5 Data Analysis & Machine Learning Trends your Business Should Know for 2018

By January 16, 2018 Insights

By David Hamilton, Consultant, Open-i Advisors

Data analytics and machine learning are among the most exciting fields in computer science – and the cutting-edge research going on in these fields is applicable to real-world business problems. With the new year upon us, we wanted to outline some of the interesting areas where big data and machine learning is having a major impact on businesses.

Here are the trends we think every business should be aware of.

1. Narrow AI

Artificial Intelligence has elicited much excitement and also fear around the apparent inevitability of it replacing human thought – and taking over many jobs now staffed by humans. While this shift will undoubtedly happening on a larger scale in the coming years and decades, AI is currently better at specific tasks than as a jack of all trades. Until “General AI” gets smarter so-called “Narrow AI” will have a bigger impact in the shorter-term. Narrow AI involves highly specific machine-learning algorithms aimed at a specific task like understanding language or driving a vehicle. In 2018, businesses need to get ready to embrace AI that can perform specific tasks more quickly and better than humans. Human workers will use Narrow AI as a tool and be able to focus their effort on work that AI can’t yet do.

2. Computing on the Edge

Going from centrally managed networks to distributed cloud networks was a huge shift that allowed for new agility and capabilities. Continuing this trend towards having computing capabilities where and when they’re needed is the edge computing. Instead of data being sent to an off-site server, edge computing promises to streamline the flow of traffic from IoT sensor data and provide real-time data analysis locally. Embedding more functionality at the edge helps overcome the bandwidth constraints of vastly increasing amounts of data.

3. Event-Driven Business Logic

To make data actionable, businesses like to apply conditional rules to data. If the numbers indicate something, it triggers an action. For instance, if your Big Data indicates a certain product will be popular over the course of the next two weeks, more inventory will be ordered. To gain a bigger competitive advantage, Big Data is moving away from batch processing into a real-time event-driven style of rule processing at crucial digital business moments such as at the completion of a purchase order.

4. Data Security is Still a Key Concern

While Big Data is powerful to any company, it can be dangerous in the wrong hands. The traditional approach to security was simple and relatively effective—build a strong, software-based perimeter with limited client and data access. However, hybrid IT, cloud computing, and mobile devices have completely changed the game by pushing IT outside of the physical datacenter. Being careful means understanding the new nature of data security where data needs to be secure and encrypted across a multiple of devices and also while traveling between devices.

5. New Business Sectors will Adopt Big Data Analysis and Machine Learning

We’ve seen examples of how real-time data and machine learning can help do complex logistics, analyze medical records, and even write news stories. Anyone who insists their industry has nothing to gain from data and automation could be giving up on productivity gains and the opportunity to be leaders in their industry.

These are just five trends in which data analytics and machine learning will be continuing to transform business this year. Ignoring these trends is a risk no business should take.



Above photo by Samuel Zeller on Unsplash


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