hello everyone! my wardrobe has grown, for many reasons: so, every time I'm stressed I have this bad habit of shopping for clothes I don't need but you know what, it's fiNE, and plus some lovely companies have sent me their pieces to style (big thank you to them!). I've been trying to only buy things I truly love, so here are some of those shirts, dresses, and accessories. tell me what's your favorite piece of clothing below (mine is the green skirt hehe).
companies that were featured in this video:
mott & bow - https://www.mottandbow.com
princess highway - http://princesshighway.com.au
thanks for watching! 🌻
m u s i c
s o c i a l m e d i a
business inquiries: [email protected]
Sometimes I gotta watch a few videos before subscribing. And others, I subscribe after the first vdeo. Linh is definitely in the rare I've-subscribed-in-the-first-minute category because this is some quality ass content right here. Keep up the great work!!
PNW CONFIRMED! When I first watched you I was like "she kinda sounds like she's one of us" but then was like "no, the northwest doesn't have an accent" YOU HAVE VALIDATED MY PREDICTION. HINDSIGHT BIAS!
im not one to usually comment, but i found you through princess highway's instagram page. they're australian based and most people who purchase from them are australians themselves (me) so i think it's amazing that you're showcasing the brand to your many international viewers! they're my favourite brand and make the cutest of clothes :) i love how fashion brings people together haha!! aside from that i also love love love your channel, keep up the good work <3 from aus
This article has been motivated by a response I gave to a problem raised on an Oracle developer forum. Our requirement is to produce a report that details customer spending for each month of the year. Our database only records actual spend, so for any given month, data for dormant or idle customers will have to be generated.
First, well create a mock CUSTOMER_ORDERS table with sparse data to represent customer spending. To keep the example simple, well denormalise the customer name onto the orders table.
a sparse report.
With our customer orders data as sparse as it is, a monthly report for purchases by customer would look as follows.
adding the missing months.
We can see from the data that we are missing most months of the year for our two customers. Remember that our requirement is to show a report for every month in 2004 for every customer. First we will build a "time dimension" set (using subquery factoring) and outer join it to our orders table.
We can see that this hasnt quite worked. We have the zero sums and the year-months, but we are missing customer names. This is because we outer joined to CUSTOMER_ORDERS on the year-months, so any customer columns would show as NULL for deficient rows. Until PARTITION OUTER JOIN appeared in Oracle 10g, we couldnt "invent" data easily , though the next section shows that it is possible in prior versions.
data-densification without partition outer join.