Gartner predicts five big data trends that will dominate 2016

Machine Learning   |   
Published January 20, 2016   |   

Gartner has predicted 5 strategic technologies for 2016. Highlights include, the importance of machine learning, artificial intelligence, the Internet of Things and its impact on business and consumers worldwide.

Even though these technologies have different names, they use data as raw material, and they use huge volumes of data sets to derive value.

Let’s take a look at these technologies.

1. Smart Machines

Smart Machines

Many private companies are using some form of smart machine technology with a limited number of employees to generate revenue.

Gartner recently interviewed representatives of three of the fastest-growing private companies in the world. Each of them was using or piloting some form of smart machine technology, and each had fewer than 150 employees generating $85 to $160 million in annual revenue. Facebook’s October 2014 purchase of the messaging platform WhatsApp ( $22 billion dollars for a company with only 55 employees) is a particularly dramatic example of this trend, and of a new pattern in valuations.

Smart machines can help both enterprises and individuals in two important ways:

  • By fully automating tasks and removing human control (for example, via algorithmic trading or “lights out” factories with no on-site employees).
  • By augmenting the cognitive and physical performance of individuals in a manner that feels like an extension of their own abilities (for example, via decision support or wearable technology).

For instance, the nonprofit online education platform edX has introduced a computer system that grades student essays and short answers on exams.

2. Customer Digital Assistants

digital assistants

While not quite in the league of true artificial intelligence, top technologies for customer digital assistants include face recognition, voice identification, emotion detection, natural language processing, and audience profile data.

After decades of constant improvements in voice recognition and detection technology and face recognition technology from large, high-profile organizations like Adobe, Apple, Google, IBM and Microsoft and others — the technology is now here, and ready for prime time.

Consider Microsoft’s Xbox One and Sony’s PS4, two leading gaming consoles that both have the ability (through Kinect and the PlayStation Camera, respectively) to recognize and sign in players by face,  when they enter a room. Both systems respond to voice commands, and all of these capabilities are used in-game. Some of the promising mobile digital assistant technologies are, Cortana, Google Now, Siri, and Amazon Echo.

Even though digital assistant technologies are used across various industries. Customers are willing to adopt these technologies to help them sift through increasing large amounts of information, choice and purchasing decisions.

3. Internet of things

Internet of things (IOT) is the concept of connecting devices with an on and off switch to the Internet or to each other through the internet.  IOT is widely used in many industries.

Growth of IOT


The above numbers clearly show that the market for IOT is growing at an incredible rate. GE’s Industrial Internet Insights Report predicts that the “Internet of Things” will add $10 to $15 trillion to global GDP over the next 20 years. It is no surprise that employer competition for skills in this space is on the rise.

Both technology and non-technology companies are hiring for IOT.



Source: Wanted Analytics

Fastest growing IOT job positions include systems software developers (215% growth in the past year), information security analysts (113% growth), and computer systems engineers (110% growth). Adding to this, General Electric has advertised 2,104 jobs looking for skills needed to support their industrial internet initiative in the last two years.

4.  Automated composition engines

automated composition engines

Significant advances in machine learning, data integration, and predictive analytics applications have empowered computers to write business content types like reports, white papers, press releases articles, etc.  For example, automated insights have already been employed to robot-write thousands of stories for fantasy football newsletters based on relatively rigid templates.

Content management vendors are adding better content composition and analytic capabilities to their systems. Solutions that combine the ability to find, analyze and assemble data into formats that can be read in natural language, will improve both the speed and the quality of business content delivery. Personal assistants such as Apple’s Siri and Microsoft’s Cortana, and IBM Watson, with its cognitive technology — provide richer and more interactive content. Drones, sensors, wearables, and cameras will create huge volumes of data that needs to be accessed and assimilated into understandable content.

5. Robo-Boss

Robo boss

Robo-bosses will increasingly make decisions that previously could only have been made by human managers. Companies will develop smart machine “contract managers” to measure and supervise the performance of particular worker classes.

Evaluation of employee performance will become even more granular as smart machines become the primary means of analyzing performance. Smart machines can effectively track activities and events that are too difficult for human managers to measure.

Robo-bosses use advanced machine learning techniques like deep learning, to automatically learn and improve with experience. A good example of deep learning is Google’s self-driving car project.


These five trends mark the beginning of a new era for big data analytics. Some, like customer digital assistants and smart machines, threaten the groundwork of big data analytics in general; while others, like Robo-boss and automated composition engines, can be adapted to and taken advantage of.

Look sharp for all these developments, make changes where you can, and enjoy the ride into 2016.