Higher education institutions are some of the most data-rich entities in the world. Postsecondary leaders need high-quality, consistent and accurate insights to make the best decisions for their institution, students and constituents. Data governance is a topic that may seem technical in nature and perhaps important to only the IT
By now you’ve seen the headlines and the hype proclaiming data as the new oil. The well-meaning intent of these proclamations is to cast data in the role of primary economic driver for the 21st century, just as oil was for the 20th century. As analogies go, it’s not too
In a recent presentation, Jill Dyche, VP of SAS Best Practices gave two great quotes: "Map strategy to data" and "strategy drives analytics drives data." In other words, don't wait for your data to be perfect before you invest in analytics. Don't get me wrong -- I fully understand and
In my last post I described "4 adaptability attributes for analytical success," and in the past I've discussed the strategic role analytics play in helping organizations succeed now and into the future. Now I'd like to discuss three attributes that define a powerful analytics environment: Speed Accuracy Scalability [NOTE: Any
The “big” part of big data is about enabling insights that were previously indiscernible. It's about uncovering small differences that make a big difference in domains as widespread as health care, public health, marketing and business process optimization, law enforcement and cybersecurity – and even the detection of new subatomic particles.
“Garbage in, garbage out” is more than a catchphrase – it’s the unfortunate reality in many analytics initiatives. For most analytical applications, the biggest problem lies not in the predictive modeling, but in gathering and preparing data for analysis. When the analytics seems to be underperforming, the problem almost invariably
After doing some recent research with IDC®, I got to thinking again about the reasons that organizations of all sizes in all industries are so slow at adopting analytics as part of their ‘business as usual’ operations. While I have no hard statistics on who is and who isn’t adopting
In my last blog I detailed the four primary steps within the analytical lifecycle. The first and most time consuming step is data preparation. Many consider the term “Big Data” overhyped, and certainly overused. But there is no doubt that the explosion of new data is turning the insurance business
Data Management has been the foundational building block supporting major business analytics initiatives from day one. Not only is it highly relevant, it is absolutely critical to the success of all business analytics projects. Emerging big data platforms such as Hadoop and in-memory databases are disrupting traditional data architecture in
It is clear from many of the comments arising from this year’s Insurance Times Broker Service Survey that brokers value underwriters who are open-minded and willing to adapt wordings and terms where possible to accommodate clients’ individual needs. They also value a close dialogue and partnership with underwriters who are
