Posts tagged ‘exploratory analysis’
I’ve been meaning to blog about Strata West for the last week or so but felt the need to take a step back and look at the conference objectively. Of course, we’ve also been very busy at PatternBuilders working on our latest release (where correlation is the king and financial services is the queen or vice versa), engaging with potential partners and customers, and all the other activities that make up a startup’s life. In other words, during and after the conference we’ve barely been able to catch our collective breath (as well as get some much needed rest)!
So before I talk about the conference as a whole as well as some of the sessions and folks that caught my eye and of course, our book signing event (yes, Terence and I signed many books for conference attendees), I wanted to give a final shout out to our stellar Big Data and SCM panelists: Lora Cecere, Pervinder Johar, and Marilyn Craig. Thank you all for participating and for taking on this very broad topic! Much ground was covered, including the need for more rigorous cold chain management to ensure the efficacy of drugs, the amount of food that is spoiled and thrown away (one out of every three fruits and vegetables and two out of every five chickens) due to poor logistics management, and how big data can be used to transform the auto repair industry. What I loved about this panel (and yes, I am admittedly biased) was that it focused on real world problems that companies, industries, and societies are dealing with today. By the way, our panel was part of Strata Jumpstart—billed as the missing MBA for Big Data and it certainly lived up to its billing! (more…)
Greetings all! While we’ve been super busy at PatternBuilders working on a destination application that we are all very excited about, doing some development work, talking with potential partners and prospects, AND not to mention the fact (but I will) that Terence and I are getting close to the finish line on our book, I came across this interesting article on Gartner’s hype cycle and the recent addition of big data to it.
Now, I am pretty sure that you all are familiar with Gartner’s magic quadrant methodology that essentially evaluates all the particular technology players in a specific industry across four quadrants: challengers, leaders, niche players, and visionaries. For those companies looking at vendors for a specific solution, the magic quadrant can help them understand how they stack up against each other. For the vendors, it’s an opportunity to take an objective look at the industry as a whole and understand what they do well and where they could be better. (more…)
As I said in my recent post on the U.S. health care system, the U.S. cannot continue at its current spending rate. Certainly, the McKinsey Study (and many other publications) makes this very clear. Now, you and I may have very different opinions on how this can be fixed depending on our political leanings, etc., but ignoring this problem is not going to make it “go away.” Lucky for us, McKinsey takes a look at how big data and analytics can alleviate health care costs in some very promising areas. Whether you share my views on health care reform or not, it’s clear that we need to figure out how to align health care policy and regulations with economic incentives designed to move the industry towards a more collaborative, data sharing approach. To me, this is the “real” health care debate!
If you are a card carrying member of the big data community but don’t know much about the state of health care data, you may be surprised at just how antiquated data collection and usage is. If you have been steeped in the health care industry (and not just in the health care reform debate), this will be old news: health care data is not systematically collected, stored, and used. It is the only trillion dollar-plus industry in the U.S. without a modern information technology infrastructure. Look at is this way: while medical technology has advanced, much of the infrastructure that supports it is paper-based. For example, most of our medical records are stored in files (and I mean physical files) at various hospitals and doctors’ offices. Whenever you see a new doctor or go to a new clinic or hospital, chances are you fill out the same forms (again and again) documenting your medical history, risk factors, allergies, etc. (more…)
In case you haven’t heard, data is “a $100 billion marketplace.” There are data markets, like Gnip, Infochimps, and Microsoft’s Azure Marketplace that offer some datasets for free and others for a price. And those prices may be dropping considerably due to data reseller, Mediasift, which is providing very low cost access to social data. This means that companies outside of the Fortune 500 can now afford to purchase small and deep slices of social data for “pennies on the dollar” when compared to other data markets. There are also public datasets offered by data.gov and others. And all of these datasets are constantly growing, fed by the data generated by social networks, e-commerce, mobile location, and yes, advertising technology. Think about this for a moment:
“… 600 billion electronic transactions are created in the U.S. every day, and many of those transactions come from geo-locational data generated by cell phones, which through cellular towers, triangulate a person’s exact location at any time. Wireless providers have that data in real time.”