“Carpe diem … seize the day,” writes Roger Schenck, Manager of Content Promotions at Chemical Abstracts Service (CAS). “This Latin phrase, coined by the Roman poet Horace in 23 BC, is used often to encourage us to take full advantage of the opportunities each day provides. In modern times with seemingly limitless amounts of data on any conceivable subject available at our fingertips, organizations globally are developing strategies to leverage this growing data volume to enhance business success — hence, ‘Carpe Datem’ may be a more timely adaptation of this phrase.”[1] He adds:

“Big data has become one of the hot topics in information management and analytics. … Almost every industry is looking for new ways to derive value from big data, and there’s no doubt that it’s used to solve problems, enhance productivity and increase convenience for all of us.”

The term “big data” may eventually fall into disuse (because “big” won’t adequately describe the immense size of databases needing to be analyzed); but, data analytics is becoming the lifeblood of digital enterprises. I was recently contacted by Maria Fraser of Retail Vision concerning some facts her company had gathered about big data and the future which John Ibbotson (@johnibbotson1) published in an interesting infographic. Although the infographic is aimed at a UK audience, some of the facts Ibbotson presents are global. “The future of big data,” Ibbotson writes, “is quite simply looking bigger than ever. In today’s digital world, data analysis is the cornerstone for almost everything, and it’s no different in the world of retail.” He continues:

“In a study published by the International Data Corporation, it was found that:

• Currently, 2.7 zettabytes of data exist in the digital universe.
• The digital universe is doubling every 2 years.
• By 2020, the size of the digital universe is expected to reach 40,000 EB (Exabytes).
• More than 570 new websites are created every minute.
• 90% of the world’s data has been created in the last 2 years
• 70% of the digital universe or 900 exabytes is generated by users
• 80% of all data is stored by enterprises

“In today’s digital world, data analysis is the cornerstone for almost everything — from making decisions with far reaching effects to predicting future trends and market forces. … Traditional data processing tools and methodologies are simply inadequate for handling, processing and meaningfully analyzing the flood of data which is being generated every day. … Big Data analytics has had a drastic affect on a vast array of elements, all of which are beneficial to any business. These include:

• Better social influencer marketing.
• More accurate business insights.
• Segmentation of customer base.
• Identifying sales and market opportunities.
• Automated decision making for real-time processes.
• Detection of fraud.
• Quantification of risks.
• Better planning and forecasting.
• Identifying cost drivers.

“Big Data is making a big splash already and it’s set to have far reaching effects across sectors and industries.”

Dr. Erik Jensen, who teaches at Ryerson University, insists that big data analytics for businesses are no longer optional.[2] This is especially true, he asserts, for businesses selling products to the public. The rise of social media means that businesses can obtain and analyze consumer attitudes about their products in near-real time. “Today,” Jensen writes, “it’s no longer an option to not use big data, because everyone else is already using it. A study done by Simply Measured found that 99 per cent of brands are on Twitter, with 30 per cent of them having a dedicated customer service handle. Social media has to be a core component of your customer service strategy, or you risk becoming obsolete.” Dave Wagner, director of Market development at TeamQuest, agrees. “More and more companies, both large and small,” he writes, “are beginning to utilize big data and associated analysis approaches as a way to gain information to better support their company and serve their customers.”[3] He adds, “With the use of big data becoming more and more important to businesses, it is even more vital for them to find a way to analyze the ever (faster) growing disparate data coursing through their environments and give it meaning.” Ben Rossi (@BenRossi89) likens big data analytics to the gold rush in the late 19th century.[4] He explains:

“The 1800s were all about mining — gold, iron and other metals. The 1900s were all about drilling — oil, natural gas and shale oil. The 2000s are again going to be focused on mining, but of a different kind — data. Everything in the modern world from humans to machines is a data factory. The total data accumulated in 2012 and 2013 was more than nine times of the total data created till 2011. By 2020 this data is expected to reach 44 Zettabytes. Data is being stored in servers across the globe, creating veritable data mines across multiple locations. North America leads the group in this data storage followed by Europe, Japan, China, Middle East, India and South America in that order. Enterprises around the world have realised the value of these data mines and the technology for its proper mining and use is evolving every day. Proprietary algorithms are being developed to comb this data for trends, patterns and hidden nuances by enterprises around the world.”

As Rossi notes, humans can no longer adequately mine data. Only computer systems utilizing artificial intelligence (AI) have enough power to adequately do the job. In fact, cognitive computing systems are likely to form the foundation of almost every company’s efforts to mine data in the decades ahead. Accenture’s latest technology vision entitled “From Digitally Disrupted to Digital Disrupter,” Accenture analysts state that cognitive computing will provide the “ultimate long-term solution” for many business challenges. They write:

“What if … machines could be taught to leverage data, learn from it, and, with a little guidance, figure out what to do with it? That’s the power of machine learning — which is a major building block of the ultimate long-term solution: cognitive computing. Rather than being programmed for specific tasks, machine learning systems gain knowledge from data as ‘experience’ and then generalize what they’ve learned in upcoming situations. Cognitive computing technology builds on that by incorporating components of artificial intelligence to convey insights in seamless, natural ways to help humans or machines accomplish what they could not on their own. At its most advanced, cognitive computing … masks complexity by harnessing the power of data to help business users ask and answer strategic questions in a data-driven way.”

The bottom line is that, if you want to transform into a digital enterprise, the full realization of that goal won’t be achieved without the implementation of cognitive computing solutions and the analytics they can provide. That’s why I agree with Schenck; the watchword for today’s businesses should be “Carpe Datem.”

Footnotes
[1] Roger Schenck, “‘Carpe Datem’: Seizing the Opportunities of Big Data to Drive Insight,” R&D, 19 November 2014.
[2] Erik Jensen, “Big data for big business – analytics are no longer optional,” The Globe and Mail, 15 August 2015.
[3] Dave Wagner, “The importance of big data analytics in business,” TechRadar, 2 October 2014.
[4] Ben Rossi, “Data revolution: the gold rush of the 21st century,” InformationAge, 21 August 2015.