The External Data Management Platform. We enable Enterprises to harness the vast ecosystem of external data and deliver business value through its use. We do this by helping data teams manage all their external data at scale with effortless and powerful orchestration of tailored pipelines of trusted external data. Drive your business at scale with external data you trust, improving data ROI with robust and lower cost deployment and management of external data.
External link for Demyst
149 E 23rd Street
Suite 2035
New York, New York 10010, US
146 Arthur Street
Suite 902 (Level 9)
North Sydney, NSW 2060, AU
9 Raffles Place, Republic Plaza
#26-01
Singapore, SG
Mark Hookey and Brenden Grace discussing the complexity of data operationalisation. A key focus at Demyst.
Why haven't we seen a Cambrian explosion in data enabled success? Why are enterprises "slow"? There's a lot of complexity to navigate to really empower centralized platforms with rich data. It's getting better but the devil in data operationalization is still in the detail.
Demyst supports open standards in data governance through an API first approach https://docs.demyst.com/
My strong view is a "no loss" regulatory move is far greater mandated interoperability. Watch here to see more discussion with Brenden Grace and I.
Mark Hookey and Brenden Grace sharing thoughts on the difference between work and creative work
Figma recently pulled it's tools under criticism that it indirectly copy's Apple's designs. This triggers the broader question of the distinction between work and creative work. And the question of whether generative AI is just glorified autocomplete, or whether humans are in fact just glorified autocomplete. Humans do something that GenAI just doesn't; we try new things and test them against a mental model of what the response will be, rather than revert to the norm of what has happened before. It's useful to think about what business problems are "just work", versus what involves some level of creativity, and how best to harness newer tools to do work (and to test the counterfactual of a creative hypothesis).
Hear Mark Hookey and Brenden Grace discuss the increasing complexity of harnessing internal data. Does it need to be this way?
The compounding complexity of harnessing internal data. One of the many promises of emerging AI is to get our data house in order but it adds yet another lineage issue to track and understand, how was the data changed? How is it being used?
Demyst is focused heavily in GenAI, not because we have any unique GenAI algorithms, but because it's a key growing area of demand for external data. However GenAI programs are often stuck in large enterprises at the ideation phase, because of data blockers. We can help.
Data is posing the greatest challenge to adoption of GenAI among the "high performers" (70%). No doubt similar for traditional / predictive AI. https://lnkd.in/gC9UPJgE
Demyst reposted this
My strong view is a "no loss" regulatory move is far greater mandated interoperability. Watch here to see more discussion with Brenden Grace and I.
Mark Hookey and Brenden Grace discussing whether data is becoming decentralized. We think it's more interesting than the presidential debate.
Is every team becoming a data team? Does federation accelerate progress? Is it even possible given a large and growing set of governance requirements? Data's "easy button" is still coming ...
Demyst reposted this
Mark Hookey discussing whether external data is at a tipping point
Contrasting the compounding complexity of internal data vs external with Brenden Grace. Are we at the tipping point?