Four challenges in an era of visualisation

Four challenges in an era of visualisation

Four challenges in an era of visualisation
The world nowadays is full of all sorts of data. With so much information from such a wide range of sources being compiled on a daily basis, we need to be capable of processing and analysing it extremely quickly. We also want information and knowledge immediately to hand, and are becoming almost spoiled by its instant availability. At the same time, we live in an age where everything is compressed into ever smaller chunks: through Twitter, text messages, one-second movies and other similar tools.

The result is that we want insights now, and in bite-sized chunks, please.

And this trend is seen more and more in the business domain too. One of its manifestations is a booming demand for 2.0 data visualisations, which are characterised by self-serviceability, scalability, interactivity and analytical character. But this creates its own challenges.

Over the last couple of years, we have seen a transformation in business intelligence (BI). Today, nobody can afford to wait for weeks or months for a report to be compiled. The traditional approach, now often perceived as obsolete, entrusted such tasks to the IT department, to process on a ‘first come, first served’ basis, often taking a long time because of the high level of demand. But more than half (57%) of respondents in a study conducted by TDWI indicated that a catalyst for introducing a self-service BI platform was a desire to move away from this model.

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Instead, analysts nowadays must be capable of adding new data fast, defining data hierarchies, and balancing detailed and aggregated datasets. There are a huge number of queries coming from business executives, so the process of testing, developing and expanding business analyses must be performed at high speed.

Another factor which shapes expectations of BI is a substantial increase in the level of analytic awareness among business executives. Company directors and board members are now much more likely to make precise demands for complex statistics. They also expect to see visually attractive presentations of different time ranges, other business segments, or geographical areas, and to be able to interrogate them. By choosing a bar, dashboard or point, they expect to be able to proceed with a detailed analysis and supplement tables or charts with notes, or share their insights with others.

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