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Get more Value From Big Data With Visualisation-Based Data Discovery Tools

Published on 03 July 13
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The purpose of big data is to provide businesses with the right tools required to handle the ever-increasing stacks of information that they accrue while working on new innovations and meeting the needs of customers and clients. It is no longer enough simply to store this information for occasional reference, since the agility of a company relies on its ability to glean insights from data and use these to fuel service improvements and catalyse the creation of new products.

The problem is that big data alone is not necessarily suited to delivering on this promise in a manner that is easy to digest. In fact it can be an overwhelming environment that is of little use to employees and managers. It is for this reason that significant growth of 30% annually is predicted by Gartner in the area of visualisation-based data discovery tools over the next two years.

This type of solution can turn torrents of esoteric and unwieldy data into the kind of package that enterprise staff will find eminently usable. It also makes it possible to meld data from a variety of sources to deliver even deeper insights. Information harvested from social media, video interactions, log files and many other platforms can be combined and assessed in parallel, unearthing the kind of findings that might otherwise be obscured and ensuring that businesses can get the best possible value from their big data service.

The benefits of visualisation-based data discovery tools are already clear to the growing number of businesses that have adopted them, but for firms who might make the leap when given a bit more of a push it is important to establish the main motivations for migration. It is also necessary to first work out which challenges are posed by big data so that these tools are seen in the correct context.
Big Data Challenges

Businesses have sought to generate visual representations of data analytics for many years, previously relying on professionals to work through this process manually over the course of several weeks and then present the most pertinent findings in a fashion that can be consumed and understood by other members of the team.

In the digital age and with big data rising to prominence, this approach is simply inadequate, because being able to assess and unlock the potential of vast stores of information is a task too great for in-house analysts. An Intel report recognises that the volume, variety and velocity of information in a big data environment can be such that the challenges posed with be insurmountable for some companies.

Big data is generally unstructured and a survey from IBM found that only a quarter of the IT professionals questioned had the means to effectively analyse information in this state, such as that presented to them in the form of voice and video files. A little over a third were able to get a handle on streaming data and harness a portion of its underlying value. In terms of the time pressures that are put upon businesses by big data, if there is no way to wring relevant insights from information in real time then further inefficiencies will prove to be a hindrance rather than a help. A further pressure is emerging in the wake of mobile and remote working becoming more common, since businesses need to democratise access to information and analytical tools so that a more geographically diffuse workforce can still collaborate and operate effectively.

Intel's IT Manager Survey found that the most popular way to address the challenges posed by big data is through visualisation tools, although the majority of businesses expressed a desire to gain help with making the transition.
Get more Value From Big Data With Visualisation-Based Data Discovery Tools - Image 1
Visualising the Problem

Visualisation-based data discovery tools are still relatively new, which is why businesses may be unfamiliar with their capabilities and why early adopters stand to gain the most from migrating sooner rather than later.

That sense of democratisation of data analytics is something which should be seen as key in this case, because the idea is not only to make it faster and easier to analyse data from multiple sources, but to make this a process which does not require a specialist set of skills. Rather than relying on the work of a small group of professionals, it is faster and more sensible to give every employee the ability to generate usable and relevant visualisations of data that has been analysed. This self-service approach means that productivity will be improved just as costs are being reduced, which means the main challenges of big data are no longer so significant.

When this visualised data is then accessible from and transferable to portable devices such as smartphones and tablets, the mobility of a workforce is significantly improved and businesses will be able to encourage BYOD (bring your own device) culture rather than feel that it is something that needs to be curbed.
Enviable Features

So what can businesses expect to experience when adopting visualisation-based data discovery tools and what features might be worth seeking out during the decision-making process prior to migration?

Real time data analysis is a top priority and something which is made possible through these tools, along with the ability to create presentations and reports quickly and make them as engaging as possible through the inclusion of interactive elements. Data and the tools to manage it also need to be accessible to staff whether they are at their desks or out in the field and using a smart device. Collaboration should be achievable in a secure, safe environment that facilitates sharing, so that team members can make valid contributions and work towards a collective goal.

When it comes to the actual interface used in visualisation-based data discovery tools, this has to be something that is intuitive enough to require minimal training to master, as well as enabling deeper insights into the data. Touch optimisation is also important, particularly with tactile displays not only featuring on smartphones and laptops but also on a growing number of enterprise-oriented laptop computers and desktop workstations.

Although the volume, variety and velocity of information in a big data environment can feel overwhelming to the uninitiated, the reality is that with visualisation-based data discovery tools it is easier to wrangle these three under control and ultimately convert them into value for the company.

Among all this it is still possible to preserve best practice and ensure that security is up to scratch, so there really is little reason for businesses that now have large amounts of information to analyse to put off adopting this type of big data solution.
The purpose of big data is to provide businesses with the right tools required to handle the ever-increasing stacks of information that they accrue while working on new innovations and meeting the needs of customers and clients. It is no longer enough simply to store this information for occasional reference, since the agility of a company relies on its ability to glean insights from data and use these to fuel service improvements and catalyse the creation of new products.

The problem is that big data alone is not necessarily suited to delivering on this promise in a manner that is easy to digest. In fact it can be an overwhelming environment that is of little use to employees and managers. It is for this reason that significant growth of 30% annually is predicted by Gartner in the area of visualisation-based data discovery tools over the next two years.

This type of solution can turn torrents of esoteric and unwieldy data into the kind of package that enterprise staff will find eminently usable. It also makes it possible to meld data from a variety of sources to deliver even deeper insights. Information harvested from social media, video interactions, log files and many other platforms can be combined and assessed in parallel, unearthing the kind of findings that might otherwise be obscured and ensuring that businesses can get the best possible value from their big data service.

The benefits of visualisation-based data discovery tools are already clear to the growing number of businesses that have adopted them, but for firms who might make the leap when given a bit more of a push it is important to establish the main motivations for migration. It is also necessary to first work out which challenges are posed by big data so that these tools are seen in the correct context.

Big Data Challenges

Businesses have sought to generate visual representations of data analytics for many years, previously relying on professionals to work through this process manually over the course of several weeks and then present the most pertinent findings in a fashion that can be consumed and understood by other members of the team.

In the digital age and with big data rising to prominence, this approach is simply inadequate, because being able to assess and unlock the potential of vast stores of information is a task too great for in-house analysts. An Intel report recognises that the volume, variety and velocity of information in a big data environment can be such that the challenges posed with be insurmountable for some companies.

Big data is generally unstructured and a survey from IBM found that only a quarter of the IT professionals questioned had the means to effectively analyse information in this state, such as that presented to them in the form of voice and video files. A little over a third were able to get a handle on streaming data and harness a portion of its underlying value. In terms of the time pressures that are put upon businesses by big data, if there is no way to wring relevant insights from information in real time then further inefficiencies will prove to be a hindrance rather than a help. A further pressure is emerging in the wake of mobile and remote working becoming more common, since businesses need to democratise access to information and analytical tools so that a more geographically diffuse workforce can still collaborate and operate effectively.

Intel's IT Manager Survey found that the most popular way to address the challenges posed by big data is through visualisation tools, although the majority of businesses expressed a desire to gain help with making the transition.

Get more Value From Big Data With Visualisation-Based Data Discovery Tools - Image 1

Visualising the Problem

Visualisation-based data discovery tools are still relatively new, which is why businesses may be unfamiliar with their capabilities and why early adopters stand to gain the most from migrating sooner rather than later.

That sense of democratisation of data analytics is something which should be seen as key in this case, because the idea is not only to make it faster and easier to analyse data from multiple sources, but to make this a process which does not require a specialist set of skills. Rather than relying on the work of a small group of professionals, it is faster and more sensible to give every employee the ability to generate usable and relevant visualisations of data that has been analysed. This self-service approach means that productivity will be improved just as costs are being reduced, which means the main challenges of big data are no longer so significant.

When this visualised data is then accessible from and transferable to portable devices such as smartphones and tablets, the mobility of a workforce is significantly improved and businesses will be able to encourage BYOD (bring your own device) culture rather than feel that it is something that needs to be curbed.

Enviable Features

So what can businesses expect to experience when adopting visualisation-based data discovery tools and what features might be worth seeking out during the decision-making process prior to migration?

Real time data analysis is a top priority and something which is made possible through these tools, along with the ability to create presentations and reports quickly and make them as engaging as possible through the inclusion of interactive elements. Data and the tools to manage it also need to be accessible to staff whether they are at their desks or out in the field and using a smart device. Collaboration should be achievable in a secure, safe environment that facilitates sharing, so that team members can make valid contributions and work towards a collective goal.

When it comes to the actual interface used in visualisation-based data discovery tools, this has to be something that is intuitive enough to require minimal training to master, as well as enabling deeper insights into the data. Touch optimisation is also important, particularly with tactile displays not only featuring on smartphones and laptops but also on a growing number of enterprise-oriented laptop computers and desktop workstations.

Although the volume, variety and velocity of information in a big data environment can feel overwhelming to the uninitiated, the reality is that with visualisation-based data discovery tools it is easier to wrangle these three under control and ultimately convert them into value for the company.

Among all this it is still possible to preserve best practice and ensure that security is up to scratch, so there really is little reason for businesses that now have large amounts of information to analyse to put off adopting this type of big data solution.

This blog is listed under Data & Information Management Community

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