Guest Article: OLAP remains a great healthcare analytics architecture, even in the Big Data era

I’ve been getting many questions these days about big data tools and solutions, especially their role in healthcare analytics. I think that unless you’re doing large scale analysis of biomedical data such as genomics, it’s probably best to stick with traditional tried and true analytics tools. Online Analytics Processing (OLAP) can be invaluable for medical facilities to use when interpreting data and health informatics because most of that data is in relational, key-value, or hiearchical databases (such as MUMPS). I reached out to Ron Vatalaro, who works with the University of South Florida Morsani College of Medicine and writes about health informatics, to summarize which commercial tools are good to consider for modern OLAP architectures. Here’s what he said: Online Analytic Processing (OLAP) is used in computing to quickly respond to multi-dimensional analytical queries. It is a subset of business intelligence, which also includes report writing, relational database, and data mining. OLAP tools make it easy to analyze data from multiple perspectives through one of its following three basic operations: consolidation (roll-up), drill-down, and slicing and dicing. OLAP and data warehousing are interacting with and shaping health informatics by allowing for new analytical opportunities, in addition to the customary statistical approaches. It is one thing to collect vast amounts of data, but gaining insights as to how to best use the data to save lives...
Source: The Healthcare IT Guy - Category: Technology Consultants Authors: Tags: Uncategorized Source Type: blogs