▲ | datax2 3 days ago | ||||||||||||||||||||||
Well written. Coming out of college years ago Gartner was a whole section of review during my business courses. Working with Data for years now I have become hyper sensitive to this keyword grift; Big data, Data lake, Datalakehouse, realtime-analytics, no-code, data model, data schema...etc. People lean so hard on certain words as if they mean they are doing something different or unique. You work in one product in your company, then you bring someone who has experience in another product and they remark "But product X cannot do XYZGrift" but it can, people hang on these keywords as though they are platform actions or enablement that exist only there. Rambling, but to get to the point, AI in general will strip this SEO/Marketing/Boomer catch phrasing, and build the common language which I appreciate greatly. I can go to ChatGPT or Claude and ask it I want to Foo this Bar with these filters, doesn't matter if its SQL, Python, Unix, Alteryx, Tableau... whatever, it digest the request without the fluff and responds commonly. To stack on this info hunting or product research with AI is also typically less full of fluff for me. I don't have to deal with a sales engineer saying how wonderful their ML product is when I know its garbage immediately, I can just move on and assess the rest of the product. The only value I can still see in Gartner is their customer survey information, but I am sure someone or somehow AI will scrape the forum post for all these products and weight the products community feedback about its product. | |||||||||||||||||||||||
▲ | SirFatty 2 days ago | parent [-] | ||||||||||||||||||||||
"Boomer catch phrasing" really? | |||||||||||||||||||||||
|