Healthcare Matters

Big data is being hyped everywhere these days –and for a change, healthcare is looking a lot more like an early adopter than a market laggard. Maybe because social media is considered such a big potential boon for healthcare (?) or is it more about the big new networks of care delivery being formed and the level of analytic “discovery” that is going to need to take place?

Of course, the answer is: “All of the above.”

Just how big is “big data?” Well, no one has yet proffered a definitive answer, but it’s safe to assume that when scaling your traditional data warehousing solution is not looking too smart (from most everyone’s perspective) and/or, for example, your ability to automatically parse/collect data from newer online sources garners chuckles from your IT department, you’re probably in the neighborhood. According to Business Intelligence (BI() analyst Jorge Garcia, big data has three main features:

• Volume. Volume is the first and most notorious feature. It refers to the amount of data to be handled. Many organizations are producing large amounts of data internally, or gathering other large amounts of data from the exterior.
• Variety. The variety of data that organizations collect has increased in several ways: there are more internal systems having (primarily structured) data collected from them, and there is the rise of internal and external sources of data from semi- or non-structured social media sources, such as blog’s and tweets, as well as data coming from sensors and even plain-text documents.
• Velocity. As with traditional types of solutions (e.g., the data warehouse), latency periods are being reduced. Information is often sensitive and needs to be used and moved according to certain time frame’s to obtain the best possible value from it. Real-time or near real-time answers are common needs in modern organizations.

Why the Hype? New tools are changing the traditional BI data cycle. Data can be collected from its sources and analyzed in a matter of seconds, giving reliable results in a fraction of the time required by traditional systems. The level of automation for collecting data of different formats and types (structured, semi-structured, non-structured, etc.) and then reading and analyzing them to reduce or automate decision making processes, including the ability to build scenarios for testing or optimization purposes, is becoming commonplace.

• And open source solutions—such as No SQL—have played an important role in the big data movement, by forcing market prices to stay down. Open source solutions should not be overlooked.

We can distinguish two major categories in the big data space.

Big Data File and Database Management Systems

Big Data Analytics Appliances

Big data has had a rapid uptake by traditional BI vendors. Some of them offer connectors to big data applications in order to be able to analyze the data. A few of these vendors are Pentaho, Tableau Software, Endeca (acquired by Oracle), Jaspersoft, and MicroStrategy.

A big data solution involves the complete data life cycle, from data collection to its visual representation. Organizations that succeed in the deployment of these sorts of solutions are the ones that are able to identify the type of data to be managed, the process the data needs to undergo, and the nature of the information to be obtained. Providers in healthcare, especially as their supply chains expand and become more integrated, are going to find competitive advantage in big data –if they know where to look.

Source: TEC

—Tom Finn