Welcome!

Apache Authors: Mark R. Hinkle, Carmen Gonzalez, Roger Strukhoff, Liz McMillan, Elizabeth White

Related Topics: Cloud Expo, Java, SOA & WOA, Open Source, Web 2.0, Apache

Cloud Expo: Article

The Cure for the Common Cloud-Based Big Data Initiative

Understanding how to work with Big Data

There is no doubt that Big Data holds infinite promise for a range of industries. Better visibility into data across various sources enables everything from insight into saving electricity to agricultural yield to placement of ads on Google. But when it comes to deriving value from data, no industry has been doing it as long or with as much rigor as clinical researchers.

Unlike other markets that are delving into Big Data for the first time and don't know where to begin, drug and device developers have spent years refining complex processes for asking very specific questions with clear purposes and goals. Whether using data for designing an effective and safe treatment for cholesterol, or collecting and mining data to understand proper dosage of cancer drugs, life sciences has had to dot every "i" and cross every "t" in order to keep people safe and for new therapies to pass muster with the FDA. Other industries are now marveling at a new ability to uncover information about efficiencies and cost savings, but - with less than rigorous processes in place - they are often shooting in the dark or only scratching the surface of what Big Data offers.

Drug developers today are standing on the shoulders of those who created, tested and secured FDA approval for treatments involving millions of data points (for one drug alone!) without the luxury of the cloud or sophisticated analytics systems. These systems have the potential to make the best data-driven industry even better. This article will outline key lessons and real-world examples of what other industries can and should learn from life sciences when it comes to understanding how to work with Big Data.

What Questions to Ask, What Data to Collect
In order to gain valuable insights from Big Data, there are two absolute requirements that must be met - understanding both what questions to ask and what data to collect. These two components are symbiotic, and understanding both fully is difficult, requiring both domain expertise and practical experience.

In order to know what data to collect, you first must know the types of questions that you're going to want to ask - often an enigma. With the appropriate planning and experience-based guesses, you can often make educated assumptions. The trick to collecting data is that you need to collect enough to answer questions, but if you collect too much then you may not be able to distill the specific subset that will answer your questions. Also, explicit or inherent cost can prevent you from collecting all possible data, in which case you need to carefully select which areas to collect data about.

Let's take a look at how this is done in clinical trials. Say you're designing a clinical study that will analyze cancer data. You may not have specific questions when the study is being designed, but it's reasonable to assume that you'll want to collect data related to commonly impacted readings for the type of cancer and whatever body system is affected, so that you have the right information to analyze when it comes time.

You may also want to collect data unrelated to the specific disease that subsequent questions will likely require, such as information on demographics and medications that the patient is taking that are different from the treatment. During the post-study data analysis, questions on these areas often arise, even though the questions aren't initially apparent. Thus clinical researchers have adopted common processes for collecting data on demographics and concomitant medications. Through planning and experience, you can also identify areas that do not need to be collected for each study. For example, if you're studying lung cancer, collecting cognitive function data is probably unrelated.

How can other industries anticipate what questions to ask, as is done in life sciences? Well, determine a predefined set of questions that are directly related to the goal of the data analysis. Since you will not know all of the questions until after the data collection have started, it's important to 1) know the domain, and 2) collect any data you'll need to answer the likely questions that could come up.

Also, clinical researchers have learned that questions can be discovered automatically. There are data mining techniques that can uncover statistically significant connections, which in effect are raising questions that can be explored in more detail afterwards. An analysis can be planned before data is collected, but not actually be run until afterwards (or potentially during), if the appropriate data is collected.

One other area that has proven to be extremely important to collect is metadata, or data about the data - such as, when it was collected, where it was collected, what instrumentation was used in the process and what calibration information was available. All of this information can be utilized later on to answer a lot of potentially important questions. Maybe there was a specific instrument that was incorrectly configured and all the resulting data that it recorded is invalid. If you're running an ad network, maybe there's a specific web site where your ads are run that are gaming the system trying to get you to pay more. If you're running a minor league team, maybe there's a specific referee that's biased, which you can address for subsequent games. Or, if you're plotting oil reserves in the Gulf of Mexico, maybe there are certain exploratory vessels that are taking advantage of you. In all of these cases, without the appropriate metadata, it'd be impossible to know where real problems reside.

Identifying Touch Points to Be Reviewed Along the Way
There are ways to specify which types of analysis can be performed, even while data is being collected, that can affect either how data will continue to be collected or the outcome as a whole.

For example, some clinical studies run what's called interim analysis while the study is in progress. These interim analyses are planned, and the various courses that can be used afterwards are well defined, but the results afterward are statistically usable. This is called an adaptive clinical trial, and there are a lot of studies that are being performed to determine more effective and useful ways that these can be done in the future. The most important aspect of these is preventing biases, and this is something that has been well understood and tested by the pharmaceutical community over the past several decades. Simply understanding what's happening during the course of a trial, or how it affects the desired outcome, can actually bias the results.

The other key factor is that the touch points are accessible to everybody who needs the data. For example, if you have a person in the field, then it's important to have him or her access the data in a format that's easily consumable to them - maybe through an iPad or an existing intranet portal. Similarly, if you have an executive that needs to understand something at a high level, then getting it to them in an easily consumable executive dashboard is extremely important.

As the life sciences industry has learned, if the distribution channels of the analytics aren't seamless and frictionless, then they won't be utilized to their fullest extent. This is where cloud-based analytics become exceptionally powerful - the cloud makes it much easier to integrate analytics into every user's day. Once each user gets the exact information they need, effortlessly, they can then do their job better and the entire organization will work better - regardless of how and why the tools are being used.

Augmenting Human Intuition
Think about the different types of tools that people use on a daily basis. People use wrenches to help turn screws, cars to get to places faster and word processers to write. Sure, we can use our hands or walk, but we're much more efficient and better when we can use tools.

Cloud-based analytics is a tool that enables everybody in an organization to perform more efficiently and effectively. The first example of this type of augmentation in the life sciences industry is alerting. A user tells the computer what they want to see, and then the computer alerts them via email or text message when the situation arises. Users can set rules for the data it wants to see, and then the tools keep on the lookout to notify the user when the data they are looking for becomes available.

Another area the pharmaceutical industry has thoroughly explored is data-driven collaboration techniques. In the clinical trial process, there are many different groups of users: those who are physically collecting the data (investigators), others who are reviewing it to make sure that it's clean (data managers), and also people who are stuck in the middle (clinical monitors). Of course there are many other types of users, but this is just a subset to illustrate the point. These different groups of users all serve a particular purpose relating to the overall collection of data and success of the study. When the data looks problematic or unclean, the data managers will flag it for review, which the clinical monitors can act on.

What's unique about the way that life sciences deals with this is that they've set up complex systems and rules to make sure that the whole system runs well. The tools associated around these processes help augment human intuition through alerting, automated dissemination and automatic feedback. The questions aren't necessarily known at the beginning of a trial, but as the data is collected, new questions evolve and the tools and processes in place are built to handle the changing landscape.

No matter what the purpose of Big Data analytics, any organization can benefit from the mindset of cloud-based analytics as a tool that needs to consistently be adjusted and refined to meet the needs of users.

Ongoing Challenges of Big Data Analytics
Given this history with data, one would expect that drug and device developers would be light years ahead when it comes to leveraging Big Data technologies - especially given that the collection and analytics of clinical data is often a matter of life and death. But while they have much more experience with data, the truth is that life sciences organizations are just now starting to integrate analytics technologies that will enable them to work with that data in new, more efficient ways - no longer involving billions of dollars a year, countless statisticians, archaic methods, and, if we're being honest, brute force. As new technology becomes available, the industry will continue to become more and more seamless. In the meantime, other industries looking to wrap their heads around the Big Data challenge should look to life sciences as the starting point for best practices in understanding how and when to ask the right questions, monitoring data along the way and selecting tools that improve the user experience.

More Stories By Rick Morrison

Rick Morrison is CEO and co-founder of Comprehend Systems. Prior to Comprehend Systems, he was the Chief Technology Officer of an Internet-based data aggregator, where he was responsible for product development and operations. Prior to that, he was at Integrated Clinical Systems, where he led the design and implementation of several major new features. He also proposed and led a major infrastructure redesign, and introduced new, streamlined development processes. Rick holds a BS in Computer Science from Carnegie Mellon University in Pittsburgh, Pennsylvania.

Comments (0)

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.


@ThingsExpo Stories

SUNNYVALE, Calif., Oct. 20, 2014 /PRNewswire/ -- Spansion Inc. (NYSE: CODE), a global leader in embedded systems, today added 96 new products to the Spansion® FM4 Family of flexible microcontrollers (MCUs). Based on the ARM® Cortex®-M4F core, the new MCUs boast a 200 MHz operating frequency and support a diverse set of on-chip peripherals for enhanced human machine interfaces (HMIs) and machine-to-machine (M2M) communications. The rich set of periphera...

WebRTC defines no default signaling protocol, causing fragmentation between WebRTC silos. SIP and XMPP provide possibilities, but come with considerable complexity and are not designed for use in a web environment. In his session at Internet of @ThingsExpo, Matthew Hodgson, technical co-founder of the Matrix.org, will discuss how Matrix is a new non-profit Open Source Project that defines both a new HTTP-based standard for VoIP & IM signaling and provides reference implementations.
SYS-CON Events announced today that Aria Systems, the recurring revenue expert, has been named "Bronze Sponsor" of SYS-CON's 15th International Cloud Expo®, which will take place on November 4-6, 2014, at the Santa Clara Convention Center in Santa Clara, CA. Aria Systems helps leading businesses connect their customers with the products and services they love. Industry leaders like Pitney Bowes, Experian, AAA NCNU, VMware, HootSuite and many others choose Aria to power their recurring revenue business and deliver exceptional experiences to their customers.
The Internet of Things (IoT) is going to require a new way of thinking and of developing software for speed, security and innovation. This requires IT leaders to balance business as usual while anticipating for the next market and technology trends. Cloud provides the right IT asset portfolio to help today’s IT leaders manage the old and prepare for the new. Today the cloud conversation is evolving from private and public to hybrid. This session will provide use cases and insights to reinforce the value of the network in helping organizations to maximize their company’s cloud experience.
The Internet of Things (IoT) is making everything it touches smarter – smart devices, smart cars and smart cities. And lucky us, we’re just beginning to reap the benefits as we work toward a networked society. However, this technology-driven innovation is impacting more than just individuals. The IoT has an environmental impact as well, which brings us to the theme of this month’s #IoTuesday Twitter chat. The ability to remove inefficiencies through connected objects is driving change throughout every sector, including waste management. BigBelly Solar, located just outside of Boston, is trans...
SYS-CON Events announced today that Matrix.org has been named “Silver Sponsor” of Internet of @ThingsExpo, which will take place on November 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA. Matrix is an ambitious new open standard for open, distributed, real-time communication over IP. It defines a new approach for interoperable Instant Messaging and VoIP based on pragmatic HTTP APIs and WebRTC, and provides open source reference implementations to showcase and bootstrap the new standard. Our focus is on simplicity, security, and supporting the fullest feature set.
Predicted by Gartner to add $1.9 trillion to the global economy by 2020, the Internet of Everything (IoE) is based on the idea that devices, systems and services will connect in simple, transparent ways, enabling seamless interactions among devices across brands and sectors. As this vision unfolds, it is clear that no single company can accomplish the level of interoperability required to support the horizontal aspects of the IoE. The AllSeen Alliance, announced in December 2013, was formed with the goal to advance IoE adoption and innovation in the connected home, healthcare, education, aut...
SYS-CON Events announced today that Red Hat, the world's leading provider of open source solutions, will exhibit at Internet of @ThingsExpo, which will take place on November 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA. Red Hat is the world's leading provider of open source software solutions, using a community-powered approach to reliable and high-performing cloud, Linux, middleware, storage and virtualization technologies. Red Hat also offers award-winning support, training, and consulting services. As the connective hub in a global network of enterprises, partners, a...
The only place to be June 9-11 is Cloud Expo & @ThingsExpo 2015 East at the Javits Center in New York City. Join us there as delegates from all over the world come to listen to and engage with speakers & sponsors from the leading Cloud Computing, IoT & Big Data companies. Cloud Expo & @ThingsExpo are the leading events covering the booming market of Cloud Computing, IoT & Big Data for the enterprise. Speakers from all over the world will be hand-picked for their ability to explore the economic strategies that utility/cloud computing provides. Whether public, private, or in a hybrid form, clo...
Software AG helps organizations transform into Digital Enterprises, so they can differentiate from competitors and better engage customers, partners and employees. Using the Software AG Suite, companies can close the gap between business and IT to create digital systems of differentiation that drive front-line agility. We offer four on-ramps to the Digital Enterprise: alignment through collaborative process analysis; transformation through portfolio management; agility through process automation and integration; and visibility through intelligent business operations and big data.
The Transparent Cloud-computing Consortium (abbreviation: T-Cloud Consortium) will conduct research activities into changes in the computing model as a result of collaboration between "device" and "cloud" and the creation of new value and markets through organic data processing High speed and high quality networks, and dramatic improvements in computer processing capabilities, have greatly changed the nature of applications and made the storing and processing of data on the network commonplace.
Be Among the First 100 to Attend & Receive a Smart Beacon. The Physical Web is an open web project within the Chrome team at Google. Scott Jenson leads a team that is working to leverage the scalability and openness of the web to talk to smart devices. The Physical Web uses bluetooth low energy beacons to broadcast an URL wirelessly using an open protocol. Nearby devices can find all URLs in the room, rank them and let the user pick one from a list. Each device is, in effect, a gateway to a web page. This unlocks entirely new use cases so devices can offer tiny bits of information or simple i...
The Internet of Things (IoT) is going to require a new way of thinking and of developing software for speed, security and innovation. This requires IT leaders to balance business as usual while anticipating for the next market and technology trends. Cloud provides the right IT asset portfolio to help today’s IT leaders manage the old and prepare for the new. Today the cloud conversation is evolving from private and public to hybrid. This session will provide use cases and insights to reinforce the value of the network in helping organizations to maximize their company’s cloud experience.
Things are being built upon cloud foundations to transform organizations. This CEO Power Panel at 15th Cloud Expo, moderated by Roger Strukhoff, Cloud Expo and @ThingsExpo conference chair, will address the big issues involving these technologies and, more important, the results they will achieve. How important are public, private, and hybrid cloud to the enterprise? How does one define Big Data? And how is the IoT tying all this together?
TechCrunch reported that "Berlin-based relayr, maker of the WunderBar, an Internet of Things (IoT) hardware dev kit which resembles a chunky chocolate bar, has closed a $2.3 million seed round, from unnamed U.S. and Switzerland-based investors. The startup had previously raised a €250,000 friend and family round, and had been on track to close a €500,000 seed earlier this year — but received a higher funding offer from a different set of investors, which is the $2.3M round it’s reporting."
The Industrial Internet revolution is now underway, enabled by connected machines and billions of devices that communicate and collaborate. The massive amounts of Big Data requiring real-time analysis is flooding legacy IT systems and giving way to cloud environments that can handle the unpredictable workloads. Yet many barriers remain until we can fully realize the opportunities and benefits from the convergence of machines and devices with Big Data and the cloud, including interoperability, data security and privacy.
All major researchers estimate there will be tens of billions devices - computers, smartphones, tablets, and sensors - connected to the Internet by 2020. This number will continue to grow at a rapid pace for the next several decades. Over the summer Gartner released its much anticipated annual Hype Cycle report and the big news is that Internet of Things has now replaced Big Data as the most hyped technology. Indeed, we're hearing more and more about this fascinating new technological paradigm. Every other IT news item seems to be about IoT and its implications on the future of digital busines...
Cultural, regulatory, environmental, political and economic (CREPE) conditions over the past decade are creating cross-industry solution spaces that require processes and technologies from both the Internet of Things (IoT), and Data Management and Analytics (DMA). These solution spaces are evolving into Sensor Analytics Ecosystems (SAE) that represent significant new opportunities for organizations of all types. Public Utilities throughout the world, providing electricity, natural gas and water, are pursuing SmartGrid initiatives that represent one of the more mature examples of SAE. We have s...
The Internet of Things needs an entirely new security model, or does it? Can we save some old and tested controls for the latest emerging and different technology environments? In his session at Internet of @ThingsExpo, Davi Ottenheimer, EMC Senior Director of Trust, will review hands-on lessons with IoT devices and reveal privacy options and a new risk balance you might not expect.
IoT is still a vague buzzword for many people. In his session at Internet of @ThingsExpo, Mike Kavis, Vice President & Principal Cloud Architect at Cloud Technology Partners, will discuss the business value of IoT that goes far beyond the general public's perception that IoT is all about wearables and home consumer services. The presentation will also discuss how IoT is perceived by investors and how venture capitalist access this space. Other topics to discuss are barriers to success, what is new, what is old, and what the future may hold.