Slides: Enterprise Architecture in the Era of Big Data and Quantum Computing

Back in April, Big Data Palooza MeetUp group held an awesome event on an ever-popular topic: enterprise architecture. However, this presentation took a unique big data and quantum computing spin.

In this presentation, titled “Enterprise Architecture in the Era of Big Data and Quantum Computing,” Enterprise Architect Jim Luisi covered the characteristics that identify the presence of big data and examples of useful frameworks to manage and organize big data products, including use case families and architectural disciplines.

Invariably, as new big data use cases emerge, new products emerge to address them. At this point, there are so many use cases and so many products that frameworks to organize and manage them are necessary.

Missed the MeetUp? You can view the slides here:

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Can Big Data Help Companies Cut Healthcare Spending?

It’s hardly news to anyone that healthcare costs have long been on the rise in the U.S. For firms footing the bill for employee healthcare, this pain has been especially acute of late. According to the Kayser Family Foundation, employers’ contribution to an average family’s yearly health insurance premium grew over 77% from 2003 to 2013. Pharmacy benefit costs make up more than 16% of that premium. Healthcare costs make up the second highest proportion of corporate spending after salary (7.9% of total compensation, by the latest figures).

The ever-looming crisis has CFOs and benefit managers scrambling to cut costs and reduce benefits – with some choosing to attack costs through wellness programs, incentives for healthy living, and preventive diagnostics. A raft of data analytics outfits and consulting firms, along with motley startups, have rushed in to fill the demand for cutting costs, squeezing efficiencies, improving vendor sourcing, restructuring provider networks, and re-negotiating rates.

The smart money these days is on Big Data to solve all sorts of problems through the impartial, cold and calculating lens of Big Analytics. Can it help companies cut healthcare costs? Time will tell, of course, but the first signs are promising.

When it comes to enterprise health spend analysis, incumbents like Verisk Health, Truven Health, and MedAI, along with Big Data behemoths lBM, Oracle, SAS, and McKinsey have all jumped into the fray, offering reporting capabilities and predictive modeling to hospital systems and insurers.

At the same time, newcomers like Zakipoint Health, Health Care DataWorks, and Zephyr Health, among others, are seeking to shake things up with top-notch analytics and visualization tools and custom-tailored recommendations for CFOs and benefit managers to optimize cost-cutting.

Big Data also is making inroads in improving employee wellness. Well-funded Flatiron Health is partnering with cancer centers to create a Big Data cloud that captures more than 100,000 cancer patients’ data, giving unprecedented insight into the disease across a large patient pool. uBiome is building and studying a database of bodily bacteria profiles from across its customer base. Withings and Fitbit, plus the bigger players like Samsung and Apple are building wearables to track quite every aspect of one’s health and wellness, starting with sleep habits, exercises, running distance, calories, and weight. Apps engaging users to record, monitor, and track nearly every aspect of their lives have sprung up like a cottage industry.

All this brings us right back to cost containment. What is our surest bet when targeting the costs of healthcare all across the enterprise? Is it to visualize the costs and see the big cost drivers and to squeeze out inefficiencies, short-term? Or is it to hand out pedometers and FitBits and track the living tissue out of employees? Aside from simply cutting benefits, a third and harsher option is to penalize for non-compliance with directives to enroll in certain programs to improve employee health, based on criteria hand-tailored to maintain a healthy workforce.

Leaders among the corporate players with a keen and cost-effective eye already have some combination of these three that they are using. Studies are scant on what has worked; this seemingly quite obvious approach is only starting to firm up in numbers and specifics.

With U.S. healthcare spending hulking in at $3.8 trillion in 2013 and ever on the rise, companies are scrambling for magic bullets to improve their bottom line. Early observers feared that ObamaCare would lead to slashed hours to decrease employer health insurance liability, but the scenario simply hasn’t panned out.

All the same, health insurance costs are rising. As data on cost drivers, problem employee demographics, procedure effectiveness, doctor reimbursement rates, and others become available, enterprises will calibrate the rewards and the punishments more carefully to make employees more accountable for their healthcare. With better tools and expertise to understand that data and to make it actionable, employee health may soon be commoditized and scored like creditworthiness. In the meantime, enterprises will continue to grope around for short-term solutions.

Is your organization using these strategies (or others) to manage healthcare spending? Let us know in the comments!

Knowledgent Cares for Saturday’s/Sunday’s Bread in Boston

We at Knowledgent are always looking to give back to our communities. That’s why we started Knowledgent Cares, our employee volunteer program.  From orphanages in Haiti to our local food banks, we’re committed to raising awareness, improving lives, providing opportunities, and volunteering for causes important to us through the power of caring.

As part of Knowledgent Cares, this past Saturday, our Boston-based team helped Saturday’s/Sunday’s Bread prepare and serve hot meals to 96 individuals in need of a good home-cooked meal! Saturday’s/Sunday’s Bread has been serving free hot meals to those in need in the city for the past 38 years.  Over the past 28 years, Saturday’s/Sunday’s Bread has served more than 300,000 guests.

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For more pics of our Knowledgent Cares volunteers in action, visit our Flickr album.

Slides: Leveraging Big Data in the Life Sciences and Healthcare Webinar

In case you missed it, Knowledgent recently co-hosted a webinar titled “Leveraging Big Data in the Life Sciences and Healthcare.” The webinar featured thoughts on using big data technologies and analytics to further Alzheimer’s advancements in research and patient care.  Speakers included  Justin Sears, Industry Specialist at Hortonworks, Drew Holzapfel, Executive Director from the Global CEO Initiative on Alzheimer’s Disease, and our very own Tom Johnstone and Chris Young.

Here’s the full slide deck from the webinar:

Continue reading Slides: Leveraging Big Data in the Life Sciences and Healthcare Webinar

Infographic: Levels of Big Data Maturity

As more organizations implement data and analytics programs, Knowledgent is seeing a clear progression from basic reporting to more advanced analytics. But what characteristics differentiate a mature organization from one that is just starting out? What do mid-level organizations need to do to reach a level where they can collaborate and share analytics across the enterprise? What do organizations need to increase their levels of big data maturity? This month’s infographic answers these questions and more.

Continue reading Infographic: Levels of Big Data Maturity

Case Study: How a Financial Insurance Company Executed a Big Data Strategy to Become a Data-Driven Enterprise

Challenge

Our client, a financial insurance organization, envisioned having a next-generation data platform to make data analysis and innovation faster, easier, and more streamlined.  Our client had previously evaluated big data technologies and wanted to craft a strategy that would make them a “data-driven enterprise.”

As part of this initiative, they sought a technical evaluation of their solution architecture, a cross-organizational readiness assessment, and an impact evaluation of their initial big data analytics use cases.  They also needed a tactical action plan and a multi-year implementation roadmap following executive buy-in and plan approval.

Continue reading Case Study: How a Financial Insurance Company Executed a Big Data Strategy to Become a Data-Driven Enterprise

Case Study: How a Large BioTech Firm Enabled Fast and Easy Self-Service Big Data Discovery

Challenge

Biotechnology organizations frequently outsource early discovery to multiple contract research organization (CRO) sources, generating massive but loosely structured research files to support scientific discovery of next-generation medicines.

Our client, a large BioTech firm, engaged our big data experts to find a solution to the burgeoning internal demand for this data that also facilitated sustainability. The increasing scale and complexity of their data significantly impeded data acquisition, slowing business momentum. Rapid, easy, and controlled access to data was a strategic imperative; it could not be compromised by the needs of traditional operating models nor technologies.

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5 Tips for Growing Your Big Data Capability

Nowadays, it’s hard to find an organization that isn’t using big data in some form or another. But while some organizations are capable of leveraging big data at the highest level of advanced analytics, others are struggling to evolve their big data initiatives into something more useful and competitive than basic reporting and proofs-of-concepts (POCs).

We at Knowledgent believe that advancing big data capabilities is critical for organizations to get the most value out of their data. After all, the higher your level of big data capability, the more effectively you are able to use data to your competitive advantage, and the greater your ROI on your big data investments.

Here are five tips to help you grow and improve your big data capability: Continue reading 5 Tips for Growing Your Big Data Capability

Case Study: How a Healthcare Payer realized $100M ROI on a Hadoop-Based Business Information Architecture

A major Healthcare Payer client was struggling to digest, evaluate and analyze the large data sets required to provide better care management to members. As a long-term objective, our client’s primary goal was clear: to operationalize the ability to quickly ingest data and provide analytics to help grow the business and increase innovation. The organization also sought opportunities to be more descriptive with physicians as related to ICD codes to ensure higher rates of accurate diagnoses.

Continue reading Case Study: How a Healthcare Payer realized $100M ROI on a Hadoop-Based Business Information Architecture