Contributor
Jelani Harper is an editorial consultant servicing the information technology market. He specializes in data-driven applications focused on semantic technologies, data governance, and analytics.
Long gone are the days when organizations were dependent on IT teams for Business Intelligence reporting. Back then, IT teams typically had to adjust data models to facilitate specific questions …
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In the hierarchy of data governance personnel, data stewards have traditionally had the least amount of influence in devising the policies that dictate how organizations govern their data. The Chief …
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The inexorable march of the enterprise to the cloud is underpinned by the multi-cloud tenet which, when involving hybrid clouds, enables organizations to seamlessly access resources between various clouds as …
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The similitude between the cloud’s most pronounced enterprise advantages and those of blockchain is too great to ignore. Both are credible means of storing data. They also excel at exchanging …
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Once, data science was an untamed, emergent discipline without rules, restrictions, or repercussions. Organizations simply wanted accurate advanced analytics; those fortunate enough to procure scarce data scientists gave them boundless …
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The inner workings of data science—much like that of multi-parameter, opaque machine learning models—have traditionally been an enigma to the average business user. While the latter simply desires accurate predictions …
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All data-driven processes are intrinsically binary. No matter what the application or use case might be, depending on data involves risks as well as potential gains. Reducing the former tends …
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With all the media attention focused on contemporary Artificial Intelligence applications of computer vision, conversational AI, and knowledge graphs, it’s easy to lose sight of the basic data management mainstays …
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An inordinate amount of some of the most vital aspects of Artificial Intelligence—from data engineering to data science, data preparation to machine learning—rely on one indispensable prerequisite: data modeling. Without …
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The dynamic software agents of Robotic Process Automation represent many things to the modern enterprise. They’re simultaneously a digital workforce of tireless, ubiquitous employees, a cogent means of actuating statistical …
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