Big Data Pains & Gains From A Real Life CIO

What does it take to make CIO Magazine’s Top 100 List? Big Data victory is one of them.
Michael Cucchi, Sr Director of Product Maketing at Pivotal, had the privilege to speak with one of the winners – EMC CIO Vic Bhagat. Discussing the pains and gains of EMC’s Big Data initiative, I have put together a summary of this interview below.  EMC IT’s approach to Big Data is exactly what the EVP Federation enables organizations to do – first collect any and all data in a Data Lake, deploy the right analytic tool that your people know how to use to analyze the data, and finally learn agile development so you can take those insights and build applications rapidly.

1. Why is Big Data important to your business?

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Can Big Data Shape A Better Future? Quid is Paving the Way

World hunger, political conflict, business competition and other complex problems cannot be solved with mathematical algorithms measuring probabilities alone. However, by combining together human intelligence with the best artificial intelligence, the company Quid has built software that experts are calling the worlds first augmented intelligence platform. Using superior speed and storage capacity of computation, the process by which human beings typically acquire the deep pattern recognition of expertise is accelerated. The software does more than run simple prediction algorithms, it allows users to interact with data in an immersive, visual environment to better understand the world at a high resolution so that they can ultimately shape it and change it.

Founded in 2010, Quid is addressing a new class of problems to help organizations make strategic decisions around business innovation, public relations, foreign policy, human welfare, and more. Through advanced visualizations that interpret massive amounts of diverse internal and publicly accessible external data sets, Quid tells a unique and compelling story about the complexity of our world – trends, comparisons, multi-dimensional relationships, etc. – to change the direction of decision making.

For Quid, it’s not about man battling it out with machines, but rather, man working with machines when entering a new level of complex problem solving. For example, military intelligence may one day be able to change the direction of future conflicts by working with Quid software to analyze millions of data points from war logs and reports, news articles, and social media about the most recent casualties of war. The intelligence teams plugged into Quid would be able to see the war unfold as it happens across multiple data dimensions and uncover the mathematical patterns hidden in the data that are shaping the direction of the conflict.

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I spoke with Quid Co-founder and CTO Sean Gourley to explain how Quid is helping organizations leverage Big Data and augmented intelligence to tackle the Bigger Problems they are facing in a fast moving world.

1.  Quid applies Data Intelligence to Big Data – a very different concept than applying Data Science to Big Data. Please explain.

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RSA and Pivotal: Laying the Foundation for a Wider Big Data Strategy

Building from years of security expertise, RSA was able to exploit Big Data to better detect, investigate, and understand threats with its RSA Security Analytics platform launched last year. Similarly, Pivotal leveraged its world-class Data Science team in conjunction with its Big Data platform to deliver Pivotal Network Intelligence for enhanced threat detection using statistical and machine learning techniques on Big Data. Utilizing both RSA Security Analytics and Pivotal Network Intelligence together, customers were able to identify and isolate potential threats faster than competing solutions for better risk mitigation.

As a natural next step, RSA and Pivotal last week announced the availability of the Big Data for Security Analytics reference architecture, solidifying a partnership that brings together the leaders in Security Analytics and Big Data/Data science. RSA and Pivotal will not only enhance the overall Security Analytics strategy, but also provide a foundation for a broader ‘IT Data Lake’ strategy to help organizations gain better ROI from these IT investments.

RSA’s reference architecture utilizes Pivotal HD, enabling security teams to gain access to a scalable platform with rich analytic capabilities from Pivotal tools and the Hadoop ecosystem to experiment and gain further visibility around enterprise security and threat detection. Moreover, the combined Pivotal and RSA platform allows organizations to leverage the collected data for non-security use cases such as capacity planning, mean-time-to-repair analysis, downtime impact analysis, shadow IT detection, and more.

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Distributed architecture allows for enterprise scalability and deployment

I spoke with Jonathan Kingsepp, Director of Federation EVP Solutions from Pivotal to discuss how the RSA-Pivotal partnership allows customers to gain much wider benefits across their organization.

1.  What are the technology components of this is this new RSA-Pivotal Reference architecture?

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Revolution Analytics Boosts the Adoption of R in the Enterprise

The path to competitive advantage is being able to make predictions from Big Data. Therefore, the more you can build predictive analytics into your business processes, the more successful your organization will become. There is no doubt that open-source R is the programming language of choice for predictive analytics, and thanks to Revolution Analytics, R has the enterprise capabilities needed to drive adoption across the organization and for every employee to make data-driven decisions.

Revolution Analytics is to R what the vendor RedHat is to the Linux operating system—a company devoted to enhancing and supporting open-source software for enterprise deployments. For example, Revolution Analytics recently released R Enterprise 7 to meet the performance demands of Big Data whereby R now runs natively within Hadoop and data warehouses. I spoke with David Smith, VP of Marketing at Revolution Analytics to explain how Revolution Analytics has accelerated the adoption of R in the enterprise.

1.  What benefits do Revolution Analytics provide to organizations over just using open-source R?

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