The domain of data visualisation is changing fast. From a tool to envisage trends and elucidate patterns to a gateway into the rapidly expanding profusion of visual data that exist, the realm of big data is evolving rapidly. More companies are using big data to glean useful, business-centric insights but traditional infrastructures are not up to the task to handle the tremendous quantities of data generated daily.
This highlights the issue of using big data in a way that stakeholders can understand and use effectively. Classical charting and graphing templates miss the mark with big data as it does not capture the entire data set, nor does it offer the potential to visualize insightful information. Thus visual analytics is bringing more to the party with respect to big data and presenting businesses with a high performance way to analyse data quickly and conveniently.
With any new technology, there are bound to be some challenges on the road to successful innovation, and the same is true for data visualization. The limitations of big data, and consequently big data visualization, are generally the nascent technology required to meet computational speed needs, deciphering and understanding the data, ensuring the quality of data and dealing with statistical issues. In order to deliver actionable insights by leveraging the power of big data, there are a few considerations that can help avoid problems down the line.
Avoiding data visualisation pitfalls starts with choosing the right tools for the job. Before embarking on a big data endeavor it is critical to evaluate the software offerings effectively to decide whether it will meet the brief and fulfill the organization’s expectations.
Fitting a tool correctly into your business model can have positive consequences in all facets. In order to ensure a good fit, it’s essential that the company have a good idea of the potential users in mind and how they are going to apply the tool. For example, with the use of server security protocols, multiple requirements, customization and necessities will need to be taken into consideration before decisions are made. Thus, it makes sense to develop a vision statement prior to tool assessment to ensure that the tools are appraised in line with the company’s expectations for future development.
