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.

Physics_explore

photo

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.

Continue reading

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.

RSA-Pivotal-Reference-Architecture

 

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?

Continue reading

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?

Continue reading

Alpine Data Labs – Making Predictive Analytics Pervasive and Persuasive

Big Data has exposed the need for deeper data insights through predictive analytic techniques such as data mining, machine learning, and modeling. The interesting thing to note is that predictive analytics has been around for a long time, used by a select few, in select organizations. Its value has always been recognized and applauded, but its true potential never fully realized due to lack of widespread adoption, as well as issues around data accessibility, performance, statistical expertise, business sponsorship, cost, and more. In fact, nearly 90 percent of organizations that do employ predictive analytic software agree that it has given them a competitive advantage, according to a new survey.

The advent of Big Data has driven the uptake of predictive analytics due to the curiosity of very capable Data Scientists, along with new tools and technologies from companies such as Alpine Data Labs.  Alpine Data Labs provides next generation predictive analytics to address legacy issues and meet the new demands of Big Data. But more importantly, Alpine Data Labs is mainstream-oriented whereby business users, not just statisticians and Data Scientists, are compelled to mine data.

collaborate-alpine-data

Backed by $16M in Series B funding, Alpine Data Labs is getting some serious momentum in the Big Data analytics startup space, offering zero coding for creating and deploying complex predictive models on Hadoop. I spoke with Alpine Data Labs CEO Joe Otto to talk about their game changing approach to predictive analytics for Big Data.

1.  Lets first talk about leading predictive analytics incumbents such as SAS, IBM SPSS, and other analytics vendors who got their start years ago with desktop and server software designed for data mining and advanced analytics. How has Alpine Data Labs overcome the issues around these incumbent technologies and address the new needs of Big Data?

Continue reading