming language or tool becomes almost secondary to that, as long as the data can be consumed and analysed. You have to know how to code, but you do not necessarily have to know computer science.
Next most important, in my opinion? The ability to translate the insight you glean into something that is useful or understandable to business. So, excellent visualisation or communication skills are vital. There is no point in finding the pearls of wisdom if you cannot explain to anyone why it is a pearl and why it should be invested in.
Lastly, becoming a data specialist will not happen overnight. And you will not ever stop learning. Every day, new insight, new tools, new industry standards, etc, become available. These can be used to hone skills, to further train the instinctive insight or gut feel many data professionals build over time. Knowing instinctively there is something worth looking for, if not necessarily understanding why.
Data is all around us and for many, it is the driving force behind what we do all day. The nitty-gritty of searching through a massive dataset for the answers to a question a business has asked.
Even more thrilling? Searching through a massive dataset and finding the answer to a question no one has ever thought to ask yet. That is the power of data!
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