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The devil is in the data

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“The greatest value of a picture is when it forces us to notice what we never expected to see.” This quote by John Tukey, the famous mathematician who developed the box plot, one of the preferred tools of data analysts used in descriptive statistics, embodies everything that data stands for. However effective and informative data is, it is the role of the data scientist to represent the crucial piece of information visually so that the audience can not only see its meaning but also intuitively perceived the broader impact.

Data is, indeed, a confusing yet necessary factor of business health. Not only can it come from a variety of sources, but it is also often overwhelming, confusing and contradictory in itself. It’s easy to appropriate the saying, the devil is in the detail, and transpose it to a world of data. Which data detail is the most relevant one for a specific business matter? What details should be ignored? There are many questions about data and the detail of their collecting, analysis, visualization, and interpretation that need to be answered every day in a business environment.

But that’s precisely what makes data so vital and yet dangerous to use without knowledge and understanding. Picture yourself sitting in the cockpit of a powerful plane. If you don’t know which button to press to get the engine started – let alone how to navigate the plane in the air – you can’t use it. Your interaction with data is very much the same. Without knowledge, you can make nothing out of it.

Data harnessing is perceived as a machine’s job

It comes as no surprise that data harnessing is a job that is now entrusted to machine bots, especially when it comes to Internet data. Indeed with roughly 70 Tb of information created every second, it’s easy to understand why a bot would be better at dealing with it than a human brain. However, the information available online is not always valuable. In fact, the Internet is definitely the place to go if you’re looking for trash, fake news, spams, and genuinely terrible ideas.

Thankfully, there is more and more clever technology to help people make sense of it all, by condensing valuable texts for instance to facilitate reading. But the artificial intelligence has its boundaries. Indeed, there is a need for human intervention, either to define how a decision needs to be taken or simply to add the necessary human touch. In other words, despite the rise of bot intelligence, people still want to rely on the human brain to make sense of the information, identify garbage vs. precious data, and bring the emotional human perception into the equation.

The human touch meets business data

Ultimately, there’s evidence that a machine can collect data more efficiently and rapidly than a human user. As big data is everywhere, there are many advantages to work with bots and AI tools to harness large volume. However, you will need to rely on human intelligence to find relevant data in the fuzzy cloud of big data.

In fact, 40% of marketing budget is wasted because people don’t make the best use of big data. But that’s precisely because creating meaning is the role of a trained expert with a masters in data science. The ability to break down large volumes of data into small and digestible pieces that are easy to understand and visualize is an essential skill of modern business intelligence.

How better data can improve your business

Today, more and more businesses are opening their structure to the potential of big data and the positive influence it can have on their strategy and decision-making process. Mastering data science means that you can help a business make the most of its available data. Indeed, proper data harnessing and visualization can help to identify powerful trends in the market sector to gain a competitive edge.

Besides, working with data means that you can provide preventive strategies to leverage opportunities as they come and avoid threats. As decisions are based on solid information, the level of risks is low, and consequently, the potential for success is high.

Get your creatives to work with data

The creative team in a business is responsible for its visual branding messaging, its identity and most customer-focused engagement campaigns. But it’s important to share data with your in-house creatives. Indeed, the best ideas are pointless if they don’t answer a specific need for your target audience. Consequently, instead of letting the stakeholders decide whether the website should be blue or green, it’s best to leave the decision to your customers, using A/B testing data and analytics information. You will need to develop an appetite for testing and optimizing and to help your creative team get used to tools, such as Google Analytics, that can guide them through the projects.

Data overload: Helping people find the essentials

Admittedly, there can be such a thing as too much data. Opening Google Analytics and other data collecting tools to your teams means that you need to not only train them to use the tools effectively but also help them to keep their priorities in focus. Indeed, customers’ needs, skills, and good governance are the three main targets that your business needs to aim for constantly. When there is too much to organize and deal with, it’s important to remember your customer-facing teams that the best strategy is to help the customer fulfil a need.

What keywords are used to find the website? What product does the customer want? Similarly, for HR teams, internal skills and productive management are the primary assets for your success. So pick the data that answer these questions.

You’re asking the wrong questions so data can’t help

Finally, it’s not uncommon for when working with analytics, which is the most common tool used across the business board, to try to make sense of the data collected without knowing what you’re looking for. In fact, a lot of marketers like to report on keywords and number of visitors without setting a business context first. Ask yourself what your purpose for the website is and what success look like before you start monitoring your data!

The bottom line is that data can only be helpful if you know how to collect it, visualize it and interpret it. Access to data is not synonymous with intelligent business strategy.

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