Big Analytics And Automation: The Evolution Of Big Data


Big Data has swiftly become a dated, catch-all phrase in the online marketing lexicon, but it is undeniable that the amount of data and the speed at which is delivered, is still increasing at an exponential rate. For example, Gartner has predicted that enterprise data will grow 650 percent between by 2020, and IDC has stated that the world’s information now doubles approximately every 18 months.

Also, the quality of data is constantly changing – ‘good’ data can rapidly become ‘bad’ data. In business, the need to make decisions laser quick, and with reliable, actionable and high-quality data is of paramount importance to stay relevant and ahead of the competition.

BT Group, chief executive, Gavin Patterson, speaking at the MRS conference recently, said:

“The key is not data, the key is insight. You need to be able to identify the signal from the noise.

The most important thing is to take the huge bank of data and turn it into operational insight, and into products and services that we can build out across the business. It should give you a very rich picture, but the key is turning it into series of actions.”

All this needs to take place in a shifting landscape. Memes on social media seem incredibly important one day and then fade into obscurity the next. Hardware needs to be upgraded on a rolling basis or outsourced to the ever-growing cloud. Anyone can like a page, share a link, read a news article but soon it’s already outdated.

It is no surprise that marketers can feel overwhelmed: within a business context, it is typically their responsibility to keep pace with the zeitgeist. Given that it is next to impossible to make sense and take advantage of all the data on an individual level, how can marketers stay ahead of the game?

The ability to harness, interpret and make decisions with the most up-to-date business intelligence will separate the winners from the losers. As Patterson asserts, it is not ‘big data’ alone that will give marketers a competitive edge, but the ability to understand it.

These are the foundations of ‘Big Analytics’ – a phenomenon that has grown so rapidly that data scientists are one of the most in-demand professions in business, and many universities across the world have been busy developing and rolling out new Bachelor’s and Master’s degrees in Business Analytics.

The Dangers Of Big Data – And The Solutions

Organisations have become very ‘data hungry’ and invest heavily in a variety of ways to capture data from a number of sources. There is a priority to collect increasing amounts of data to give a more representative sample of customers, prospects, or any other target audience. However, not all data has the same value, and errors in the collection, examination, and interpretation of data can cause critical problems in the future. What organisations really want, is the ability to discover anything that they don’t know and confirm everything they think they know – which requires a focus on analytics as well as simple data gathering.

To tell the whole story behind a decision, a business first needs the technology to capture relevant and accurate data from all the sources of information available – including social media, transactional and financial data, point-of-sale data, survey data, and any other source available. The sources themselves are set to expand even further with the evolution of the Internet of Things – every smart device is another potential data creator. The next step is to use the right technologies and partners to see the patterns in the data, and assess what has value and then to provide actionable recommendations.

Taking Action Through Automation

First, marketers need to balance their investment between both data collection and analytics – and now automation. Traditional analytics undertaken by agencies can take weeks or months to compile – and this method is being rendered increasingly obsolete by the speed at which brands and consumers now respond to each other.

Not only is it impossible to gather and synthesize all the information manually, but automation is the only way an organisation can reach into the myriad data sources, gather the necessary information, and provide meaningful analytics.

Automated analytics is destined to go further faster. Automated recommendations are the latest development, and these will continue to gather speed and sophistication in the months and years to come. Decision-makers will no longer have to comb through data and make subjective decisions based on their own interpretations. Instead, they’ll get a list of recommendations based on evident trends in the data. That will further reduce the time it takes to travel from problem to solution, and will mean marketers will be able to create and implement campaigns at the moment of peak relevance. It’s the next logical step in the evolution of automated analytics tools, and will mean brands can reach consumers within ideal timeframes.

Companies that are not taking up residence in the land of Big Analytics and automated tools are destined to fall behind. The real competitive edge will be held not be the organisations who have the most data – but by those who can action it most effectively.