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
Most of our conversations about information management and other data-focused topics touch on data governance (specifically, what good data governance is and how to leverage it). This may seem like a good place to start; after all, if you’re trying to get the most value out of your data, you want the data to be clean, accurate, and accessible.
However, at Knowledgent, we like to look at things from another angle and ask a different question: Why data governance?
Continue reading Video: Why Data Governance?
Knowledgent strongly believes all companies have the data required to know their customers a whole lot better. But who out there is developing the necessary customer insights to make an impact on their business? Is Big Data the solution to developing some of those insights? The hype tells us it’ll be just that. But will Big Data play all by itself at the deep end of the pool, or will it need a helping hand? The clear answer is that synergistic technologies are the key.
Continue reading Big Data Enrichment with MDM
Since there is such an extreme amount of data available in a Big Data platform, it is important to understand the situational relevance of certain types of data needed to drive business value. Understanding and managing the semantics of the data is centrally important for optimizing its relevance.
Continue reading Big Data Semantics & Search
In this video, Informationist Frank Norman discusses the opportunities to leverage big data in healthcare.
Can you think of other ways healthcare organizations can leverage big data? Let us know in the comments!
Many organizations approach Master Data Management (MDM) by taking an inventory of the data in their source systems, defining policies to improve the quality and usefulness of that data, and building a consolidated hub of that data. This “build it and they will come” approach too often results in an MDM hub that fails to meet the needs of the processes that want to consume that data.
Continue reading How Knowledgent Approaches MDM