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Understanding The Body With Smart Data: In-Memory Technology In Personalized Medicine

Frank Wittmann

Huge amounts of data exist in today’s healthcare. Technically speaking, this data can be analyzed with real-time methods, such as in-memory technology, and be made available for medical treatment.

Computer researchers at Hasso Plattner Institute (HPI) are thus working to help patients receive more personalized treatment.

The human body is complex. Just one genome, for instance, contains more than 3 billion pieces of genetic information. Modern medicine seeks to penetrate this complexity in order to offer patients even better treatment. New diagnostic procedures like genome sequencing help exploit these huge data sources. However, the analysis involved often proves difficult. The problems lie in the diversity of the distributed data and its collection.

“Physicians have become data analysts, who must laboriously gather and standardize the data themselves,” says Dr. Matthieu-P. Schapranow, program manager of E-Health & Life Sciences at Hasso Plattner Institute (HPI). Consequently, the time-consuming analyzes are only carried out in certain cases. Yet already today interdisciplinary teams can create future-proof solutions, the Potsdam scientist said.

Together with project partners from clinical research, Schapranow’s team in the HPI Research Group led by Prof. Hasso Plattner are working on customized software applications that support experts in the analysis of huge amounts of data. The in-memory technology researched at HPI is thereby used, which for the first time allows combining and analyzing large amounts of data in real time.

“Physicians, clinical researchers and health experts can make precise therapy decisions based on the knowledge available worldwide, regardless of where they are located,” says Schapranow. In addition to individual patient data, information from worldwide medical databases is also at their disposal. Physicians can then concentrate on what is most crucial to them—the treatment of their patients. Not only does faster and more accurate decision-making then become possible, but also a minimization of side effects and a reduction of costs, said the computer scientist.

The cloud platform Analyze Genomes bundles the joint research of the Potsdam scientists with that of physicians, biologists, and geneticists. The platform already offers researchers and doctors applications for their work:

  • With the help of the Genome Browser, even without access to sequencing machines, researchers can explore DNS in detail and identify information about pathogenic changes themselves.
  • In the Medical Knowledge Cockpit, doctors and patients get a comprehensive picture of individual and genetic characteristics, biological relationships, and information about the therapies available worldwide.
  • Clinicians can use the Drug Response Analysis to incorporate, for the first time, findings from past cases to the chemotherapy prognosis for current cases

Schapranow and his team present two ongoing research projects from the health sector at CeBIT 2016 (Hasso Plattner Institute, Hall 6, D18):

  • The SMART project, sponsored by the Federal Ministry of Research program e: Med – Med Sys, is focused on facilitating a better understanding of the complex causes of chronic heart failure and how they interact. Using the methods of analysis, physicians will be able to make better predictions in the future about the possible course of the disease and therapeutic successes.
  • With their project Smart Analysis – Health Research Access (SAHRA), HPI scientists show how huge amounts of already available healthcare data can be combined and examined on the basis of in-memory technology and scientific analysis. Treatment, billing, study, and registry data, rendered anonymous to protect privacy, can be combined and made available for healthcare research.

The application of in-memory technology and information technology analysis methods in medicine are manifold. The range of possibilities extends from the planning of future medical care to the personalization of cancer treatment. But the goal of the various research fields always remains the same: to make it possible for patients to get the best holistic treatment now and in the future.

For more on the power of Big Data and analytics in healthcare, see Analytics And Personalized Medicine—Just The Tip Of The Iceberg.

Top image via Shutterstock

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Frank Wittmann

About Frank Wittmann

Frank Wittmann is the online marketing manager for the Hasso Plattner Institute. His specialties include online marketing, social media marketing, web content management, online publishing and online communications.

Data Analysts And Scientists More Important Than Ever For The Enterprise

Daniel Newman

The business world is now firmly in the age of data. Not that data wasn’t relevant before; it was just nowhere close to the speed and volume that’s available to us today. Businesses are buckling under the deluge of petabytes, exabytes, and zettabytes. Within these bytes lie valuable information on customer behavior, key business insights, and revenue generation. However, all that data is practically useless for businesses without the ability to identify the right data. Plus, if they don’t have the talent and resources to capture the right data, organize it, dissect it, draw actionable insights from it and, finally, deliver those insights in a meaningful way, their data initiatives will fail.

Rise of the CDO

Companies of all sizes can easily find themselves drowning in data generated from websites, landing pages, social streams, emails, text messages, and many other sources. Additionally, there is data in their own repositories. With so much data at their disposal, companies are under mounting pressure to utilize it to generate insights. These insights are critical because they can (and should) drive the overall business strategy and help companies make better business decisions. To leverage the power of data analytics, businesses need more “top-management muscle” specialized in the field of data science. This specialized field has lead to the creation of roles like Chief Data Officer (CDO).

In addition, with more companies undertaking digital transformations, there’s greater impetus for the C-suite to make data-driven decisions. The CDO helps make data-driven decisions and also develops a digital business strategy around those decisions. As data grows at an unstoppable rate, becoming an inseparable part of key business functions, we will see the CDO act as a bridge between other C-suite execs.

Data skills an emerging business necessity

So far, only large enterprises with bigger data mining and management needs maintain in-house solutions. These in-house teams and technologies handle the growing sets of diverse and dispersed data. Others work with third-party service providers to develop and execute their big data strategies.

As the amount of data grows, the need to mine it for insights becomes a key business requirement. For both large and small businesses, data-centric roles will experience endless upward mobility. These roles include data anlysts and scientists. There is going to be a huge opportunity for critical thinkers to turn their analytical skills into rapidly growing roles in the field of data science. In fact, data skills are now a prized qualification for titles like IT project managers and computer systems analysts.

Forbes cited the McKinsey Global Institute’s prediction that by 2018 there could be a massive shortage of data-skilled professionals. This indicates a disruption at the demand-supply level with the needs for data skills at an all-time high. With an increasing number of companies adopting big data strategies, salaries for data jobs are going through the roof. This is turning the position into a highly coveted one.

According to Harvard Professor Gary King, “There is a big data revolution. The big data revolution is that now we can do something with the data.” The big problem is that most enterprises don’t know what to do with data. Data professionals are helping businesses figure that out. So if you’re casting about for where to apply your skills and want to take advantage of one of the best career paths in the job market today, focus on data science.

I’m compensated by University of Phoenix for this blog. As always, all thoughts and opinions are my own.

For more insight on our increasingly connected future, see The $19 Trillion Question: Are You Undervaluing The Internet Of Things?

The post Data Analysts and Scientists More Important Than Ever For the Enterprise appeared first on Millennial CEO.

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Daniel Newman

About Daniel Newman

Daniel Newman serves as the Co-Founder and CEO of EC3, a quickly growing hosted IT and Communication service provider. Prior to this role Daniel has held several prominent leadership roles including serving as CEO of United Visual. Parent company to United Visual Systems, United Visual Productions, and United GlobalComm; a family of companies focused on Visual Communications and Audio Visual Technologies. Daniel is also widely published and active in the Social Media Community. He is the Author of Amazon Best Selling Business Book "The Millennial CEO." Daniel also Co-Founded the Global online Community 12 Most and was recognized by the Huffington Post as one of the 100 Business and Leadership Accounts to Follow on Twitter. Newman is an Adjunct Professor of Management at North Central College. He attained his undergraduate degree in Marketing at Northern Illinois University and an Executive MBA from North Central College in Naperville, IL. Newman currently resides in Aurora, Illinois with his wife (Lisa) and his two daughters (Hailey 9, Avery 5). A Chicago native all of his life, Newman is an avid golfer, a fitness fan, and a classically trained pianist

When Good Is Good Enough: Guiding Business Users On BI Practices

Ina Felsheim

Image_part2-300x200In Part One of this blog series, I talked about changing your IT culture to better support self-service BI and data discovery. Absolutely essential. However, your work is not done!

Self-service BI and data discovery will drive the number of users using the BI solutions to rapidly expand. Yet all of these more casual users will not be well versed in BI and visualization best practices.

When your user base rapidly expands to more casual users, you need to help educate them on what is important. For example, one IT manager told me that his casual BI users were making visualizations with very difficult-to-read charts and customizing color palettes to incredible degrees.

I had a similar experience when I was a technical writer. One of our lead writers was so concerned with readability of every sentence that he was going through the 300+ page manuals (yes, they were printed then) and manually adjusting all of the line breaks and page breaks. (!) Yes, readability was incrementally improved. But now any number of changes–technical capabilities, edits, inserting larger graphics—required re-adjusting all of those manual “optimizations.” The time it took just to do the additional optimization was incredible, much less the maintenance of these optimizations! Meanwhile, the technical writing team was falling behind on new deliverables.

The same scenario applies to your new casual BI users. This new group needs guidance to help them focus on the highest value practices:

  • Customization of color and appearance of visualizations: When is this customization necessary for a management deliverable, versus indulging an OCD tendency? I too have to stop myself from obsessing about the font, line spacing, and that a certain blue is just a bit different than another shade of blue. Yes, these options do matter. But help these casual users determine when that time is well spent.
  • Proper visualizations: When is a spinning 3D pie chart necessary to grab someone’s attention? BI professionals would firmly say “NEVER!” But these casual users do not have a lot of depth on BI best practices. Give them a few simple guidelines as to when “flash” needs to subsume understanding. Consider offering a monthly one-hour Lunch and Learn that shows them how to create impactful, polished visuals. Understanding if their visualizations are going to be viewed casually on the way to a meeting, or dissected at a laptop, also helps determine how much time to spend optimizing a visualization. No, you can’t just mandate that they all read Tufte.
  • Predictive: Provide advanced analytics capabilities like forecasting and regression directly in their casual BI tools. Using these capabilities will really help them wow their audience with substance instead of flash.
  • Feature requests: Make sure you understand the motivation and business value behind some of the casual users’ requests. These casual users are less likely to understand the implications of supporting specific requests across an enterprise, so make sure you are collaborating on use cases and priorities for substantive requests.

By working with your casual BI users on the above points, you will be able to collectively understand when the absolute exact request is critical (and supports good visualization practices), and when it is an “optimization” that may impact productivity. In many cases, “good” is good enough for the fast turnaround of data discovery.

Next week, I’ll wrap this series up with hints on getting your casual users to embrace the “we” not “me” mentality.

Read Part One of this series: Changing The IT Culture For Self-Service BI Success.

Follow me on Twitter: @InaSAP

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How Much Will Digital Cannibalization Eat into Your Business?

Fawn Fitter

Former Cisco CEO John Chambers predicts that 40% of companies will crumble when they fail to complete a successful digital transformation.

These legacy companies may be trying to keep up with insurgent companies that are introducing disruptive technologies, but they’re being held back by the ease of doing business the way they always have – or by how vehemently their customers object to change.

Most organizations today know that they have to embrace innovation. The question is whether they can put a digital business model in place without damaging their existing business so badly that they don’t survive the transition. We gathered a panel of experts to discuss the fine line between disruption and destruction.

SAP_Disruption_QA_images2400x1600_3

qa_qIn 2011, when Netflix hiked prices and tried to split its streaming and DVD-bymail services, it lost 3.25% of its customer base and 75% of its market capitalization.²︐³ What can we learn from that?

Scott Anthony: That debacle shows that sometimes you can get ahead of your customers. The key is to manage things at the pace of the market, not at your internal speed. You need to know what your customers are looking for and what they’re willing to tolerate. Sometimes companies forget what their customers want and care about, and they try to push things on them before they’re ready.

R. “Ray” Wang: You need to be able to split your traditional business and your growth business so that you can focus on big shifts instead of moving the needle 2%. Netflix was responding to its customers – by deciding not to define its brand too narrowly.

qa_qDoes disruption always involve cannibalizing your own business?

Wang: You can’t design new experiences in existing systems. But you have to make sure you manage the revenue stream on the way down in the old business model while managing the growth of the new one.

Merijn Helle: Traditional brick-and-mortar stores are putting a lot of capital into digital initiatives that aren’t paying enough back yet in the form of online sales, and they’re cannibalizing their profits so they can deliver a single authentic experience. Customers don’t see channels, they see brands; and they want to interact with brands seamlessly in real time, regardless of channel or format.

Lars Bastian: In manufacturing, new technologies aren’t about disrupting your business model as much as they are about expanding it. Think about predictive maintenance, the ability to warn customers when the product they’ve purchased will need service. You’re not going to lose customers by introducing new processes. You have to add these digitized services to remain competitive.

qa_qIs cannibalizing your own business better or worse than losing market share to a more innovative competitor?

Michael Liebhold: You have to create that digital business and mandate it to grow. If you cannibalize the existing business, that’s just the price you have to pay.

Wang: Companies that cannibalize their own businesses are the ones that survive. If you don’t do it, someone else will. What we’re really talking about is “Why do you exist? Why does anyone want to buy from you?”

Anthony: I’m not sure that’s the right question. The fundamental question is what you’re using disruption to do. How do you use it to strengthen what you’re doing today, and what new things does it enable? I think you can get so consumed with all the changes that reconfigure what you’re doing today that you do only that. And if you do only that, your business becomes smaller, less significant, and less interesting.

qa_qSo how should companies think about smart disruption?

Anthony: Leaders have to reconfigure today and imagine tomorrow at the same time. It’s not either/or. Every disruptive threat has an equal, if not greater, opportunity. When disruption strikes, it’s a mistake only to feel the threat to your legacy business. It’s an opportunity to expand into a different marke.

SAP_Disruption_QA_images2400x1600_4Liebhold: It starts at the top. You can’t ask a CEO for an eight-figure budget to upgrade a cloud analytics system if the C-suite doesn’t understand the power of integrating data from across all the legacy systems. So the first task is to educate the senior team so it can approve the budgets.

Scott Underwood: Some of the most interesting questions are internal organizational questions, keeping people from feeling that their livelihoods are in danger or introducing ways to keep them engaged.

Leon Segal: Absolutely. If you want to enter a new market or introduce a new product, there’s a whole chain of stakeholders – including your own employees and the distribution chain. Their experiences are also new. Once you start looking for things that affect their experience, you can’t help doing it. You walk around the office and say, “That doesn’t look right, they don’t look happy. Maybe we should change that around.”

Fawn Fitter is a freelance writer specializing in business and technology. 

To learn more about how to disrupt your business without destroying it, read the in-depth report Digital Disruption: When to Cook the Golden Goose.

Download the PDF (1.2MB)

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3 Ways To Convince Your Workforce To Stop Fearing Digital Transformation

Paul Kurchina

Change of any kind – especially when it’s foisted on you without your commitment – can be dreadful. It may even resemble the return home from a disappointing doctor’s appointment. After shocking the doctor with high numbers across the board, your spouse replaces all of your most-loved foods (the leftover pizza from last night!) and beverages (the after-work beer and soda!) with kale, quinoa, and juice that looks like algae purged by a blender. Immediately, you resist: “How dare my loved one change my diet without my consent! I have no control! Why eat if I can’t be happy with what’s on my plate?”

That’s exactly how most employees view digital transformation initiatives. During the Americas’ SAP User Group (ASUG) webcast “The Only Thing to Fear Is Fear Itself: Embracing Change and Seizing the Opportunity of the Digital Transformation,” Keith R. Sturgill, CIO of Eastman Chemical Company and ASUG Board Chair, said, “in times of transformative change, great opportunities are invaluable. But, it also comes at a great cost because it’s not easy.” Sometimes the process is so daunting that we stop it, ignore it, and resume using our ingrained habits.

While technology-enabled, the real change behind digital transformation is all about people: how they work, collaborate, and make decisions. And changing people is always harder than implementing new technology. But, it’s not impossible once everyone – including leadership, employees, and partners – accepts these three realities of our digital world.

Reality check #1: Digital disruption is not just evolving. It’s already here!

Hearing from customers directly, reacting to what they want, and correcting what they don’t like at hard-to-imagine speeds is raising the bar high for every business. “Connecting people worldwide isn’t just allowing them to self-organize ideas and share opinions; it’s creating a new environment [in which] new business models can emerge. Just ask any growing business,” says Sturgill.

Just think:

  • Amazon is changing the face of retail without a single brick-and-mortar store
  • Airbnb is surpassing traditional hotels and motels without building a physical resort
  • Uber is upending the whole notion of taxi service without a single cab

However, it’s not as easy as setting up a website and creating a network of people, assets, and capital to support it. According to Sturgill, “it’s impossible to know the impact of what’s going to occur [in the future.] We can’t even begin to imagine how this is going to change the world. But without a doubt, it will be huge.”

Reality check #2: Decision making will never – and cannot – be the same

In the past, computers were set up with rules to inject automation and efficiency into business processes. Yet, they failed to support more difficult, complex problem solving such as predictions and forecasting that went beyond the scope of a predefined set of algorithms.

Our digital era is bringing about a new approach to decision making. Not just improving or accelerating decisions, but ultimately changing how they are made. Without the confines of codified decision flows, machine learning will soon consume and process an incredible amount of data to “understand” patterns and correlations. And as more data enters the systems, decisions on complex issues will likely become more improved and accurate.

“Machine learning algorithms will augment human insights, not replace them. Let people do what they do best – create, design, establish relationships and capabilities, and knit together insights to innovate with better judgment and unimaginable ideas,” advises Sturgill. “Think of your business as a decision machine.”

Reality check #3: The user experience (not technology) matters most

Like I said earlier in this blog, digital transformation is not about the technology you implement; it’s about your people. This is why the user experience will always eclipse corporate standards. From your customer to your workforce, consumer-grade technology is increasingly expected to become the norm – and it’s even happening to business-to-business (B2B) companies quicker than anyone realizes.

Most digital transformation strategies place a bright spotlight on the customer experience. By understanding what customers value and their unique preferences, B2B companies are using technology as a differentiator that gives customers a reason to engage and purchase from the business.

However, digital transformation does not end with the customer experience. “It is about people in your organization – talented, empowered, and passionate people. Employees should expect the work environment to be at least as good as their home computing environment. It should be as easy to order a new laptop at work as it is at home,” remarks Sturgill. “You need to commit to improving the work experience of your employees.”

Get your workforce engaged and passionate about digital transformation. Watch the webcast replay The Only Thing to Fear Is Fear Itself: Embracing Change and Seizing the Opportunity of the Digital Transformationin a series hosted by ASUG.

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