The Terminator, Transcendence, Her, Wall-E; these movies are most definitely a treat for sci-fi lovers like us. Remember the use of animation, cool special effects, stunts, and that jaw-dropping plot-line?
There is another thing that is common amongst the stated movies- Human bots!
Yeah, Artificial Intelligence be wrecking us since 1984; the first Terminator movie!
Machine learning is no different. They have been here for some time and are going to be here forever, subtly embedded in our daily activities.
What makes your facebook or google search a lot easier? Who doesn’t let you feel alone on SNS by recommending ‘people to follow’? What makes you love Netflix so much? Yup, machine learning!
But, they aren’t here just for entertainment purposes per se. They have been a major part of the critical technology and business challenge-solving saga since they were first introduced. Including BI and Big Data!
We’ll be coming to that, but first, let’s know what AI and machine learning actually are and how they differ from each other!
AI and machine learning; these two buzzwords have taken the whole tech world by storm. About a million of the world’s population searches for this specific keyword monthly, according to Google AdWords.
That’s a good amount of traffic, honestly.
Both the concepts look similar, talk about being ahead-of-the-time, are most definitely heavy. So it’s quite common for us to get them mixed.
We’re here to solve it for you. To begin:
Artificial Intelligence (AI): Is the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings (1).
Whereas,
Machine Learning: A subset of Artificial Intelligence (AI) concerning with the implementation of computer software that can learn autonomously (2).
So to conclude, Machine learning is the more logical and algorithm-based subset of AI that uses predictive analytics to present AI out to the world. It finds patterns and comes up with the best suitable answers using prescriptive, cognitive and automated computational techniques. Face recognition, speech recognition, Google answers- they all use machine learning!
Now when you know them, scroll down to get acquainted with AI and Machine learning’s game-changing effect on BI and Big Data!
Gone are days when you could survive with your old-school business intelligence tools. Legacy BI platforms are good, but not good enough to compete with the digitally advanced and automated world.
Thus, we need to embed a bit of future into our past tools. Enter Artificial Intelligence and Machine Learning!
Thanks to them, data is now analysed a hundred times faster with accuracy and automation helps reduce human error to a great extent- an ultimate recipe to increase the organisation’s profits.
The best part, AI and Machine learning aren’t limited to a specific field. Whether you are from machining industry or a hospital, a school or are crucial cloud service providers- they work for all!
The predictive and the detailed nature of AI and machine learning could help businesses improve their performance and cyber security by providing top-class services on:
Other than this, leveraging AI and machine learning could give you a competitive advantage when human resources aren’t available (like with stars and planets discovery), or when you don’t know what lies ahead of you (GPS traffic details, for example), or to get different solutions for different individuals (medical cases are never the same).
These were only a few examples, AI and machine learning is actually making a lot more things possible with its future-assessing capabilities.
In a BI platform, visualisation dashboards are the best place to embed AI techniques. This comes in the form of real-time powered alerts like basic threshold alerts (Absolute value alerts, relative value alerts), pattern recognition alerts, and highly advanced neutral network alerts.
Let’s crack them one by one.
Threshold Alerts: Users are immediately notified when the values go outside the predefined threshold.
Absolute Value Alerts: A type of threshold alert wherein the users are notified when an observed value falls below or exceeds a predefined absolute value.
Relative Value Alerts: Another type of threshold alerts that works when the percentage difference between the observed value and previous value goes beyond or falls below the range defined.
Pattern Recognition Alerts: A specific algorithm- based alert that can help enhance dashboard experience and security.
Neutral Network Alerts: Triggers when any intrusion is detected and automatically activates -anti-malware functions on a network to kill the problem.
Engaging these alerts could help scale and smoothen your business process by defining key factors and alerting you as soon as any disruption occurs.
AI and machine learning are most definitely paving a way for an advanced BI and Big data practices. But, as AI scientists predict, this is just the beginning. We are yet to discover much more things that AI and machine learning are capable of!