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Business Model Transformation and What it Means to the Data Industry I recently read an MIT Sloan Management Review article by Clayton Christensen’s recent book titled “The Hard Truth About Business Model Innovations.” While the article is full of great observations about business model transformation, the most important motivation for business model transformation is found at the end: “..our understanding of the business model journey allows us to see that, over the long term, the greatest innovation risk a company can take is to decide not to create new businesses that decouple the company’s future from that of its current business units.” We use the Big Data Business Model Maturity Index as a vehicle for engaging with our clients about how they can leverage data and analytics to transform their business models (see Figure 1). Figure 1: Big Data Business Model Ma... (more)

Aggregated Data Dilemma | @BigDataExpo #BigData #Analytics #DataScience

Okay, I am weird (tell me something that I don’t know, say most of my friends).  For Christmas I wanted a Nike Apple Watch to go with my existing FitBit and Garmin fitness trackers (I look sort of like a cyborg in the photo below…which is always cool). While I was intrigued by the ability to do all sorts of cool things on the Apple Watch (like take a phone call and talk into my wrist watch like Dick Tracy), the thing that most intrigued me was the ability to buy third-party apps that could yield detailed exercise and health data.  I was hoping that this detailed exercise and health data could help me understand what effect particular behaviors or activities (or lack of particular behaviors and activities) were having on my overall health. Why is this important to me?  You can thank articles like “Unexpected Heart Attack Triggers” for my health and exercise anxiety.... (more)

Tips for Data Scientists | @CloudExpo #BigData #IoT #ML #AI #DataScience

I spend a lot of time helping organizations to “think like a data scientist.” My book “Big Data MBA: Driving Business Strategies with Data Science” has several chapters devoted to helping business leaders to embrace the power of data scientist thinking. My Big Data MBA class at the University of San Francisco School of Management focuses on teaching tomorrow’s business executives the power of analytics and data science to optimize key business processes, uncover new monetization opportunities and create a more compelling, engaging customer and channel engagement. However in working with our data science teams, I have come to realize that we also need to address the other side of the data science equation; that we need to teach the data scientists in order for them to think like business executives. If the data science team cannot present the analytic results in a w... (more)

Is Data Science Really Science? | @BigDataExpo #BigData #Analytics #DataScience

My son Max is home from college and that always leads to some interesting conversations.  Max is in graduate school at Iowa State University where he is studying kinesiology and strength training.  As part of his research project, he is applying physics to athletic training in order to understand how certain types of exercises can lead to improvements in athletic speed, strength, agility, and recovery. Figure 1:  The Laws of Kinesiology Max was showing me one drill designed to increase the speed and thrust associated with jumping (Max added 5 inches to his vertical leap over the past 6 weeks, and can now dunk over the old man).  When I was asking him about the science behind the drill, he went into great details about the interaction between the sciences of physics, biomechanics and human anatomy. Max could explain to me how the laws of physics (the study of the pro... (more)

Don’t Call #BigData Dead | @CloudExpo #IoT #AI #ML #MachineLearning

You can call me biased, or out of touch, but over the past two years, I’ve been reading articles and blogs about how Big Data is going away, dying, or already dead. So what changed? Is Big Data falling into Gartner’s dreaded trough of disillusionment? Did someone discover that predictive analytics could have a butterfly effect and change the course of history and hence, we should abandon these voodoo analytics practices? Did we figure out that we actually don’t have enough data to call it “Big” data? Did we already finish analyzing all the data and we’re all done? Or… are the people calling it dead really just a bunch of marketers who are looking move on to the next new thought leadership topic, so they write one final blog to make one final impression just before they abandon the topic? Bingo. I’m looking at you… industry pundits, thought leaders, and analysts. T... (more)

Citizen Data Scientist, Jumbo Shrimp | @CloudExpo @Schmarzo #BigData

Citizen Data Scientist, Jumbo Shrimp, and Other Descriptions That Make No Sense Okay, let me get this out there: I find the term “Citizen Data Scientist” confusing. Gartner defines a “citizen data scientist as “a person who creates or generates models that leverage predictive or prescriptive analytics but whose primary job function is outside of the field of statistics and analytics.” While we teach business users to “think like a data scientist” in their ability to identify those variables and metrics that might be better predictors of performance, I do not expect that the business stakeholders are going to be able to create and generate analytic models. I do not believe, nor do I expect, that the business stakeholders are going to be proficient enough with tools like SAS or R or Python or Mahout or MADlib to 1) create or generate the models, and then 2) be profi... (more)

Data Is a New Currency | @ClousExpo #BigData #BI #AI #ML #Analytics

This guest blog is provided by Brandon Kaier (@bkaier). Brandon has more than two decades of experience in the IT industry as a transformational leader.  Kaier is responsible for setting the strategy, defining the service line offerings and capabilities as the Field CTO for the North America. These responsibilities include bringing net new products and solutions to market with a focus on the deployment of solutions enabling analytics and agile application development. Most recently Kaier held positions on Technical Architecture team and Strategy and Direction team for Dell EMC’s Data Lake solutions. Kaier also brings experienced based, Dell EMC IT best practices, Big Data and Transformational strategies to Dell EMC customers. “Data is the new Oil.” Has anyone not heard this phrase yet? This analogy was first presented by Clive Humby at the Association of National A... (more)

Better Predictors | @CloudExpo @Schmarzo #BigData #IoT #AI #ML #Analytics

Data Science: Identifying Variables That Might Be Better Predictors I love the simplicity of the data science concepts as taught by the book “Moneyball.” Everyone wants to jump right into the real meaty, highly technical data science books. But I recommend to my students to start with the book “Moneyball.” The book does a great job of making the power of data science come to life (and the movie doesn’t count, as my wife saw it and “Brad Pitt is so cute!” was her only takeaway…ugh). One of my favorite lessons out of the book is the definition of data science: Data Science is about identifying those variables and metrics that might be better predictors of performance This straightforward definition sets the stage for defining the roles and responsibilities of the business stakeholders and the data science team: Business stakeholders are responsible for identifying (brai... (more)

Election #DataScience and the Death of Truth | @CloudExpo #BigData #Analytics

The U.S. Presidential election is finally over. The protests are winding down, they’ve stopped burning cars in Oakland (for now), and the talks of California succession are waning. But I am struggling to return to “normal” because in this election, truth got hammered. Many candidates treated opinions as “truth” and a large portion of the American public grabbed a hold of these “truths” as gospel. It may have been a good time to be in the “fact checking” business, but I’m not sure how effective even the fact checkers could be given the spontaneous nature of “opinions as facts” being thrown around, not to mention the people who create fake news intentionally. So let’s play a game! Let’s call this game “Separate the Truth from the Myths.” Let’s see how you do. Bat Boy Sighted in NYC Subway (probably too expensive to get a condo in Manhattan) Obama Appoints Martian Amb... (more)

Big Data Model Maturity Discussion – What Are You Measuring? | @BigDataExpo #BI #BigData #Analytics

Big Data Model Maturity Discussion - What Are You Measuring? “Maturity models” can be very useful. Every analyst firm and most vendors have created some sort of maturity model. Not only can a maturity model benchmark where you are with respect to your cohorts, but good maturity models also provide a roadmap to help organizations advance along the maturity model. But different maturity models measure different things, and what the maturity model measures is critically important because you are what you measure. For example, a friend recently sent me the below cartoon about the “5 Stages of Data-Driven Marketing” (see Figure 1). Figure 1: Five Stages of Data-Driven Marketing Figure 1 measures how effective an organization is at leveraging data to drive an organization’s marketing culture. In the case of Figure 1, it conveys the organizational and cultural challenges ... (more)

In 2014 Big Data Investments Will Account for Nearly $30 Billion - Eventually Accounting for $76 Billion by 2020 End

DALLAS, Aug. 21, 2014 /PRNewswire-iReach/ -- Amid the proliferation of real time data from sources such as mobile devices, web, social media, sensors, log files and transactional applications, Big Data has found a host of vertical market applications, ranging from fraud detection to R&D. Photo - http://photos.prnewswire.com/prnh/20140821/138541 "Big Data Market: 2014 – 2020 – Opportunities, Challenges, Strategies, Industry Verticals & Forecasts" Key Findings: In 2014 Big Data vendors will pocket nearly $30 Billion from hardware, software and professional services revenues Big Data investments are further expected to grow at a CAGR of nearly 17% over the next 6 years, eventually accounting for $76 Billion by the end of 2020 The market is ripe for acquisitions of pure-play Big Data startups, as competition heats up between IT incumbents Nearly every large scale IT ven... (more)