Related Topics: @DXWorldExpo, Java IoT, Linux Containers, Containers Expo Blog, @CloudExpo, SDN Journal

@DXWorldExpo: Article

Big Data Needs a Thought Collective

Big Data should follow the lead of the scientific method to put greater emphasis on sharing and reusing data

Sharing data is a cornerstone of the scientific method because it makes it possible to replicate work. That foundation is mostly absent from data science, which makes obtaining and reusing knowledge more difficult than it should be.

Job postings for data scientists increased 15,000 percent between 2011 and 2012, and Gartner predicted that 63% of organizations would invest in Big Data this year. The communications, consumer, education, financial, healthcare, government, manufacturing, and retail sectors are all adopting business practices that are using data science to inform their activities and improve operations.

There are a number of companies creating solutions to visualize and uncover insights from large volumes of data with robust platforms in operation worldwide. Vast volumes of data from applications logs to the network and business activities are well served by today's analytics technologies - computation isn't the issue. The ability to model data into experiments that act on data with data sources and conclusions is what's missing, and it's an emerging problem for businesses.

Gartner has observed that those same organizations are now "struggling" with deriving value from and managing Big Data (depending on organizational maturity). That could be due to what famed microbiologist Ludwik Fleck deemed an "empty mind" as he explored the sociology of science during the 1930s. What is that exactly? Fleck postulated that a mind must be filled with initial knowledge before it can perceive or think. This logic applies to organizations too.

Fleck's theory was that participating in a "thought collective" of institutional knowledge would fill minds. His works concluded that cognition is a collaborative activity because a body of knowledge is acquired from a group. It could be argued that making it possible to reuse data experiments would have the same effect. Organizations that can't find value in data have an empty mind.

Big Data should follow the lead of the scientific method (which was influenced by Fleck's ideas) to put greater emphasis on sharing and reusing data. Why is that important for businesses? Scientific data is easy to share among different organizations. Having the ability to do the same with data science could solve what's emerging as a major pain point. Employees change roles and organizations, but what happens to the knowledge, experiments, and patterns?

Whether the academic model would also function in the enterprise is a fascinating question for data scientists, operations professionals and industries. The next great "open source" horizon could be the exchange of knowledge.

It would be interesting to see companies take on the challenge of building systems that organize and share experiments more liberally to put an end to the empty brain problem. After all, data science is still science. Why should it be treated differently?

More Stories By Haim Koshchitzky

Haim Koshchitzky is the Founder and CEO of XpoLog and has over 20 years of experience in complex technology development and software architecture. Prior to XpoLog, he spent several years as the tech lead for Mercury Interactive (acquired by HP) and other startups. He has a passion for data analytics and technology, and is also an avid marathon runner and Judo black belt.

Comments (1)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.

Latest Stories
Cloud-enabled transformation has evolved from cost saving measure to business innovation strategy -- one that combines the cloud with cognitive capabilities to drive market disruption. Learn how you can achieve the insight and agility you need to gain a competitive advantage. Industry-acclaimed CTO and cloud expert, Shankar Kalyana presents. Only the most exceptional IBMers are appointed with the rare distinction of IBM Fellow, the highest technical honor in the company. Shankar has also receive...
DXWorldEXPO LLC announced today that Kevin Jackson joined the faculty of CloudEXPO's "10-Year Anniversary Event" which will take place on November 11-13, 2018 in New York City. Kevin L. Jackson is a globally recognized cloud computing expert and Founder/Author of the award winning "Cloud Musings" blog. Mr. Jackson has also been recognized as a "Top 100 Cybersecurity Influencer and Brand" by Onalytica (2015), a Huffington Post "Top 100 Cloud Computing Experts on Twitter" (2013) and a "Top 50 C...
There is a huge demand for responsive, real-time mobile and web experiences, but current architectural patterns do not easily accommodate applications that respond to events in real time. Common solutions using message queues or HTTP long-polling quickly lead to resiliency, scalability and development velocity challenges. In his session at 21st Cloud Expo, Ryland Degnan, a Senior Software Engineer on the Netflix Edge Platform team, will discuss how by leveraging a reactive stream-based protocol,...
Enterprises have taken advantage of IoT to achieve important revenue and cost advantages. What is less apparent is how incumbent enterprises operating at scale have, following success with IoT, built analytic, operations management and software development capabilities - ranging from autonomous vehicles to manageable robotics installations. They have embraced these capabilities as if they were Silicon Valley startups.
Daniel Jones is CTO of EngineerBetter, helping enterprises deliver value faster. Previously he was an IT consultant, indie video games developer, head of web development in the finance sector, and an award-winning martial artist. Continuous Delivery makes it possible to exploit findings of cognitive psychology and neuroscience to increase the productivity and happiness of our teams.
Poor data quality and analytics drive down business value. In fact, Gartner estimated that the average financial impact of poor data quality on organizations is $9.7 million per year. But bad data is much more than a cost center. By eroding trust in information, analytics and the business decisions based on these, it is a serious impediment to digital transformation.
The standardization of container runtimes and images has sparked the creation of an almost overwhelming number of new open source projects that build on and otherwise work with these specifications. Of course, there's Kubernetes, which orchestrates and manages collections of containers. It was one of the first and best-known examples of projects that make containers truly useful for production use. However, more recently, the container ecosystem has truly exploded. A service mesh like Istio addr...
As DevOps methodologies expand their reach across the enterprise, organizations face the daunting challenge of adapting related cloud strategies to ensure optimal alignment, from managing complexity to ensuring proper governance. How can culture, automation, legacy apps and even budget be reexamined to enable this ongoing shift within the modern software factory? In her Day 2 Keynote at @DevOpsSummit at 21st Cloud Expo, Aruna Ravichandran, VP, DevOps Solutions Marketing, CA Technologies, was jo...
Predicting the future has never been more challenging - not because of the lack of data but because of the flood of ungoverned and risk laden information. Microsoft states that 2.5 exabytes of data are created every day. Expectations and reliance on data are being pushed to the limits, as demands around hybrid options continue to grow.
Business professionals no longer wonder if they'll migrate to the cloud; it's now a matter of when. The cloud environment has proved to be a major force in transitioning to an agile business model that enables quick decisions and fast implementation that solidify customer relationships. And when the cloud is combined with the power of cognitive computing, it drives innovation and transformation that achieves astounding competitive advantage.
As IoT continues to increase momentum, so does the associated risk. Secure Device Lifecycle Management (DLM) is ranked as one of the most important technology areas of IoT. Driving this trend is the realization that secure support for IoT devices provides companies the ability to deliver high-quality, reliable, secure offerings faster, create new revenue streams, and reduce support costs, all while building a competitive advantage in their markets. In this session, we will use customer use cases...
Digital Transformation: Preparing Cloud & IoT Security for the Age of Artificial Intelligence. As automation and artificial intelligence (AI) power solution development and delivery, many businesses need to build backend cloud capabilities. Well-poised organizations, marketing smart devices with AI and BlockChain capabilities prepare to refine compliance and regulatory capabilities in 2018. Volumes of health, financial, technical and privacy data, along with tightening compliance requirements by...
The IoT Will Grow: In what might be the most obvious prediction of the decade, the IoT will continue to expand next year, with more and more devices coming online every single day. What isn’t so obvious about this prediction: where that growth will occur. The retail, healthcare, and industrial/supply chain industries will likely see the greatest growth. Forrester Research has predicted the IoT will become “the backbone” of customer value as it continues to grow. It is no surprise that retail is ...
Evan Kirstel is an internationally recognized thought leader and social media influencer in IoT (#1 in 2017), Cloud, Data Security (2016), Health Tech (#9 in 2017), Digital Health (#6 in 2016), B2B Marketing (#5 in 2015), AI, Smart Home, Digital (2017), IIoT (#1 in 2017) and Telecom/Wireless/5G. His connections are a "Who's Who" in these technologies, He is in the top 10 most mentioned/re-tweeted by CMOs and CIOs (2016) and have been recently named 5th most influential B2B marketeer in the US. H...
Andrew Keys is Co-Founder of ConsenSys Enterprise. He comes to ConsenSys Enterprise with capital markets, technology and entrepreneurial experience. Previously, he worked for UBS investment bank in equities analysis. Later, he was responsible for the creation and distribution of life settlement products to hedge funds and investment banks. After, he co-founded a revenue cycle management company where he learned about Bitcoin and eventually Ethereal. Andrew's role at ConsenSys Enterprise is a mul...