Using big data to improve health outcomes has rapidly become a prevalent trend in the healthcare industry; in fact, most healthcare organizations are already doing it. However, the promise of big data has only recently been considered for treating Alzheimer’s.
Chris Young, Life Sciences Partner with Knowledgent, will be presenting on current efforts to apply big data solutions to support the efforts towards finding a cure, early detection, and care delivery innovations for Alzheimer’s at Bio-IT World at the Seaport World Trade Center in Boston, Massachusetts. His session, “Big Data Agenda to Tackle Alzheimer’s,” will take place in the Vendor Theater on the expo floor on Wednesday, April 30 from 3:20pm – 3:40pm.
Prior to the event, Chris shared his insights on the potential of big data specific to Alzheimer’s:
Continue reading Q&A: Chris Young on Alzheimer’s and the Big Data Opportunity
With the rise of Hadoop, the demise of the data warehouse seemed only a matter of time. Surprisingly (or not), that’s not the case. Instead, organizations are looking to augment their current enterprise data warehousing solutions with the analytics and cheaper storage that Hadoop brings.
Continue reading Infographic: Offloading “Cold” Data from DW to Hadoop
As discussed in my previous blog, data in Hadoop is mainly accessed via programming languages such as MapReduce or Python, a scripting language like Pig, or an SQL-like language (Hive). However, the skillset for data analysis most prevalent in IT shops is SQL, which means that Hadoop will have to support a SQL interface in some capacity to appeal to these people and to the widespread BI tools in existence. However, Hadoop was created to process data in a “batch” mode – you submit jobs to analyze massive datasets stored in HDFS. A number of initiatives and solutions are underway that are focused on marrying SQL with Hadoop. This convergence is truly in progress.
Continue reading Taking Hadoop Mainstream: The Convergence of SQL and Hadoop