Now introducing the “Insight Ops” model. This new model will embrace and enable an agile environment for discovery and exploration and manage the transition necessary to deploy the insight to make it actionable.
The transition to a modern business intelligence and analytics platform helps create value by getting deeper insights from diverse data sources. But how can organizations make this transition? By focusing on four important areas.
Predictive analytics provides real-time insights into your customers, employees and processes, fueling better decisions throughout your business. This presentation gives an overview of how predictive analytics can strengthen four key areas of your business for improved performance and competitive
Smart predictions can spell the difference between whether your company succeeds wildly or falls by the wayside. Get the details on four strategic pillars for smart, proactive business through predictive analytics deployment in a series of new blog perspectives.
Big data can empower consumers and organizations alike, but is your organization taking advantage of real-time data analytics? Learn how data analysis tools are increasingly putting analytics in the hands of users.
The number of anticipated Baby Boomer retirees will surely be accompanied by a corresponding rise in healthcare costs—which will affect professionals and patients in a big way. Applying a preventative big data solution can help avoid these growing pains.
A recent healthcare information research event explored the role of master data management in supporting research, care coordination and health information exchange. Take a look at the interaction that transpired and validates the importance of matching patient data to clinical records.
Large municipalities need to be ever vigilant in providing essential health, safety, security, social, traffic and other services. What better way to glean their citizens’ sentiments on these matters than capitalizing on social media data channels such as Twitter?
Financial services and banking are data-driven. Organizations in these industries store and analyze data on millions of customers, this data valued in the billions. As a consequence, they have to struggle with ever increasing volumes, velocity and variety of data. To stay ahead of competition, and