The journey of advanced analytics has been a long in development, with many hurdles along the way. Some of the most complicated aspects of data analytics that still remain today are data gathering technologies, data cleansing methods, and skill support for advanced analytics. It has taken years to come to the automated age of business […]
Building a Productive Organization with Artificial Intelligence
There’s plenty of research on employee productivity, which is key to building a profitable and successful business. Engaged employees are likely to put their heart into their jobs – not just go through the motions. Here are some findings that put this into perspective: Happy workers are 13 percent more productive, according to research by […]
Scaling the Analytics Team: Developing Key Roles
In an enterprise analytics team, different roles exist to fill different needs, and those needs must be met in order to be successful. Launching an analytics program doesn’t necessarily require a massive influx of personnel before producing usable insights from data, yet it’s important that critical roles are filled, whatever the size of the team. […]
Case Study: Tracking and Tracing Drugs in the Pharmaceutical Supply Chain
Failures or lack of visibility in the many-tiered pharmaceutical supply chain have multiple repercussions. Drug shortages have adverse economic and clinical effects on patients — they are more likely to have increased out-of-pocket costs, rates of drug errors, and, yes, mortality. Hospitals and health systems allocate over 8.6 million hours of additional labor hours to […]
Business Intelligence Meets Metadata Challenges
Many BI managers, CEOs, and CIOs cannot afford to add more staff, so they are seeking technologies that can help their existing teams operate more accurately and efficiently. They “need to change the physics, as we call it. They can’t just add more people to the team,” said Amnon Drori in a recent DATAVERSITY® interview. […]
Understanding DataOps
DataOps (data operations) has its roots in the Agile philosophy. It relies heavily on automation, and focuses on improving the speed and accuracy of computer processing, including analytics, data access, integration, and quality control. DataOps started as a system of best practices, but has gradually matured to a fully functional approach for handling data analytics. […]
Deep Learning and Analytics: What is the Intersection?
Emergent artificial intelligence (AI) technologies, especially the automated algorithms populating analytics platforms, are impacting and reshaping the world of business analytics. The underlying connections between traditional analytics processes and the disruptive technologies will make you cheer if you happen to be a data scientist or a business analyst — because your redefined role in the […]
Data Intelligence on the Edge
The term “edge intelligence,” also referred to as “intelligence on the edge,” describes a new phase in edge computing. Organizations are using edge intelligence to develop smarter factory floors, retail experiences, workspaces, buildings, and cities. The edge has become “intelligent” by way of analytics that were formerly limited to the cloud or in-house data centers. […]
Data-as-a-Service (DaaS): An Overview
As external data begins to gain importance in business analytics, data assumes a new role in global businesses. Now data is not only an organizational asset, but also a distinct revenue opportunity via data-related services offered under the umbrella term of “Data-as-a-Service” (DaaS). DaaS service providers are either replacing the traditional data analytics services or […]
Utilizing Business Intelligence with AI
Business intelligence (BI) is, in essence, new information that is not necessarily common knowledge and is sought to gain a competitive advantage over the competition. Business intelligence comes from a variety of sources, ranging from spies working for the competition to data mining. Contrary to the theme of several current articles, business intelligence is not […]