Afleveringen
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On Hadooponomics this week we have Jerry Overton, Data Scientist and Distinguished Engineer at Computer Sciences Corporation (CSC), and a teacher, author, and thought leader in using Big Data to influence change in an organization. This week we are action-oriented, looking at the concrete steps Big Data practitioners can take to be more effective at their jobs. We dive into high impact data science, and the difference between Big Data in theory and Big Data in practice – both how to be personally effective, and how to make an impact at enterprise scale. This episode is particularly relevant to data practitioners, but has insights that resonate across the spectrum of Big Data involvement.
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In partnership with Arcadia Data, Blue Hill Research presents Hadooponomics. Host James Haight brings you top thinkers, leaders, and practitioners in the world of Big Data and Hadoop ecosystems to cut through the hype and guide you to the Big Data payoff.
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In partnership with Arcadia Data, Blue Hill Research presents Hadooponomics. Host James Haight brings you top thinkers, leaders, and practitioners in the world of Big Data and Hadoop ecosystems to cut through the hype and guide you to the Big Data payoff.
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This week we brought Ryan Goodman onto the Hadooponomics show to talk about everything from where data scientists should ‘live’ in your organization to the genesis of the age-old “business vs. IT” conflict. Ryan was great to have on the show not only because he is one of the hosts of the top rated analytics podcast “Analytics on Fire” but because he is also the CEO of consulting firm CMaps Analytics.
We tap into Ryan’s experience consulting Fortune 500 companies to explore where the tension between IT and business users stems from. We discuss why the world of data doesn’t fit into the traditional IT mold and what that means for you when you are building your organization.
From there, we transition the episode into what is next in the world of Big Data analytics. We talk through what the data visualization revolution did to Business Intelligence and how such innovations have changed expectations on the largest scales. More interestingly, we speak to what is beyond data visualization and why we believe real-time analysis is the foundation that Big Data analytics initiatives must be built upon for future success.
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Our show this week features Cornelia Davis, the CTO of the Transformation Practice at Pivotal. Bringing Cornelia on the show allowed us to cover a lot of ground ranging from best practices for Big Data investments, all the way to closing the gender gap in high tech.
What I loved about Cornelia’s background is that her job is to work with some of the largest Fortune 500 companies out there and to help them get value from their Big Data investments. She has a lot of experience to share and for the first half of the show we talk through areas where companies fail in their Big Data investments as well as what actions more often lead to successful outcomes.
From there we pivot into a discussion around Cornelia’s other role as an advocate for gender equality in the technology realm. We dive into why the tech industry hasn’t yet achieved gender parity (we are further away than where we were 20 years ago) and examine the underlying causes behind it. To me the most interesting point of the discussion revolves around the idea that the gender gap is more a function of unconscious, yet systematic, biases than anything else.
Anyone interested in how to make the most out of their Big Data investments or how to steer the tech industry towards gender parity has a lot to gain from Cornelia’s perspective.
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Dr. John Johnson headlined our Hadooponomics show this week as we took a wide view of how we use data to influence our decision making process. For his part, Dr. Johnson is PhD economist and founder and CEO of the firm Edgeworth Economics. Additionally Dr. Johnson is also a new author of his recently published book Everydata.
What I especially loved about this episode was our discussion around how to influence and inform others with data. Instead of discussing the usual narrative around how we can better understand data, we took a look from the opposite angle. In this episode we focused on what data savvy influencers (like those of you in our audience) can do to make sure that their work is not misinterpreted or misunderstood. Over the course of the touched on everything from data manipulation tactics to inherent biases within presidential polling, and had some fun discussing absurd spurious correlations as well.
Throughout the episode we dive into Dr. Johnson’s experience as an expert witness for major corporate trials and his own stories of growing an analytic centric organization from its founding to over 80 employees. This episode should prove useful to anyone who is responsible for influencing decisions based on their work with numbers.
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This week on the Hadooponomics podcast we welcomed Bob Hayes to the show. Bob not only runs his own consultancy focusing on the intersection of Big Data and customer experience, but he also serves as Chief Research Officer at Analytics Week as well.
What I enjoyed most about Bob’s perspective is that he holds a PhD in Industrial Organizational Pshychology and brings a lens of applying the human element to the very fact-based world of data. In this episode we start the discussion by breaking down findings from his primary research surveying 490 data scientists. We highlight key outcomes including the types of skills that data scientists typically do (and do not) have as well what it takes to build a data science team with maximum effectiveness.
From there we navigate the conversation into a discussion around STEM education in America and finally we end the interview with talking about how Bob works with his own clients. We explore what Bob advises his clients to do when they start their own analytics initiatives, and also talk about the biggest mistakes that he sees clients making as they try to get a positive return from their Big Data investments.
All in all, this episode shaped up to be an informative piece with a number of actionable tips and insights to bring back to your day job.
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This week’s episode of Hadooponomics features well-known techno-ethicist Emer Coleman.
Emer is the Chair of Ireland’s Open Data Governance Board, a frequent speaker, and a respected advocate for gender equality in the world of technology. Having Emer on the show let us take the podcast into uncharted territories. We navigated the discussion around the uneven socio-economic benefits associated with technology and posed questions as to why we should be designing our future with great care.
We start the interview with a conversation around data privacy and the merits of whether or not we should regulate the algorithms that tech giants use to influence our every day experiences (such as Google search results and the Facebook newsfeed). From there, Emer proposes that we should start thinking about the merits of ethics training for the data scientists and software engineers that are building the digital world. I’ll admit, I was skeptical of this argument, but Emer’s points were enough to force me to reconsider.
We round out the episode talking about gender equality in the technology industry (or more specifically, the lack of gender equality) and discuss first why it is an important issue and then lay out strategies to address it. All in all, this episode offers a number of discussion starters and dives deeper into the social forces that underpin the Big Data revolution.
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We invited Edd Dumbill, the VP of Strategy at Silicon Valley Data Science,to join us for episode 7 of Hadooponomics. It’s a real treat to have Edd as a guest and I thoroughly enjoyed the conversation for a number of reasons.
Not only does Edd work with hundreds of companies on their Big Data strategies, but he is also an incurable futurist who spends his time thinking about how emerging technologies like Artificial Intelligence are going to impact our lives. To top it off, during his time at O’Reilly Media, Edd just so happened to be one of the founders of the Strata Conference, which has since evolved into the preeminent Big Data Show – Strata + Hadoop World.
Over the course of the interview we first discuss how the culture and community of Big Data has evolved (following the arc of the conferences) and then talk through tactical strategies that organizations use for realizing value from their Big Data investments. Finally we round out the show discussing the effects of Artificial Intelligence on Big Data and what it might mean for the future of our work.
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This week’s episode features Kirk Borne, the Principal Data Scientist at Booz Allen Hamilton. I was absolutely thrilled to have Kirk on as a guest. Not only is he a renowned astrophysicist, but also he’s one of the world’s preeminent thought leaders when it comes to Big Data.
Given his varied background working on everything from the Hubble Space Telescope to starting one of America’s first undergraduate programs on data science - we had the chance to span a wide range of topics. Most prominently we talked about the idea of ‘data literacy’ and it’s key role in advancing the opportunity for data to address humanity’s largest challenges. We ventured into how crowdsourcing challenges present a unique opportunity for expanding scientific discovery and even theorized on how the human mind processes information. Eventually we brought the discussion full circle to speak about what Kirk sees as the largest challenges enterprise’s face in adopting Big Data Technologies. In this episode, Kirk sprinkles in lessons from his time at NASA and as a professor in a way that makes understanding the role of data in today’s world accessible to just about any listener.
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For the fifth episode of Hadooponomics I brought Alex Williams and Benjamin Ball from The New Stack onto the show. The New Stack is a research and news outlet that specializes in following how a new breed of technologies is forever changing the enterprise and startup technology landscape. This angle gave us the ability to morph our discussion into more of a roundtable chat where we touched on everything from the parallels between containerization and Big Data, to the economic incentives in technology development.
In this episode, Benjamin gives a particularly insightful bit about the ebb and flow of ‘skills gaps’ associated with any emerging technology. He offers an explanation of the pros and cons of the role that the media (i.e. we) play in over hyping/bringing attention to such issues and what that means for the world of Big Data. The last third of our episode focuses on a discussion around open source foundations and why people should perhaps be more cynical (or at least aware) of their underlying economic motivations and incentives. We talk about why open source foundations are an amazing catalyst for innovation, but also raise the specter of their growing economic and political motivations that dictate their actions.
While we center the conversation around Big Data, this episode has a a broader appeal that should resonate with any technology enthusiastic that cares to follow the trajectory of enterprise technology.
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Shant Hovsepian and Claudia Perlich are back in episode four of Hadooponomics as we tackle the hot-button topic of Data Scientists. Both Shant and Claudia are premier data scientists (For more background check out episode 2), which gives us a great entry point for discussion.
I broke this episode into a two-part discussion in which I ask each about the current and future role of data scientists. For her part, Claudia is quick to point out what is and what is not a data science problem, and how refusing to recognize the difference can lead organizations down the wrong path. Shant took the approach of illuminating the importance of communicating results with simplicity by discussing how the most complex data science problems, such as weather, often manifest themselves in simplistic end results.
As the conversation drifted into the future role of the data scientist we discussed the implications of advanced software abstracting away much of the technical portions of the data scientist job. Claudia warned us about taking such advancements at face value and Shant helped us explore the rise of supporting technologies to amplify human input.
For anyone who is interested in how to build effective data science teams, what the evolution of the job will look like, or how to augment the impact of human effort I would highly suggest this episode.
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In this episode of Hadooponomics James Haight interviews the Chief Security architect of Cloudera, Eddie Garcia. As one of the preeminent leaders in the field, Eddie leads a discussion around the current and future state of Big Data security. This episode explores how organizations should think about their security efforts, what threats they need to prepare for, and how the field will continue to evolve in the near future.
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In the second episode of Hadooponomics James Haight hosts two guests: Claudia Perlich, Chief Scientist for Dstillery and Shant Hovsepian, Co-founder and CTO of Arcadia Data.
In this two-part episode James digs deep into the evolution of data science within the fast paced world of digital advertising. Topics of discussion range from the cat & mouse game between data scientists and hackers, how Big Data fuels real time advertising auctions, and why rural Kansas is the most populated region in the United States. -
In this episode James Haight interviews IoT thought leader, Dana Blouin, and Arcadia Data CEO, Sushil Thomas. The three push the discussion beyond the traditional IoT narrative and highlight how real organizations are adapting to the new world of Big Data. This episode discusses how Hadoop is becoming an essential ingredient to IoT success, and how supporting technologies, such as augmented reality and machine learning, will continue to push the Big Data envelope.
