Collaboration in the era of the Internet of Everything (IoE) is not just about people connecting with people. Yet when you ask most people how they picture “collaboration,” they probably think of person-to-person collaboration first: perhaps a web-based conference call where people are sharing content such as a Word document or a PowerPoint presentation. Or they might envision an immersive teleconference experience with people from different continents, across multiple time zones. Or they might think of a more traditional approach—a group of people having a lively discussion around a conference table, with someone taking notes on a whiteboard.
What if you had a “virtual doctor” who was available at any time—24x7—to give you a quick checkup, dispense friendly health advice, and even alert you to possible health problems before they become serious? What if your parents or grandparents got a gentle daily reminder to take their medication, so they would never have to worry about missing a dose? What if you could walk into any emergency room in the country and receive exactly the care you need because the hospital has instant access to all your medical records? While much of this may seem futuristic, it will become reality in a future not that far away.
Big Data and analytics are transforming healthcare as we know it. Let me share a few examples:
1. Patient care
Many healthcare providers are stretched to capacity, and can’t always follow up with patients to see how they’re doing and make sure they are following medical advice. Today, we are beginning to see pills with tiny ingestible sensors that send a message to your doctor or to a loved one to confirm that you have taken the pill—giving peace of mind to worried children of elderly parents, or anyone who needs to take medication at a specified time. In the future, these sensors will likely also be able to report whether the medicine results in the right impact, and to suggest a change of dose or even a different medication, if that is appropriate.
A high-risk pregnancy is a constant source of worry for many women. In the near future, small electronic “tattoos” will provide nonstop fetal monitoring through a sticker worn right on the skin. Wireless communications capabilities will send vital signs directly to the cloud, where Big Data and analytics capabilities can evaluate the information and send appropriate alerts to the mother and her doctor.
“Software is Eating the World” is a quote attributed to Marc Andreessen and somewhat further explored by his business partner Ben Horowitz. Mark Andreessen gives compelling reasons to validate this quote. To some extend I have to agree with some of his reasons (but I am also a little bit biased as a software engineer). On the other hand, when I read this (and this is partly based on working in different domains on software), I wonder if software is that disruptive? If you look “under the hood” of software applications, you find that a lot of software is based on fundamental software principles that are already 20-30 years old, yet Read More »
“Software is Eating the World” is a quote attributed to Marc Andreessen and somewhat further explored by his business partner Ben Horowitz. Mark Andreessen gives compelling reasons to validate this quote. To some extend I have to agree with some of his reasons (but I am also a little bit biased as a software engineer). On the other hand, when I read this (and this is partly based on working in different domains on software), I wonder if software is that disruptive. If you look “under the hood” of software applications, you find that a lot of software is based on fundamental software principles that are already 20-30 years old, yet they are still frequently used (and for good reasons). That does not mean there are no new advances in software, however old and proven technologies still play an important role (like we say in mathematics, it does not become old, it becomes classic).
So maybe the reason that “Software is Eating the World” is due to the advances in hardware? Would you run modern enterprise applications in the Cloud 20 years ago? One of the challenges could certainly be the bandwidth. Was the IPhone a victory for software or hardware? A lot of the IPhone GUI was not that revolutionary IMO but the combination of hardware and software made for a potent technology disruption.
I am attending South Korea’s Big Data Forum in Seoul, and one question here is, “How big is Big Data?” My friend and colleague Dave Evans has pointed out that by the end of this year, more data will be created every 10 minutes than in the entire history of the world up to 2008. Now, that’s big!
Much of this data is being created by billions of sensors that are embedded in everything from traffic lights and running shoes to medical devices and industrial machinery—the backbone of the Internet of Things (IoT). But the real value of all this data can be realized only when we look at it in the context of the Internet of Everything (IoE). While IoT enables automation through machine-to-machine (M2M) communication, IoE adds the elements of “people” and “process” to the “data” and “things” that make up IoT. Analytics is what brings intelligence to these connections, creating endless possibilities.
To understand why, let’s step back and take a look at the classic approach to Big Data and analytics. Traditionally, organizations have tended to store all the data they collect from various sources in centralized data centers. With this model, if a retailer wants to know something about the buying patterns of a certain store’s customers, it can create an analysis of loyalty card purchases based on data in the data warehouse. Collecting, cleansing, overlaying, and manipulating this data takes time. By the time the analysis is run, the customer has already left the store.
Big Data today is characterized by volume, variety, and velocity. This phenomenon is putting a tremendous strain on the centralized model, as it is no longer feasible to duplicate and store all that data in a centralized data warehouse. Decisions and actions need to take place at the edge, where and when the data is created; that is where the data and analysis need to be as well. That’s what Cisco calls “Data in Motion.” With sensors gaining more processing power and becoming more context-aware, it is now possible to bring intelligence and analytic algorithms close to the source of the data, at the edge of the network. Data in Motion stays where it is created, and presents insights in real time, prompting better, faster decisions.