Skip to main content
Jelani Harper on Muck Rack

Jelani Harper

United States
As seen in: Flipboard, SearchDataManagement, VentureBeat, GigaOM, The Code Project, Tech Xplore, The New Stack, Data Science Central, SC Magazine UK, DATAVERSITY and
Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work. Claim your profile

Get in touch with Jelani

Contact Jelani, search articles and posts on X, monitor coverage, and track replies from one place.

Learn more about Muck Rack

Actions

Share this page

Is this you?

As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile

Articles

What a leadership transition reveals about your data strategy

|
By Jelani Harper
| SearchDataManagement
When a CDO departs, organizations often discover that their data strategy was little more than the vision of a single executive, never embedded in the organization's culture and fleeting in its efficacy. When that's the case, vendor relationships strain, governance initiatives stall and undocumented processes that existed only in the CDO's mental roadmap surface as gaps -- a pattern that plays out before, during and after a departure.
Open in Who Shared Issue with article?

Nuances of Build-or-Buy Decisions

|
By Jelani Harper
| Enterprise AI World Verified
The intricacies of the time-honored question of whether to build or buy take on new dimensions when it comes to enterprise AI. Organizations must not only account for traditional considerations like cost, time-to-market, and proof of concepts but also for those that are unique to advanced machine learning and language model deployments.
Open in Who Shared Issue with article?

The Multimodal World of Enterprise AI

|
By Jelani Harper
| Enterprise AI World Verified
Multimodal applications of AI are gaining credence throughout the enterprise at increasingly rapid rates—and for good reason. Firstly, they come close to realizing the full potential of foundation models and large language models (LLMs) which, by default, are multimodal. Although commonly deployed for textual use cases, several of these models are just as well-versed in image and video applications and, to a lesser extent, audio ones.
Open in Who Shared Issue with article?
See all 411 licensed articles (424 Total)