Without a doubt, data integration is essential to the success of big data projects. However, some folks in the big data vendor community, including data warehouse, Hadoop and data integration vendors, are telling a very confusing story about the fitness of Hadoop as a data integration platform.
On January 9, 2014 IBM announced that it was forming a new organization (the Watson Group) and investing a billion dollars ($1B!) in future Watson development. The company also announced three new Watson cloud services—The Watson Discovery Advisor, Watson Analytics and IBM Watson Explorer—as well
On day two of HIMSS14, I had the pleasure of listening to leaders from UPMC, MD Anderson and Amedisys share their stories about how their organizations are turning information into an asset. At the third annual IBM Big Data & Analytics luncheon, attendees from across the healthcare ecosystem
When IBM announced innovations in information integration and governance for big data last fall, we IBMers believed we were on to something. Experience with clients worldwide suggested that automated integration, enabling self-service integration for big data repositories, would be a big deal. A
When an organization sets out to become more customer-centric, lots of changes have to happen. Employees—from senior executives to the frontline—must change and adopt new behaviors and mindsets. Processes and technologies must change to reflect the company’s customer-centric desires. Large-scale
HIMSS14 attendees are in for a treat this year; in addition to the amazing educational sessions and exhibits, visitors will have the opportunity to an exciting story about real-time analytics for research and data quality. Dr Ray Duncan, CTO for Cedars-Sinai Medical Center in Los Angeles, and Dr
Is big data just a buzzword? I say no way! More than 80 percent of the world’s data was created in just the last two years: video, email and social media just to name a few. This data explosion is not lost on healthcare. Beyond the digitization of transactional and clinical data in medical records
The amount of data created is growing rapidly and it is expected that in 2020 we will create a minimum of 40 trillion gigabytes; 40 percent of all this data is expected to come from sensors or machine-to-machine data. All of this data will significantly impact global industries, from creating
In my last blog post I shared some of the background on the December ONC Patient Identification and Matching Stakeholder meeting, as well as barriers explored during the meeting. Lively debate erupted around some findings, with a few participants feeling that the whole discussion was going down the
In today’s increasingly connected world, machine data analysis is becoming a business imperative. While managing it may be challenging, opportunities abound across multiple industries for those who can tackle this complex data.
Using a powerful big data platform from IBM, Vanderbilt University School of Medicine clinicians cut research timelines from nearly a year to only a few weeks to help accelerate the pace of discovery and, ultimately, improve patient health.
"Don't we already have a data warehouse solution?"
"Is big data even relevant to our organization?"
"Why do we need it?"
"Isn't big data costly and hard to implement?"
There is an obvious disconnect between the C-Suite and big data initiatives. Given today’s competitive market it’s hard to
The December 16, 2013 ONC Stakeholder meeting addressing patient identification and matching could best be summed up by a statement made early in the day’s discussions by Dr Scott Schumacher, chief scientist for MDM at IBM: “We don’t have an algorithm issue, we have a data quality issue.” As the