3min chapter

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How to Trade Market Sentiment & Why Inflation Is Coming Down | Jared Dillian

Hidden Forces

CHAPTER

Introduction

hidden forces is a podcast that inspires investors, entrepeners and everyday citizens to challenge consensus narratives. Our guest in this week's episode is Jerrid Dillion, the editor of the daily dirt dabits - an es letter for professional investors focused on gauging and capitalizing on changes in market sentiment. Since some of this episode deals with investing, it should be absolutely clear that nothing we say on this podcast can or should be viewed as financial advice.

00:00
Speaker 1
I sould that's abood point,
Speaker 2
because you're almost like having an internal product, like an internal sas protuct en creater, with the abstraction that the nuse at the point doesn't carry care, like the just looking at dat upons deelement as well, which, cate reminds me of the whofe security litis, clear defined, like tope, orlistning about tecato a, or would you say te the kiote deta leg is like a foundation on which this is built? It could't be, right? I think you're
Speaker 1
itoneed indeed. A stor riht, whethert a graf a leg, a warehouse. And i'm pretty sure that you'll probably use twoor three, if not all through, right? So you notus it a data leg is a system that can contain a structured, semi structure and unstructured data, rightand peb halasaits a bokeu know something very well, structure coud be, you know. And, you know, an example for all that could be liking u you pt af dogs. You have, you know, free tax cindlexet logs and im. You have jason documents, you know. So that's cindolikte, different things that you're dealing withand instead of aasinli, you're not going index a pof inside of a frecan sin. Put fhree text files inside of a sin like a sim ysit in a very specific form a. It may have a tool that you could license, or you could use to, like, transform records. It may flatten jason for you, but it's like, well, that's a half measure. I i want to flaten the jason. It needs to be a nest of listeris the dictionary, you reason, rightso that's where the dalight comes into inthe security daily link, isnt you know, thereare companies out there, panther, for instance. Po kind of dises itself. Even thoits more distributed query in a snowflake spends a lot of time talking about the security. Dalan security do warehouse. So it's on o anything special, just a day lake ra billd o vanalake, you understand your axis patterns, how you're writing k all the operational davis stuff that goes along with it, and then you're using it for security outcomes, right? A, rightb, i guess a practical example would be, you know, maybe taking, you now, don't use like information, but, you know, ui, building your own fake lake nformation, right? Which is what ourside project, synthetics o supposed to be. But it's not h here nor there. So it's taking mus be, we see logs its ploud ti logs, application specific logs. And a meeven pooling like deta from the pis rii, you know, easy to describe instances, you know, a me to smar, little balancers. You've taken all that yore, putting it, like, different paths, rtd, a vestry, and then you're running in o queries on top of it. Maybe you're extracting that data wifh another, you know, of the k, and then you're putting it together with pandas, and then giving somebody to cee a spee, dropin tasspeto, that same la. Grags, now this is your struct ure data, thand you're having your quicksight on top of it, or something else. Thou beod, yes, that can be a practical example. O, flo building up towards it but it differ plays a part if that's going to be, you know, a it's picker poison, really.

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