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Data Science Monetization: Focus on Innovation, Not Effectiveness “I have over 1,200 Data Analysts, so we have it nailed.” When I heard this being uttered by the head of their “analytics” group, I knew the meeting was over. I knew that I could safely close my laptop, put away my notebook, and gracefully thank them for their time. It didn’t matter that others in the room didn’t agree with that assessment.  It didn’t matter that others could see the benefit of a “think differently” collaborative engagement with key business stakeholders in envisioning how to broaden the organization’s thinking with respect to the how to leverage data and analytics to power the business.  Nope, their analytics leader made the statement with such authority and confidence that any further conversation was just going to frustrate both him and me.  He already had all the answers, even to pr... (more)

Is #Blockchain Enabler of Data Monetization? | @CloudExpo #BigData #FinTech

Special thanks for the help on this blog to the coolest, most hip group of industry experts that I have ever met: the Pathfinders. The Pathfinders is an elite forces group of master system engineers inside of Dell EMC who tackle our customers’ most difficult and inspiring challenges. I am honored to be part of that club! Suppose an autonomous vehicle learns of a more efficient route and wants sell this knowledge to other autonomous cars for a fee (using blockchain to handle machine to machine transaction). Suppose the autonomous vehicle could start to monetize itself; to self-fund its own operations and the acquisition of goods and services such as gas, repairs or vehicle upgrades (using blockchain to conduct commerce).  Now suppose the autonomous vehicle could couple real-time analytics of vehicle performance and maintenance with real-time bidding for maintenance... (more)

Whose Data Is It? | @CloudExpo #IoT #AI #ML #DL #M2M #BigData #Analytics

Many times, sports have been at the leading edge of data analytics.  The book “Moneyball” was one of the first popular books to bring the basic concepts behind data analytics and data science to the general audience.  Fantasy leagues, sabermetrics and even games like “Strat-O-Matic” baseball and basketball provided an introduction into basic statistical concepts. And it now seems that sports, in this case the National Basketball Association (NBA), are breaking new ground with another data analytics topic: who owns the data?  The National Basketball Players Association recently banned NBA teams from using a player’s wearable data in contract negotiations or other transactions (see “NBA Bans Teams From Using Wearable Data In Contract Negotiations”). Maybe after the bitter fights professional and college athletes had about their “likeness” being used for advertising... (more)

Data Is a New Currency | @CloudExpo #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)

The Future Is Intelligent Apps | @ThingsExpo #IoT #M2M #BigData #Analytics

I have seen the future! Of course, I seem to say that every other month (maybe that’s because the future keeps changing?), but this is a good one. The future is a collision between big data (and data science) and application development that will yield a world of “intelligent apps.” These “intelligent apps” combine customer, product and operational insights (uncovered with predictive and prescriptive analytics) with modern application development tools and user-centric design to create a more compelling, more prescriptive user experience. These intelligent apps not only know how to support or enable key user decisions, but they continually learn from the user interactions to become even more relevant and valuable to those users. Several developments and posts by industry leaders over the past few weeks have started to add some substance to this intelligent apps tre... (more)

Organizational Analytics Adoption | @BigDataExpo #BigData #DataLake #Analytics

Organizational Analytics Adoption: A Generation Away? A recent article titled “We Are Likely 3-5 Years Out From Advanced Analytics Being Critical To The Viability Of A Company” (and I thought my titles were too long) interviewed Walter Storm, the Chief Data Scientist at Lockheed Martin. The article offers some great perspectives such as: “There’s also a culture shift required – moving from experience and knee-jerk reactions to immersion and exploration of rich insights and situational awareness.” However, Mr. Storm believes that we are only 3 to 5 years away from advanced analytics being critical to the viability of a company: “We are at a point where data-driven decisions may still offer companies a competitive advantage, however we are likely 3-5 years out from advanced analytics being table stakes and critical to the viability of a company to even remain in busin... (more)

Difference Between #BigData and Internet of Things | @ThingsExpo #IoT #M2M

A recent argument with folks whose intelligence I hold in high regard (like Tom, Brandon, Wei, Anil, etc.) got me thinking about the following question: What does it mean, as a vendor, to say that you support the Internet of Things (IoT) from an analytics perspective? I think the heart of that question really boils down to this: What are the differences between big data (which is analyzing large amounts of mostly human-generated data to support longer-duration use cases such as predictive maintenance, capacity planning, customer 360 and revenue protection) and IoT (which is aggregating and compressing massive amounts of low latency / low duration / high volume machine-generated data coming from a wide variety of sensors to support real-time use cases such as operational optimization, real-time ad bidding, fraud detection, and security breach detection)? I don’t beli... (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)

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)

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)

Big Data Technology - the Rebel without a Cause | @BigDataExpo #BigData #DataLake

Big Data Technology - the Rebel without a Cause Gartner cited the #1 challenge in Big Data as “Determining how to get value from Big Data.” Did I read that right? And by no a small margin! How to get value from Big Data? Shouldn’t it be shocking that such a fundamental question persists while businesses are spending billions on data analytics capabilities and infrastructure? If ever there was a solution looking for a problem (or a rebel without a cause), this is it.  How can the most elusive part of Big Data be “how to get value?” Shouldn’t someone have thought of this “before?” We all talk about the opportunities to enhance customer experiences, uncover new monetization opportunities, and increase operational efficiencies. But… where’s the beef??? Well, here is my take on it. The graphic below is over one year old – I know that. But the majority of organizations ... (more)