Everyday the human race creates 2.5 quintillion bytes of data.
2.5 quintillion bytes … that’s 2.5 followed by 17 zeros.
Most of this data is generated at extremely high speeds from diverse sources, including audio, video, social, online activity, cloud applications, and text streams.
This massive amount of complex, real-time, historical, structured, and unstructured data is commonly known as “Big Data.”
And big data is big business. The International Data Corporation (IDC) estimates that big data technology and services will become a 48.6 billion dollar market by 2019.
Given the 2.5 quintillion bytes of data we produce everyday, 2016 promises see nothing but the growth of all things “big data” related.
“The word of 2016 is ‘activation,’ as in data activation. This is the year that companies will get serious about stitching together the various stores of data across the enterprise and through this be able to activate the data to drive a serious competitive advantage through data science.”
To keep you at the top of the big data game … here are four game-changing predictions for analytics in 2016.
1. Analytics will be “micro”
Welcome to the era of microservices.
Unlike traditional monolithic servers, which run multiple applications in a single (bulky) system, microservices “separate components into discrete functional elements or individual services.” These components work together by utilizing customized APIs, thereby reducing complexity (and testing time), increasing scalability, and enhancing efficiency.
In other words, big data will go small with an increasingly microservice-driven business landscape by being connected to systems and processes via an API.
What’s more, these microservers will allow analytics to be embedded everywhere.
Gil Press for Forbes reports, “IIA predicts that computing will become increasingly microservice-enabled, where everything – including analytics – will be connected via an API. … Embedded data analytics will provide U.S. enterprises $60+ billion in annual savings by 2020.”
2. Analytics will be real-time
Extracting real-time intelligence from continuous data streams is one of the many thrills of big data analytics.
“2016 will be the year that the definition for business intelligence shifts, from on-premise solutions delivering rear-window insights to solutions that deliver continuous intelligence in real-time,” says Ramin Sayar, the President and CEO of Sumo Logic
The most agile organizations understand the importance of producing, shipping, testing, and pivoting in quick succession. Real-time data will narrow the gaps between “data, insight and action,” thereby enabling you to make faster decisions and adapt more quickly customers feedback.
By leveraging the insights of real-time analytics, companies can sustain their competitive edge, innovative drive, and customer loyalty. But that’s not all …
3. Analytics will be predictive
Traditionally, analytics have followed action.
For years, businesses have used both external and internal data after the fact to assess customer behavior and adapt their services accordingly. Reactive analytics, however, will increasingly become a thing of the past. Why? Because reactive analytics do not bode well if you want to get ahead of your customers and competition.
Instead, predictive analytics are the future.
“With the dawn of the ‘zettabyte era’, and the world churning out more than a trillion gigabytes of data, 2016 will see businesses looking to predictive analytics to uncover trends and patterns and gain unprecedented insight into customers, businesses and markets,” says Mark Darbyshire, Chief Technologist at SAP UKI
In addition, according to the the B2B Predictive Analytics Technology Report by TopoBlog, predictive analytics is one of the hottest technologies in the B2B world, with almost 37% of high-growth companies investing in this field over the next twelve months.
Despite the buzz surrounding predictive analytics, this industry is still in the nascent stage. 2016 is the year when businesses will realize the importance of predictive analytics in order to forge stronger customer relationships and fashion better business outcomes.
4. Analytics will be integrated
According to Capgemini Consulting’s report Cracking the Data Conundrum, the two primary challenges facing big data implementation are siloed data — 79% have not integrated their data sources — and ineffective team coordination – more than 50% do not have joint product teams.
Data silos are scattered and standalone units of data. And siloed data is greatest nemesis of growth. They exist in isolation, without ever interacting with, cross-referencing, or augmenting the other self-contained data sets. Such exclusivity results in a fragmented business approach, untimely decisions, and inaccurate conclusions.
Aside from data silos, major organizations also lack departmental cohesiveness and central planning, leading to an unproductive distribution of resources, uneven information flow, and unprioritized resources.
In 2016, more companies will be dedicated towards creating an integrated analytics system that identifies market opportunities, improves communication, streamlines marketing and sales processes, and creates a unified environment of growth.
“I think the one thing that really excites me is the continued convergence of data. Businesses are merging more first- and third-party data sets to draw deeper insights about existing customers, attract new customers and, ultimately, increase revenue,” explains Justin Cutroni, Analytics Evangelist at Google
Solving the integration problem will make it much easier to solve the insights problem. 2016 is the year when analytics integration will jump to one of the top business priorities.
Although big data — as a concept — has been around for a while, it is going to flourish as the “breakthrough technology of 2016.”
Businesses will finally wake up to the reality that this often cluttered, confused and continuous jumble of information holds the key to a profitable business that delights your customers.
Through four trends:
This means, your organization must nurture a culture of connectedness, creativity, communication and coordination in order to derive the wholesome benefits of big data analytics.