Health Information Governance Strategies for Unstructured Data

Information governance becomes particularly important when exploring the use of unstructured data for healthcare analytics. While electronic health records still have the potential to standardize care by enabling advanced analytics and informing clinical decision-making, much of the data held within these systems – and a large proportion of the data used in conjunction with these [...]

How Cloud Governance Can Provide Cost Saving Benefits

How Cloud Governance Can Provide Cost Saving Benefits - Enterprise cloud computing has transformed IT. Cloud computing decreases time-to-market, improves agility by allowing businesses to adapt quickly to changing market demands, and, ultimately, drives down costs. For many CIOs/CISOs, this raises significant concerns regarding governance: Compliance: IT's visibility as to the location of corporate data [...]

By |CIO, cloud, cloud computing, governance|

Top 4 Machine Learning Use Cases for Healthcare Providers

Machine learning is generating a lot of excitement amongst healthcare providers, but what are some of the top use cases for these advanced analytics tools? Here are some of the top initiatives and most intriguing research projects that are currently harnessing these tools. Imaging analytics and pathology Improving imaging analytics and pathology with machine learning [...]

Mini-glossary: Big data terms you should know

When it comes to assembling a list of key big data terms, it makes sense to identify terms that everyone needs to know — whether they are highly technical big data practitioners, or corporate executives who confine their big data interests to dashboard reports. These 20 big data terms hit the mark. Analytics The discipline [...]

By |Analytics, Big Data|

How (and whether) to implement machine learning in your organization

Machine learning is making substantial impacts on businesses around the world, but many organizations struggle to understand where and when to optimally use ML. To enable successful deployments, businesses must first recognize which problems are most amenable to ML and, second, ensure the right processes are in place to evaluate its impact. In general, ML [...]

By |Machine Learning|

Tips for Improved Cybersecurity in Healthcare

It is no surprise that healthcare organizations have been a target of cyber attacks for a while now. Each year, these attacks are not only increasing in numbers, but they are also becoming more complicated and difficult to predict. Health systems are subject to various types of cyber attack, including ransomware, phishing schemes, and encrypted [...]

By |Healthcare|

Difference between Cognitive Computing and AI

Both AI and Cognitive Computing may look extremely alike, but like we mentioned above there is a small difference between both methods. Firstly, artificial intelligence does not work at mimicking human thought processes. The concept behind AI is to not mimic human thought and processes, but to solve a problem through the use of the [...]

Financial Firms Embrace Predictive Analytics

Four growing use cases where predictive analytics maps to return on investment (ROI) and risk management objectives include: Optimizing capital deployed. A deeper understanding of the link between portfolio risk/reward models and the impact of events on capital at risk and market liquidity can help market participants anticipate volatility and exposures under various scenarios.  Without [...]

Data Mining vs. Predictive Analytics – Are They the Same?

Predictive analytics is currently one of the most important Big Data trends. But both predictive analytics and data mining attempt to make predictions about possible events in the future with the help of data models. What are the differences between them? “Data mining is an interdisciplinary subfield of computer science. It is the computational process [...]