Perhaps one the single most significant changes to the analytics landscape in recent years had been the emergence of the data scientist. This role is continuing to evolve, with many organizations still in the process of establishing how best to incorporate this relatively new discipline into their
The data lake can be considered the consolidation point for all of the data which is of value for use across different aspects of the enterprise. There is a significant range of the different types of potential data repositories that are likely to be part of a typical data lake.
One thing that a recent event in Beijing, China confirmed is there’s no shortage of interest in machine learning for developers in that region. Take a look at snapshots of event highlights featuring rich content on artificial intelligence, cognitive capabilities, machine learning and more presented
Historically, Master Data Management (MDM) projects have focused on creating a single view of the truth that can be consumed by business processes. Learn more about how the evolving need to utilize MDM serves as catalyst for a new solution extension offering a managed data preparation and data
Ubiquitous data is so easily generated, and for that reason many enterprises today are exceedingly challenged to handle it all successfully. Take a look at a comprehensive information lifecycle governance solution that can help prevent enterprises from becoming submerged in their own sea of data.
The application of analytics and capturing information inside business documents can lead to all sorts of information for running smarter, faster and highly competitive businesses. Take a look at a few examples of how a workflow can dramatically change where and how information is collected and
By using predictive analytics, providers can use real-time data to see risk factors that previously went undetected. Armed with this information, healthcare systems can then intervene and hopefully change the course of the patient's future health.
Determining the total cost of care for a patient is not an easy task. By using big data in healthcare, however, providers can accurately determine the overall cost and use this insight to provide higher quality service at a lower price tag.
By remotely monitoring patients, doctors can reduce costly visits while still providing top-quality care for their patients. Real-time analytics allows doctors to immediately spot problems and intervene, even before patients know something is wrong.
It's no secret that there are wasted resources in the healthcare system, but it can often be hard to find areas where small changes can result in big savings. With data analytics, however, providers can find cost-saving measures that also improve the quality of patient care.