jKool Blog

A blog about big data & streaming analytics.

Why machine learning will decide which IoT ‘things’ survive

Why machine learning will decide which IoT ‘things’ survive – No billion-dollar machine could replace a doctor. But a $25 machine can tell you when you need one.

In 1996, the ER at Cook County Hospital of Chicago used an algorithm to determine when a patient with chest pain was in danger of having a […]

By |February 24th, 2017|machine learning|0 Comments

4 keys to transforming an organization with Artificial Intelligence

In many ways, we’re close to a tipping point in the development of artificial intelligence technologies, with fleets of self-driving cars, hive drones, automated retail experiences, and more. Companies of every size now must grapple with how AI will affect and possibly eliminate their sector, and how they can adapt and leverage AI and machine […]

By |February 23rd, 2017|AI|0 Comments

What are the technology trends for 2017 and beyond?

What are the technology trends for 2017 and beyond? Networking, connectivity, security, artificial intelligence and workforce engagement – these are what is changing the way we live and work, and driving new business models and use cases.
Mike Weston, Vice President of Cisco Middle East, looks at these different points of technology inflexion that will […]

By |February 22nd, 2017|Digital Transformation|0 Comments

What does digital transformation mean for your industry?

What does digital transformation mean for your industry? Cloud technology continues to disrupt existing business models across industries, including manufacturing, food and retail.

With a powerful, scalable computing power that can harness machine learning, the internet of things and actionable intelligence, there is no doubt cloud technology drives better decision making.

Modern cloud technology enables companies […]

By |February 21st, 2017|Digital Transformation|0 Comments

10 Interesting Business Use Cases of Internet of Things (IoT)

The term “Internet of Things” often throws people, even in the technology industry, off balance. They begin struggling for definitions, explanations, market statistics and what not. There are those who throw multiple spanners in the works by citing security concerns (like they did with cloud). And then, those who generally do a lot of huffing and puffing.

Nothing wrong with that, actually. Any new or not-yet-mature technology segment goes through its own cycle of hype, hazards and hurrahs. So there’s no reason to treat IoT any different. Except perhaps that IoT is much bigger than a typical flavor-of-the-season type technology. (Without giving conflicting numbers but to keep things in some perspective, by 2020, billions of things/devices are to be connected and trillions of dollars in additional value will be generated.)


By |February 17th, 2017|Internet of Things|0 Comments

Big Data Analytics: Why Are They So Important?

Since big data analytics play an important role in gathering data and producing significant knowledge that indicates new business opportunities, companies can act according to those smart insights. That will make them not only more efficient, but likely more profitable in the long run, since customers will have their needs satisfied better, because they […]

By |February 16th, 2017|Big Data Analytics|0 Comments

Realizing The Potential Of Big Data And Analytics

It’s not what you know. It’s what you do with what you know. That’s something companies worldwide will be learning—for better or worse—in the coming year when it comes to big data.

Gurus among us have proclaimed 2017 will be the year big data goes mainstream. If you’re anything like me, you may be wondering […]

By |February 15th, 2017|Analytics, Big Data|0 Comments

How You Can Improve Customer Experience With Fast Data Analytics

In today’s constantly connected world, customers expect more than ever before from the companies they do business with. With the emergence of big data, businesses have been able to better meet and exceed customer expectations thanks to analytics and data science. However, the role of data in your business’ success doesn’t end with big data – now you can take your data mining and analytics to the next level to improve customer service and your business’ overall customer experience faster than you ever thought possible.
Fast data is basically the next step for analysis and application of large data sets (big data). With fast data, big data analytics can be applied to smaller data sets in real time to solve a number of problems for businesses across multiple industries. The goal of fast data analytics services is to mine raw data in real time and provide actionable information that businesses can use to improve their customer experience.
“Fast data analytics allows you to
turn raw data into actionable insights instantly”
Connect with Albert Mavashev
Co-author, CTO & Evangelist at jKool


Machine learning vs AI

People often conflate AI with machine learning, but there are key differences

Two of the biggest trends in technology right now are machine learning and artificial intelligence. In fact, the two terms are used almost interchangeably. However, there are subtle but important differences between them both.

In many ways, machine learning is a subset of artificial intelligence. Also, the term AI is older than machine learning.
What’s the difference?
At its heart, artificial intelligence involves the attempt to make machines think in the way humans do. The famous Turing test says that a system can be said to be intelligent if a human judge cannot distinguish the system’s behaviour from that of a human. However, current technology is far off achieving this, so artificial intelligence at the moment simply means creating systems that are good at doing what humans are good at. It is a catch-all term.
Machine learning also harks back to the middle of the twentieth century. Arthur Samuel defined machine learning as “the ability to learn without being explicitly programmed”.


By |February 13th, 2017|AI, machine learning|0 Comments

The Top 5 Banking Trends for 2017

Without a doubt, 2016 was the year ‘disruption’ became tangible. Events like Brexit, the U.S. election and India’s demonetization exercise brought home the reality we are living in a fast-changing global society where a sense of anti-establishment and rebellion is accelerating change. This shows no sign of stopping in 2017, with new technologies allowing banks to offer service levels more synonymous with hospitality than financial services, and with established technologies like artificial intelligence and robotic process automation seeing a resurgence in combination with new voice commerce models, IoT data, and robo advisors to offer more personal, more contextual and ultimately unique banking experiences for each and every one of us. In meeting with decision-making executives from the U.S to Europe, the Middle East, India and Singapore, I have compiled a clear list of trends that are dominating technology investment discussions across the globe’s leading banks.


By |February 7th, 2017|blog|0 Comments