It’s going to take another step change in analytics capability to realize the trillions of dollars in value being tied to AI

Most of the analysis of AI Value Generation takes it for granted that AI will cross a pretty big chasm. A few years in, the technology has advanced but the techniques for using it are still lacking. Image by Riette Salzmann from Pixabay

Where does AI Value come from?

Classifying Problems using the Cynefin Framework


All you need is a Smart Bulb and an hour to automate the communication of your meeting status to your kids as Red/Green

High-level system architecture diagram for the Zoom->Smart Bulb Integration


It’s amazing how much a simple indicator can change the relationship with your kids while you’re working from home

Red Light means mommy / daddy is in a meeting, better be quiet and leave the door closed.

Kids Barging into your Zoom Meetings?


A lack of trust will dramatically impact your efforts to become data driven unless you proactively limit the spread of mistrust from data quality incidents.

Data Mistrust is already Endemic


A lack of trust will dramatically impact your efforts to become data driven unless you proactively limit the Blast Radius of data quality incidents.

Image Source: US Air Force (via Wikimedia)


Simple, highly effective, faded into the background of your life

If this is your general working life, then Krisp will make it better without getting in the way. Image Source: PxFuel

Two ways to learn about AI Product Design


Just like in chemistry, a data catalyst can dramatically speed up the rate at which your data ends up how you want it

Catalyzing the decomposition of (lots of) Hydrogen Peroxide created this massive foam blob. Photo courtesy of Vlog Squad. Original Video on YouTube.

Catalyzing a reaction accelerates it


A detailed look at the missing Data Owner role that keeps organizations from becoming data driven.

Your data & analytics team is probably running like a recycling plant

Image Source: US Air Force


Leveraging data tests and safe environments makes data quality an everyday activity for everyone who touches your data

Image Source: Pixbay

The cost of Bad Data


How your organization can adopt the (non-technical) practices in DataOps to improve Data Governance outcomes

Adopt an analytics lifecycle

Ryan Gross

Emerging Tech leader at Pariveda Solutions | Interested in how people & machines learn, and how to bring them together.

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