Posts Tagged ‘data warehousing’

OK, maybe that’s an overstatement. But, it’s worth mentioning that President Barack Obama briefly talked about “precision medicine” in his State of the Union address last week. Here’s what he had to say: Twenty-first century businesses will rely on American science and technology, research and development. I want the country that eliminated polio and mapped […]

If you’re a Java developer, you probably know that you can create a thread by implementing the Runnable interface or by extending the Thread class. You can then execute multiple threads in parallel to achieve concurrency. Still with me? It gets a bit more challenging when you need to spawn long-running tasks in parallel and […]

  Throughout 2015, we should continue to see life sciences companies investing in technology to reduce drug and device development costs and time, and more importantly, to improve the safety and efficacy of their products. It’s no longer a choice, but rather a matter of time: life sciences companies need to upgrade their IT solutions […]

Last time, we concluded that the costs associated with hosting clinical trial software in the cloud can actually be less than for on-site solutions. In this post, we’ll tackle access to data and system uptime. Claim #4: Clinical or safety data stored in the cloud can be accessed at any time. Fact or fiction? Fact. […]

In our last “cloud fact or fiction” post, we discussed the cost of implementing clinical trial software in the cloud. This time around we’ll address the ongoing costs you can expect to see if you decide that hosting your applications in the cloud is the way to go. Claim #3: Ongoing costs for cloud/hosted clinical […]

I recently heard a segment on the radio about personalized medicine. Or “translational medicine.” Or “translational research.” Or “precision medicine.” Whatever you want to call it! Dr. Murray Feingold, a pediatrician and geneticist in the Boston area, painted a clear description of the term. He put it in words that all of us can understand. […]

Last time, I posted about how BI/DW accelerator and framework tools need to be used with care, and not as a substitute for solid requirements analysis. This time, I want to debunk a misconception that can be framed by the following question: Will Agile processes speed up my BI development timeline?   I see many situations […]

While big data is a catchy buzzword and many race to offer their own definition of it, many still struggle to understand what it really means and question its real value. According to a recent survey conducted by Talend, only 10% of respondents were engaged in a large scale big data implementation project, while 36% […]

In my last post, I wrote about BI’s reputation for being a long drawn-out process. And of course, where the market sees a vacuum…  A plethora of products and processes exist to aid with “shortcutting” BI/DW development. So this time, I want to look some common factors at play when you use the various types […]

This is Part I in a two part series on how Perficient helped to support ProHealth Care in operationalizing their BI program, data governance, and the Business Intelligence Competency Center. Here, I’ll focus on the workstreams and the road map. In Part II, I’ll cover the members of the data governance steering committee as well […]

A common complaint about data warehousing/BI has been time to market.   The investment in real months required to stand up analytics is just too large. Descriptions of the actual time required vary (depending on who you ask, and what their interests are) from a year to 24 months. The numbers are open to debate, but […]

Data science is a discipline conflating elements from various fields such as mathematics, machine learning, statistics, computer programming, data warehousing, pattern recognition, uncertainty modeling, computer science, high performance computing, visualization and others. According to Cathy O’Neil and Rachel Schutt, two luminaries in the field of Data Science, there are about seven disciplines that even data scientists in training […]