Big Data is, almost literally, everywhere these days. We now understand that companies cannot exist in the modern market without adopting some form of data strategy, and that becoming data-centric is the only way to survive in the industry.


However, trends come and trends go, so what about Big Data? What about all that time and money invested in setting your organization up for data-centric success? Was it all a waste of time?

No, it was not. Let’s take a look at what we can expect in the coming year and how data visualization and analytics are needed more now than ever before.

Increasing Volumes Indicate Big Data Is Here to Stay

Anyone concerned that big data was merely a flash in the pan can rest easy; it’s here to stay. In fact, the volumes of data at our disposal are increasing.

The data journey, for many of us, goes something like this: we begin with anxiety – how are we going to find the data we need? This is followed by relief as we discover that data is, in fact, abundant and readily available. Finally, the anxiety returns – just what the heck are we going to do with all this data?

This data surfeit is only going to increase. Consider how many internet-enabled devices there are doing the rounds, including desktop and laptop computers, tablets, and smartphones. Now, consider the Internet of Things, the smart connectivity of previously inert objects. All of these things are miniature data generators, pumping out facts and figures for us to harness and use.

It’s time to get excited – and a little nervous – about the sheer volume of data coming our way.

What does this mean for visuals and analytics?

Well, all that data needs to go somewhere. Simply letting it flow out into the void is a waste; instead, we need to harness its power, siphoning it off and putting it to good use.

Data visualization is the ultimate tool for making sense of figures of this magnitude, turning an unwieldy mass of data into a convenient reference point. Analytics, similarly, are necessary for understanding the data points which our companies, and the markets they operate in, throw our way.

To put it simply, expect a far greater demand for visuals and analytics than ever before, and expect this demand to increase even further in coming years.

The Rise of DaaS – Data as a Service

The SaaS – Software as a Service – business model is a lucrative one. A company develops software for managing customer interaction, enhancing security across a network, or enabling collaborative work between separate departments, and then they farm this out to buyers.

Rather than gaining a one-off purchase fee, these companies can enjoy long-term subscriptions, along with all the benefits that this model provides. If the service is a good one, the buyer will feel that they are getting a good deal too. It’s win-win.

As demand for data increases, expect more and more market-savvy organizations to build similar business models around data. In this climate of data-centricity, facts, figures, statistics and reports have become a sort of currency; a valuable resource to be mined and monetized.

This could mean charging a subscription fee for access to data in a specific field, or for applying data-focused processes within small and medium-sized businesses.

What does this mean for visuals and analytics?

There are two ways to approach this. Perhaps you have a solid set of reporting and data analysis functions already implemented within your business, and you are looking for a way to achieve additional financial value from these. In this instance, you may be interested in looking into a DaaS business model.

On the other hand, you may feel reluctant to pay a company to provide you with data, but also concerned that missing out on juicy insights could see your organization left behind in the marketplace. This translates to an unprecedented need for visualization and analytics, gathering, interpreting and implementing your own data as and when required.

Either way, powerful visualization and analytic capabilities will play vital roles in this new market landscape.

Direct Integration with Physical Processes

Internet connectivity is not the luxury it once was; it is increasingly becoming a standard across the board. We wouldn’t buy a cellphone or word processor unless it could connect to the internet, but such connectivity goes beyond even this.

With more data comes more possibility. As early as 2015, Gartner Inc.’s Doug Laney, reporting for Forbes, was describing the rise of ‘smart machines’ and their increasing prevalence within industry and business. This ranges from the use of algorithmic predictions within stock market trading, to energy-saving automation within factories and industrial facilities.

While this represents a solid solution, and a serious leap forward in the commercial application of technology, it also generates problems of its own. Perhaps ‘problems’ is the wrong word – perhaps ‘considerations’ is more appropriate; as we implement these ‘smart machines and mechanisms’ in business, there are new questions to be considered.

How can we oversee these new systems? How can we gauge their level of success? How can we design and hone their next generation?

Data is going to play a big part as we strive to answer all of these questions.

What Does This Mean for Visuals and Analytics?

As we have discussed above, increased connectivity equals more data, and more data equals an increased need for data-handling and management processes. Would you be comfortable implementing a system within your organization unless you fully understood it and its benefits? I guess the answer to this is ‘no.’

So, we must use visuals and analytics to get to grips with these exciting developments, and to keep track of the benefits they provide to businesses. These tools become vital as we seek to demonstrate the worth of the systems we are putting in place, as we aim to enhance their benefit and overall efficacy, and as we reposition our organizations in response.

In short, the data tide is continuing unabated, and you can bet that visuals and analytics are going to be on the front line for the foreseeable future. It’s time to prepare for the next phase in the journey of Big Data.

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