What’s Next for Big Data in Healthcare

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“Big Data will leave no sector untouched as it continues to change the way we think about everything from sales to human resources, and medicine and healthcare are no different,” writes Bernard Marr for Forbes.

Handling data is nothing new to the healthcare industry.  But, in recent years, increased abilities to share and access data plus new data from sensors and wearables has created not only more data but better data according to Mr. Marr.  In his article he outlines several ways big data will make an impact:

Prevention.  Mr. Marr writes, “smartphones and other popular smart devices including Jawbone, Fitbit and others, now have the capacity to help people track their progress towards a healthier lifestyle. Apps and devices to help track and monitor physical fitness but also chronic ailments like diabetes, Parkinson’s and heart disease are also being developed.”  Not only do these devices track more data but this data can be more reliable than traditional patient led tracking and reporting methods.

Diagnosis. Improvements are being made to how big data is stored and shared in the healthcare industry with the goal of  bringing medical providers more access. Systems, such as IBM’s Watson, are also looking at test results, recognizing patterns and learning in order to aid in diagnostics and improve early detection.

Treatment.  To get to more personalized medicine and better patient  treatments you first have to start big, as in big data.  The results of big data analytics, predictive modeling and new systems crunching vast amounts of information will help to better inform doctors about the needs of each patient.

Big data is definitely a “game changer” for the healthcare industry both now and in the future.

Survey Says: Big Data

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Big data management remains a topic at the table for most IT teams. Whether you are preparing a project, in the middle or on to that “next step”, utilizing data – structured or unstructured – to form actionable insights is key to your company’s long term viability and success. Today, let’s look at an article by Thor Olavsrud on CIO that covers a recent big data survey of enterprise executives.  What do the executives feel is working?  What challenges do even enterprise-sized businesses face?

 

First, what is working?

  • Strategy – 94% of the executives surveyed are confident their big data strategy is headed in the right direction
  • Motivation – 98% of the executives believe they rightfully encourage their employees to ground business decisions in “data and evidence”
  • Investment – 81% of those surveyed will increase their investments in talent, tools and technologies that will help the company leverage big data

What are the challenges?

  • Data Silos – 41% still report that the data their companies have is too siloed to be easily accessed
  • Access – 37% of survey respondents find it can take one day or more to access big data sources to analyze
  • Legacy Systems – 59% of executives surveyed find their data storage systems require too much processing time to meet today’s requirements

This survey demonstrates the importance of expanding your big data planning discussions to consider the operations and the daily management.  What are the potential  pain points  when accessing or using the data?  Do current systems or processes limit in any way and what is the solution and what can be done to overcome?  Big data management includes not only the end user capabilities but also those in the middle managing the operation and the systems already in place (or needed) to support.

CIO Big Data Obstacles

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“Most CIOs and other senior IT executives believe their companies are not prepared to make full use of the waves of data coming into their organization” Bain Insights leaders Steve Berez, Paul Callahan and Rasmus Wegener report for Forbes.

Big data, when accessible, can lead to more meaningful and actionable insights, but there is also the management and processing of that data behind-the-scenes and that is the place where many companies feel they are not quite ready.  Bain Insights finds that consolidating and cleaning data, simplifying access and rights management and improving access to external data sources are all commonly cited by CIOs as big data obstacles.  These are pretty specific but there are also cultural obstacles that are playing a role and sometimes even preventing some companies from working towards using big data.

Here are the culture or mindset obstacles that companies face with big data as identified by Bain Insights:

  • Owners of the data (business) and stewards of the data (IT) still make decisions with little interaction or understanding of the other group’s needs
  • IT focuses on storing and securing data versus focusing on getting data to the right hands for gaining insights
  • The company continues to apply old processes to new challenges and needs

How to overcome? One recommendation is to form closer relationships between business and technology teams. Once a relationship is established, balance business priorities with the technology investments that help productivity long-term.  DataOps is the term Bain Insights uses, “a DataOps mentality focuses the organization on improving the way that business leaders, data scientists and IT managers work together to discover insights.”

Share what big data obstacles your company faces? Does your company also have to make a mindset shift in order to capitalize on big data?

Big Data Predictions

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Bernard Marr compiles some of the top big data predictions for the year from leading analysts and firms in a recent Forbes article. Let’s take a look at those today.

  • Big data growth. Mr. Marr writes, “There’s absolutely no question that we will continue generating larger and larger volumes of data, especially considering that the number of handheld devices and Internet-connected devices is expected to grow exponentially.”
  • New tools for analyses. Emerging tools like Spark will compliment SQL
  • Decision making. Data analysis leading to real-time decisions will continue to be important
  • Machine learning. Gartner reported this as a top strategic trend for 2016
  • Privacy. Mr. Marr cites a Gartner report, which predicts by 2018 50% of business ethics violations will be related to data. This makes managing privacy controls and procedures a top concern for businesses
  • Staffing. A shortage of the types of workers needed to handle big data – from scientists and analysts to architects –  will continue
  • Data-as-a-service. Mr. Marr finds that Forrester is predicting that more companies will attempt to monetize their data
  • Cognitive computing. We see this word popping up more and more in the media and Mr. Marr believes businesses will start to realize its a natural fit with analytics
  • Data, data. “All companies are data businesses now” this statement is from Forrester and relates to the fact that more and more businesses are looking for ways to capitalize on their data

Mr Marr shares these closing thoughts, “Only time will tell which of these predictions will come to pass and which will merely pass into obscurity.” He points out that the key take away here is that big data is here to stay and will continue to grow.

Share your own thoughts on these big data predictions and what is happening in your company.

Super Bowl, Super Data

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With Super Bowl 50 played and the Denver Broncos enjoying their victory, today let’s take a look at the tech side of things. In particular, how big data and wearables are making an impact on football.  Bernard Marr breaks down the different ways football can use big data to gain new insights in a recent Forbes article:

 

Real-time data

From sensors in stadiums, helmets and pads, coaching staff can get access to real-time position data. Mr. Marr points out, “[data] can even help indicate when a player may have suffered a damaging hit to the head.”  NFL has given coaches access to tablets during the game to process data and plays.

Predicting Outcomes

Mr. Marr writes, “For the biggest football game of the year — and the biggest sporting event of any kind in the U.S. — you can bet that people are betting on their ability to predict the outcome of the game.”  As more data is collected people have moved to better computer algorithms for predicting game results. On the game side, big data and wearables can even help predict how weather conditions may affect a play.

Advertising

A Super Bowl article that doesn’t mention advertising would not be considered complete. As the cost for a 30 second television ad spot continues to rise – Mr. Marr reports this year’s costs was $5 million per 30 second spot – marketers are turning to better data analytics and the increased abilities to use social data to make better use of their ad spend.

So next year when you tune into your favorite NFL team, remember big data is making an impact on the big game.

2016: Predictions for Big Data

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As we approach the final month of 2015, let’s take a look at what is in the news for big data trends.

Growth through 2019

Thor Olavsrud reports for CIO that “the market for big data technology and services will grow at a compound annual growth rate (CAGR) of 23 percent through 2019” according to IDC. IDC looks at growth in big data infrastructure, software and services and finds that software, which includes information management, discovery and analytics and app software, will grow the most, by 26% in the next five years.  Also, growth in professional and support services will account for half of all big data spending through 2019.

Industry Growth

Mr. Olavsrud’s article also takes a look at big data trends by industry. IDC found that top spenders on big data technology and services to-date are:

  • Discrete manufacturing
  • Banking
  • Process manufacturing

In the coming years IDC expects fast growth in the securities and investment, banking and media sectors. According to a Forbes article by Louis Columbus the top five industries for hiring big data professionals are (the percentage represent the number of total advertised positions in the market):

  • Professional, Scientific & Technical Services – 30%
  • Information Technologies – 19%
  • Manufacturing – 18%
  • Finance and Insurance – 10%
  • Retail Trade – 8%

You can see manufacturing and finance not only emerging as large drivers of  big data spending but also big data hiring.

In other industry news, big data will continue to play a role in the medical industry. Paddy Padmanabhan reports for IBM Big Data Hub current big data trends in healthcare include using analytics and data for disease detection and prevention, prevention of system fraud and abuse and improved population health management. In the news, you can also see the term precision medicine more regularly as well as new partnerships developing in the industry that incorporate big data into every day medicine and research.

Overall, big data growth is expected to be strong. Analysts believe that the market will begin to mature in the coming years but big data will continue to be a key element for company’s to remain competitive.

Big Data in 2016: Hadoop

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Ken Hess of ZDNet reports on the results of a recent big data trends survey that focused on Hadoop use. The survey asked 250 data architects, IT managers, developers, BI and data analysts and data scientists on what they expect in 2016.

The overall theme of the survey results writes Mr. Hess is, “the move away from Hadoop experimentation into full production with big data analytics.”  The big “three” trends identified in his article were:

  • Apache Spark production deployments
  • Conversion from other platforms to Hadoop
  • Leveraging Hadoop for advanced use cases

70% of respondents were interested in Apache Spark. Mr. Hess explains, “The two primary factors in this interest in Spark is that it is easy to deploy and its speed.” The conversion from older platforms to Hadoop is also interesting. When asked what they expect to gain from switching to Hadoop the respondents cited the following:

  • 63% expect Hadoop to increase business and IT agility
  • 55% expect to improve operations and reduce costs
  • 51% expect it to allow them to give business users more access

Also, Mr. Hess reports, “More than half the respondents view Hadoop as a way to innovate by using social media data and data from IoT sources.”  One of Hadoop’s strengths is its ability to bring data together. Companies used to struggle with just combining internal data that was often in siloes. In today’s world, companies must also find ways to combine and process external data with their internal information and that is where Hadoop  can come in to help.

As January winds down, what does your team hope to accomplish on the big data front in 2016 and what tools are you most interested in learning more about?

Big Data Analytics Trends for 2016

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Today let’s look at what is in the news for big data analytics trends and what industry leaders are predicting for 2016.

First, David Weldon of Information Management writes, “Data analytics remained one of the most important areas of technology investment throughout 2015, and industry analysts agree the same will hold true in 2016.”

Big data trends from his article are:

  • More businesses will seek out value in all data
  • Platforms that support “data in motion” will evolve
  • Demand for “big data made easy” will drive platforms to simplify
  • Hadoop will be used for more enterprise critical workloads

Venture Beat reports the growth in machine learning will be a key driver in the big data industry, “Machine analytics will be the fastest growing area of big data, which will have CAGR greater than 1000%. As digital transformation grows, so does the reliance on new software and architectures. Today, software is not only driving business processes, but entire business models, and the need to manage, monitor, and troubleshoot applications in real-time has never been more critical. Thus, the need for speed, full-stack visibility, and agility — all in real-time — is the true business demand underpinning the growth of machine data analytics.” Machine learning will drive changes in DevOps, bring to light the importance of log management and new software-based architectures will grow that better utilize the processing power of public and private clouds. Finally, business intelligence will change from “rear-window” analytics to continuous big data analytics in real-time.

Hema Reddy of IBM’s Big Data Hub writes, “Big data is the world’s newest natural resource. The value of big data is self-evident, and the need for powerful analytics capable of delivering that value is pressing in the business environment. Business leaders no longer question whether value is to be found in data; instead, they wish only to learn how to extract that value to understand their customers and meet critical business needs.”  In 2016 companies will continue to look for platforms that allow them to extract value from analytics including rich media such as video and images. Predictive analytics will continue to be important as a means to drive efficiency and finally big data growth in the cloud will continue.

Data is everywhere and in 2016 more companies will find better ways to capture it and analyze it to drive innovation.

The Enterprise Mainframe and Big Data

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So what is next for the mainframe? Ok, maybe you haven’t asked yourself that in awhile or perhaps you didn’t think it was necessary, but according to Ken Hess of ZDNet big data may be in its future.

Mr. Hess examines a survey of IT pros. He writes, “Based on the survey results, the mainframe may be the key to closing the big data processing gap and supporting the latest data delivery technologies. Over 89 percent of respondents indicated that mainframe’s key benefit in the next year is its Big Data processing horsepower through CICS, DB2 and WebSphere, and more than a third see it as an opportunity to provide data to big data platforms such as IDAA, Netezza, Splunk, Spark, Oracle, Teradata and Hadoop.”  Key findings from the survey include:

  • 69% of respondents ranked the use of the mainframe for large-scale transactions as “very important”
  • 79% still analyze real-time transactional data from the mainframe with a tool that is also on the mainframe, but survey respondents are also using outside tools such as Hadoop (8.6%)

The survey also asked about the strengths of using a mainframe for analysis:

  • 67% pointed out that a key strength of the mainframe is its ability to integrate with other platforms
  • 82% felt the mainframe provides good security
  • 83% of respondents also cited availability as a key strength

Mr. Hess further points out that companies like IBM are also launching systems that help mainframes connect and utilize outside big data analysis tools like Hadoop.

So when you think big data, do you also think about your mainframe?  This article further underlines the importance of a thorough evaluation of your company’s unique resources and systems against outside options in order to develope a big data solution that will meet your needs.

Big Data Put into Practice: Patient Care & Costs

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Greg Freiherr writes for CIO, “Mining massive collections of patient data has healthcare poised to improve patient outcomes while holding down costs.”  Today let’s look at two real-life uses of big data in the healthcare industry that improve patient care and costs.

The work of data scientists at Penn Medicine in Philadelphia was highlighted by Ken Terry on CIO.  Penn Medicine has data in the amounts of petabytes and it is using big data tools to analyze and create better care pathways. The team not only sets out new pathway ideas, but also tests with patients and “feeds” the results back into their algorithms to learn and recalculate. Mr. Terry reports that so far the team has improved the hospital’s ability to predict what patients are at a high risk of developing sepsis.  The team can identify patients a full 24 hours sooner than it could prior to using big data methods.

Jessica Davis reports for Information Week that Blue Cross Blue Shield (BCBS) is using big data to tackle healthcare quality and costs, “the Axis big data initiative at Blue Cross Blue Shield Association incorporates more than $350 billion in annual claims, 36 million provider records, and more than 700,000 BCBS patient reviews, all with the goal of helping healthcare consumers make informed decisions.” Axis will be a reference tool that allows consumers to compare costs by geography but also goes one step further and looks at the costs of pre-procedure and follow ups – providing a “total cost price reference.”  All 36 BCBS members are now contributing data making it the only healthcare system to have data from every ZIP code in the U.S.

The Penn Medicine example focused on patient care and Blue Cross Blue Shield focused on evaluating costs are two examples of the power of big data to benefit the healthcare industry in numerous ways.