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Data Visualisation And How It Impacts Business Strategy

Data is an integral part of forming a business strategy. With expansive and rapidly-growing volumes of data, it may seem decision makers are well equipped. Therefore, they should prepare to reap generous benefits from their digitalisation efforts. However, more is not always better. Dealing with large amounts of data can be overwhelming. It can result in “drowning” if the companies don’t solve particular challenges before stepping into a data-driven era.

It’s no secret that with big data*¹ comes the potential for great opportunity. Understanding the significance of data by placing it in a visual context is one of the most significant commercial results of technology in recent years. Not only does it provide an organisation with the ability to visually present and analyse its information. More importantly, it gives the organisation a new way of seeing and interacting with its data.

One of the key unlocks of data visualisation is the ability to look at things from a different angle. Implemented correctly, a data visualisation platform would provide managers and decisions makers with more detailed insights into the way their business is currently operating, in an easier to absorb format. Just short of flying cars and utopian houses in the sky, we’re basically living in the era that we used to watch on TV, thinking “we’ll never know that”. Well, the future is upon us. The opportunities we have to create a much more productive environment in the business world, as well as make everyone’s life a little easier, are seemingly endless.

Why do we need data visualisation?

Big data and data visualisation are powerful discovery tools for companies seeking to glean new insights. Essentially, data visualisation is the presentation of data in a visual format. Sounds simple, doesn’t it? It’s not. With interactive visualisation, you can take the data one step further. This is done by using technology to drill down into charts and graphs for more detail, interactively changing how data is seen and processed.

Co-founder and CEO of IoT.nxt, Nico Steyn, noted that ”with big data and data visualisation, we’re able to look at and better understand data that has been under our noses for centuries. It gives us the ability to pick up certain complexities of the data that we may have otherwise missed while pouring over spreadsheets and reports.”

The human brain processes information in a particular way. Therefore, we are met with certain limitations when it comes to analysing data. The purpose of data visualisation is to simplify data values. As well as promote the understanding of them and communicate important concepts and ideas. Visualisations are the single most effective way for our brains to receive and interpret large amounts of information.

The human brain is incapable of processing more than one value at a time. Let alone the hundreds, thousands, millions and billions of values that come through with a company’s data. However, being able to understand, interpret and react to that data is vital for the productivity of a business. Enter data visualisation. It’s clear that the flow of data is not going to shrink in the near future. It is just going to continue to grow rapidly. Data visualisation produces big data that allows managers and decision makers to gain more insight into the operation of their business. As well as forecast what might happen.

Data visualisation and IoT

The explosive growth in the number of devices that are connected to the Internet of Things and the exponential increase in data consumption only reflect how the growth of big data perfectly overlaps with that of IoT.

Mr Steyn added that “IoT represents a new approach to thinking about devices and data generation. However, one of the challenges for the IoT industry is currently data analysis and interpretation as the technology is still in its ‘infant’ stages. Therefore, data visualisation allows for information to be properly interpreted by humans once IoT technology has generated it.”

So, data visualisation and the Internet of Things go hand-in-hand when it comes to impacting business strategies. The powerful advantage of this data generation and visualisation, coupled with the visual cortex and pattern recognition capabilities of technology as well as the human brain, allow data analysts and decision makers to quickly grasp the meaning, identify trends and even notice inconsistencies and errors in the data.

Essentially, data visualisation is the initial filter for the quality of data streams. By combining data from various IoT sources, visualisation tools perform preliminary standardisation, shape data in a unified way and create easy to understand visual objects.

How data visualisation helps data impact business

One of the most predominant benefits of visualisation is data cleansing. As just mentioned, visualisation allows for the data to be seen by humans in a clear, relevant and informative way. It means that even novice users can create data visualisations that are meaningful. These visuals simplify the totality of the data. Which then cleanses it in a way that is able to be interpreted by the human brain.

It’s also no secret that big data is only getting bigger. It’s condensing an ocean of information into simplified visual reports. One main thing that’s keeping bigger companies from drowning in this ocean of information is the fact that their large data sets are more coherent. As the quantity of data is always increasing, businesses that rely on manual data analysis and visualisation methods could very likely fall behind. With automated data visualisation tools, different teams across a business ecosystem can present their data in different formats and levels of detail. Furthermore, the ability to pick up on important patterns and trends easily missed by the human eye in the data streams enabled by the work of IoT technology.

Another benefit of data visualisation in the business world is that it helps to clarify certain customer trends. Sales and marketing in Industry 4.0 is all about using data to understand and engage with customers more effectively. It’s far more productive and cost-effective for a company’s marketing team to be able to skip all the time spent crunching numbers and trawling through spreadsheets. With big data, that company could have access to an efficient and highly productive means of identifying important customer trends. Sales executives can go one step further and use real-time data visualisation to forecast their sales figures. Therefore, if a certain product is underperforming, they’ll have the means to determine why allowing them to re-strategise accordingly.

The challenges of big data

Data visualisation can help professionals across the business acquire a shared point of view on important trends and issues. In today’s highly competitive business environment, finding and acting on these data correlations is key to success. For example, if a company was not able to identify that consistently delayed manufacturing processes are damaging customer satisfaction. Something like that could make or break the business.

However, as with everything, there are some challenges in working with big data. These include cleaning the data, deriving insights and data strategy. Data-driven technology is only as good as the people who take advantage of it. Therefore, at the end of the day, the one main goal is to drive employees to action.

An Experian report states that only about 44% of decision-makers actually trust their data and C-level executives, in general, are always sceptical, believing that 33% of their data is inaccurate.

This is where data cleansing comes in. When it comes to inconsistencies, incompleteness and human errors, cleansing raw data is the first step for any company.

Another challenge is when it comes to actually deriving insights from the data and understanding how to extract meaningful dependencies and finding patterns in that data. Realistically, those insights and patterns are what allows a company to problem solve, drive sales, cut costs and find new revenue streams, bringing you unprecedented ROI of IoT. Therefore, if the data is not interpreted correctly, the point of retrieving this big data may become moot.

Furthermore, when it comes to the data strategy, it doesn’t matter if you have the data cleansed and the insights extracted, knowing what to do with all this is vital. Without a clever strategy, the resources and efforts that are put into leveraging this data may end up being in vain.

Unifying the business strategy

Data visualisation, interpreting big data and working with IoT technology is not without its challenges. However, when implemented correctly, data-driven technology is the key to staying on top of your industry market. New generation data visualisation based on AR and VR technology also provides formerly infeasible advantages in terms of identifying patterns and drawing insights from various data streams. These 3D data platforms introduce immersive visualisation with brand new benefits for business and the whole industry.

These tools allow us to expand the capabilities of data visualisation by creating collaborative environments for the team. However, as the data grows, it becomes harder to follow. This is where data strategy is essential. Data visualisation tools enable continuous real-time monitoring of how your business’s strategy and decisions influence performance and business outcomes. And with the constant and timeless development of IoT technology and data visualisation tools, the ability to extract, interpret and successfully utilise data-driven insights is not only completely accomplishable but also crucial to your company’s success.

*Large data sets that may be digitally dissected to disclose patterns, trends, and associations, especially relating to human behaviour and interactions. (Definition via Google).

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