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Big Data for Humans: Why Data Visualisation is Important

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The phrase “Big Data is the future” is now used so often that it has become a cliché within the tech world. However, this oft-repeated soundbite doesn’t give many clues as to how Big Data will actually exert its influence in the marketplace. Oftentimes, it’s data visualisation that allows Big Data to unleash its true impact.

There is no doubt that Big Data is a powerful discovery tool for companies seeking to gain new and valuable insights. But the difficulty inherent to isolating a signal from vast seas of noise means that much of this knowledge is still being left untapped. This is where modern data visualisation tools can make a real difference.

At its best, data visualisation allows decision makers to see subtle connections within huge multi-dimensional data sets. It also provides new ways to interpret that data through the use of rich, interactive graphical representations. When it comes to getting the most out of the data your company is gathering, there is no substitute for a well-designed data visualisation strategy.

The brain prioritises visual information

Due to the way the human brain processes information, using graphs and charts to visualise large amounts of complex data will always be more effective than poring over enormous spreadsheets or lengthy report papers.

Studies suggest that more than 50 percent of the brain’s pathways are involved in visual processing. Humans are quite literally hardwired to prioritise visual information over all other incoming stimuli.

Processing numerical information takes much longer and requires a greater level of cognitive effort. Presenting results from a big data project in a static numeric table renders them virtually impossible to understand.An appropriate method of visualisation is needed in order to transform the information into a comprehensible format which delivers a clear take-away message to the viewer.

Building the right strategy

Visualisation is often the most overlooked step in the analytics process. A failure to invest sufficient time and effort into building a solid data visualisation strategy means that useful insights may continue to go unnoticed.

Ben Glanville, Head of Data Services at market research company YouGov, said that when developing a visualisation strategy, it is crucial to keep your target audience at the forefront of your mind.

“It’s so basic, but a building a good visualisation strategy comes down to involving your stakeholders from the very beginning. For example, when strategizing for a client it’s important to keep in close contact with a few individuals from that company with whom you have a trusted relationship. Their input will help you keep sight of the bigger picture and ensure you are developing ways to look at data that people will love,” he said.  

The same rule applies when visualising data for internal presentation to fellow employees.Failing to keep the end goal in mind frequently results in visualisation which is unfit for purpose. All too often, employees and clients are left scratching their heads wondering what it is that they should be taking away from all that brightly coloured information.

Moving beyond Excel

In the early days of data visualisation, the only tools available were those that exist within Excel.Using a spreadsheet as an initial starting point, you then had to go through the painstaking process of creating a simplified graphic to help convey a message or understand a business trend.

For years, Excel was the best (and only) tool out there.  However, over the past decade, data has evolved to a point where Excel can no longer handle its size.Furthermore, professionals now require more complex visualisations than straightforward pie, line, or bar graphs. “Static graphs are fine for people who just need a top-line view on things, but they do not allow end-users to truly explore the dataset” said Ben.

The growing demand for improved visualisation technology brought about the modern era of data visualisation we are now in. An abundance of advanced visualisation tools now populate the market. Notable examples include Tableau, QlikView, and Vizify.At progressive companies, employees are using such tools to do much more than create simple graphs. They are now beginning to interact with their data, learning new things about their businesses in the process.

Ben pointed out that this is democratising Big Data, putting more power into the hands of users.

“What’s really exciting is that advanced coding means that datasets can be updated in real time, giving people not just more, but more current, information than was possible before. Programming languages such as Python allow these datasets to be analysed almost instantly, which means that insights can be acted on faster than ever before. In time, as coding becomes more mainstream as a skill, we will see people interacting with datasets in a far more bespoke way as they’ll be able to do so much more themselves. Users will become accustomed to making their data work harder,” he said.The days of IT departments needing to generate reports for non-technical employees will soon be gone thanks to these new technologies.

Answering tough questions

While these tools are powerful, they can only deliver useful insights when users are asking their data the right questions. The ‘right’ questions depend entirely on the business environment. As each organisation has its own specific set of needs, the questions asked of data need to be carefully tailored to fit around them.

Priyanthi Perera-Nathan, Senior Manager (Data Strategy Consulting) at a large aerospace engineering company has experience handling data in a diverse range of environments.In her previous role as Head of Personnel Analytics at the British Army, Priyanthi was tasked with helping to find answers to incredibly complex questions.

“The Ministry of Defence requires constant updates from the Army in order to keep track of the demand for manpower. Therefore, the Army must be able to accurately quantify its existing strength i.e. how many people they have, the capabilities each of those individuals possess, the positions that are currently vacant, the training pipeline and promotion plans etc.  

“The problem is that the information needed to answer the MOD’s questions comes in from a multitude of data sources. My role at the Army was to collate all of that information into a single consistent data set. This made it much simpler for the Staffing Department to find the answers they were looking for.Essentially, my team worked to deliver data in a way that allowed visualisation tools to perform optimally. This greatly enhanced the Army’s planning and forecasting activities,” she said.

This is a prime example of how data visualisation can be leveraged to deliver tangible improvements in operational efficiency.

Visualisation tools and the silo effect

Modern visualisation tools are certainly convenient, but they also have a downside, as Priyanthi explained:

“In some situations, the increased use of visualisation tools may serve to reinforce the silo effect which has always been a major challenge within the data and analytics industry.As the tools are typically not compatible with each other, using a number of them creates fragmentation in the reporting and analysis processes which hinders the delivery of coherent business intelligence; especially if the data integration is also performed within the visualisation tool.It can cause companies to deviate more and more from a ‘single version of the truth’ – which is ultimately what every organisation aspires to achieve,” she said.  

As a data-oriented mindset continues to permeate throughout the business world, there is now a real need to ensure that insights are being delivered from comprehensive, assured datasets. Priyanthi suggested that data governance protocols need to catch up with the advancements in technology to ensure this fragmentation does not get out of control. A failure to properly regulate how data is being used may give rise to new information security risks.

The potential pitfall of fragmentation is important to keep in mind when planning your visualisation strategy.Rather than deploying a variety of tools a wiser approach may be to carefully weigh up what you intend to achieve through your visualisation strategy and then choose the tool which best suits those specific aims.

Regardless of the tool you choose to use, implementing the right data-visualisation strategy for your business will give you a real advantage in the market place. 

As we all know that “Big Data is the future” it is crucially important to ensure that your company is ready to capitalise on the business landscape of tomorrow. Improving your data visualisation efforts is a great place to start.