Where’s the Best View for Big Data Visualisation?

Where’s the Best View for Big Data Visualisation?

Where’s the Best View for Big Data Visualisation?

Opinion: Jonathan Priestley, Senior Vice President with MultiTaction provides examples of how large scale interactive visualisation democratises big data by letting leadership teams really get in touch with the big picture.

Once you have coped with all the issues around the four Vs of big data - volume, velocity, veracity and variety - you need a fifth V to start making sense of it. Many vendors provide business with the ability to import data from every conceivable database and slice and dice it in many different ways to generate insights through powerful visualisation.

However, too often these visualisations are small snapshots in a little window as opposed to a dynamic big picture that lets you look at disparate data sources in parrallel. In addition to visualisation you need the viewing technology that can display information from a wide range of systems and allow leaders to interact with it to derive actionable outcomes.

Without this you have the common scenario of senior decision-makers coming together to review static reports only to grow frustrated because they cannot question and interact with information to get the insights they need. What follows is a request for further information and the conclusion of the meeting without any actionable outcomes.

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The Gartner report, Magic Quadrant for BI & Analytics Platforms 2015 highlighted how business demands interactive styles of analysis and advanced analytics without the need for IT or data science skills. One of the key requirements identified when it came to enabling, producing and consuming data, was a set of robust tools to visualise the data in meaningful ways that are interactive.

Over in Canada at the National Basketball Association's Toronto Raptors basketball team, a new facility designed by IBM Interactive Experience and powered by IBM Watson cognitive business technology provides some useful lessons on what works.

There the big data includes trade-off analytics which assess possible team roster combinations against a variety of criteria and a personality insights module with linguistic analytics to understand player personality and social characteristics that align with organisational culture. And there is also the facility to further analyse public news sources to round out player profiles.

So far so good when it comes gathering, analysing and visualising data! But people need the means to interact with the data in a meaningful and dynamic way. In the Toronto Raptors case, the answer was the creation of a special 'War Room' which uses interactive touch-screens, formatted in table and wall formats, to show data visualisations and help better understand the data through touch screen interaction.

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