“There are only two certainties in Big Data today: It won’t look like yesterday’s data infrastructure, and it’ll be very, very fast.” – Matt Asay: Head of Developer Ecosystem at Adobe.
Technology and the power of data science have created huge leaps of growth for businesses who utilise it, and it’s no surprise that the mass increase of worldwide data will mean that Big Data will encounter some big changes in the year ahead.
#1 – COGNITIVE TECHNOLOGIES
Cognitive technologies are constantly evolving, and becoming more and more capable of performing tasks that require human intelligence.
“It is now possible to automate tasks that require human perceptual skills, such as recognising handwriting or identifying faces, and those that require cognitive skills, such as planning, reasoning from partial or uncertain information, and learning.” – Deloitte University Press.
Cognitive systems like IBM Watson are improving business products, processes and insights by allowing systems to interact with humans more naturally, and understand complex questions posed in natural language.
“Computing systems of the past can capture, move and store unstructured data, but they cannot understand it. Cognitive systems can. The application of this breakthrough is ideally suited to address business challenges like scaling human expertise and augmenting human intelligence.” – IBM.
#2 – PRESCRIPTIVE ANALYTICS
“If analytics does not lead to more informed decisions and more effective actions, then why do it at all?” – Mike Gualtieri: Vice President & Principal Analyst at Forrester Research.
Informed decisions lead to better results. Prescriptive analytics incorporates both predictive and descriptive analytics, and is used to determine the best course of action to take in a given situation. It involves a combination of mathematics, analytics and experimentation that help businesses make
better decisions based on logic. When used correctly, it can help businesses optimise production and enhance the customer experience.
“Prescriptive analytics predicts not only what will happen, but also why it will happen providing recommendations regarding actions that will take advantage of the predictions.” – halobi.com
#3 – FAST DATA IS THE NEW BIG DATA
“The argument is that big isn’t necessarily better when it comes to data, and that businesses don’t use a fraction of the data they have access to. Instead, the idea suggests companies should focus on asking the right questions and making use of the data they have — big or otherwise.” – Forbes.
Fast data applies Big Data Analytics to smaller datasets in near-real or real time to mine both structured and unstructured data and quickly gain insight on what action to take. With streaming systems like Apache Storm and Apache Kafka, the value of fast data is being unlocked.
“As organisations have become more familiar with the capabilities of Big Data Analytics solutions, they have begun demanding faster and faster access to insights. For these enterprises, streaming analytics with the ability to analyze data as it is being created, is something of a holy grail.” – Dana Sandu: Marketing Evangelist at SQLstream.
#4 – MACHINE LEARNING & AUTOMATION
“It’s possible to quickly and automatically produce models that can analyse bigger, more complex data and deliver faster, more accurate results – even on a very large scale. The result? High-value predictions that can guide better decisions and smart actions in real time without human intervention.” – sas.
The learning capabilities of machines are growing at a large scale, and connecting people, processes and products in new and exciting ways.
“Your digital business needs to move towards automation now while ML technology is developing rapidly. Machine learning algorithms learn from huge amounts of structured and unstructured data, e.g. text, images, video, voice, body language, and facial expressions. By that it opens a new dimension for machines with limitless applications from healthcare systems to video games and self-driving cars.” – Ronald Van Loon: Director at Advertisement.
Today, machine learning is transforming online businesses and being used by organisations for a myriad of things like fraud detection, real-time ads, pattern recognition, speech analysis and spam-filtering. But in 2018, machine learning is said to become faster and smarter than ever before, while also making better predictions for the future.
“Now machine learning seems to offer a solution for demand forecasting. With the inherent capability to learn from current data, machine learning can help to overcome challenges facing businesses in their demand variations.” – Dataversity.
#5 – AI ENHANCING CYBER SECURITY
“Artificial Intelligence is looking quite interesting for 2018 and the near future with the attempts to apply reinforcement learning to problems, which enables machines to model human psychology in order to make better predictions; or contesting neural networks with generative adversarial networks algorithms which requires less human supervision and enables computers to learn from unlabeled data; making them more intelligent.” – Exastax.
With capabilities of problem-solving and modeling human psychology, enhancements in AI are also said to be a defence mechanism for safeguarding data in the near future.
“Ironically, our best hope to defend against AI-enabled hacking is by using AI. AI can be used to defend and to attack cyber infrastructure, as well as to increase the attack surface that hackers can target, that is, the number of ways for hackers to get into a system. Business leaders are advised to familiarise themselves with the cutting edge of AI safety and security research.” – Harvard Business Review.
For more resources, please see below:
2018 Big Data Predictions
AI & Cyber Security
Machine Learning & Automation