【乾,我講英文有夠乾】: 看完「魷魚遊戲」只講得出 It’s great. 嗎?
大家也看了魷魚遊戲了嗎?很多紐約的 #美國朋友 跟我說
・It’s way better than the Hunger Games.
・I binged the whole 9 episodes (一次追了九集).
・It’s graphically brutal. (超級血腥殘忍)
・Totes worth a watch. (Totes 是 totally 的口語寫法)
但當我問問身邊的人會怎樣用英文聊這部劇時,台灣人的對這部影集的描述常常是:
・It’s really good.
・I liked it!
・You should watch it.
・I highly recommend it.
當然,這 4 句話在語意上、用法上沒有問題。但如果你想要用得更 #道地、#到位,請繼續讀下去。
1️⃣ 傳統無啥用的 solution:
面臨這樣的問題,傳統上不少英文老師會建議你去查閱同義字字典,去 #升級自己會的形容詞。但,其實不斷用 It’s adj. 的方式
或去升級 “like” 這個動詞,調成 I enjoyed watching it. 只是繼續圍繞在相似的想法裡頭,英文還是 #沒有質的變化。�
2️⃣ 從「#思維模板」、母語人士的「#說話習慣」下手:
其實不管是魷魚遊戲、還是 The Hunger Games、還是其他相似種類 (genre) 的電影,英美國人會講述的方式「大同小異」,並 #不會因人而異。這樣的好處就是我們有個範圍可以學習這些「思維模板」。不只是一兩個字的片語、搭配詞,而是整體「表達的方向」。
例如:
✔︎ 在表達從第一集就ㄉㄧㄠˊ住時,你可以說:�
I was hooked from the first episode.
It had me hooked from the start.
✔︎ 在表達很棒時,他們不會只說 It’s great. 他們會說
It's hands down one of the best series I’ve seen on Netflix.
One of the best shows I’ve seen in a long time.
✔︎ 其他正向表述、讚揚的講法還包含:
It’s worth a watch for sure! (值得一看)
It has set a high bar for other movies of this genre. (把標準提得很高)
It has definitely lived up to the hype! (真的如大家所說般地好 )
之所以為思維模板,就是母語人士ㄧ要描述電影觀後感時,
#幾乎都會馬上想到這些用法。我們不應該再走「中文想這樣講 — > 翻成英文」這樣的路。
記得,英文要學好不是要變成「逐字翻譯大師」。要從慣用思維、表達習慣下手。
🔥 如果你 / 妳喜歡這樣從思維下手,學習語塊不學單字的學習方式,歡迎你加入我在好學校 (Hahow) 上開設的線上課程 #3D英文筆記術。 站上大折扣剩下最後 3 天,不要錯過囉!
https://bit.ly/3mYj83s
(輸入折扣碼 GR2183,單堂 88 折、兩堂以上 83 折。)
Photo credit: Netflix
同時也有30部Youtube影片,追蹤數超過56萬的網紅kottaso cook【kottaso Recipe】,也在其Youtube影片中提到,English subtitles are available. Click the subtitle button on the screen. 有中文字幕。請按下畫面上的字幕按鈕選擇。 한국어 자막이 있습니다. 화면의 자막버튼에서 한국어를 선택해주세요. ◆こっタソ動物園チャンネル 新し...
「definitely中文」的推薦目錄:
- 關於definitely中文 在 Alexander Wang 王梓沅英文 Facebook 的最佳解答
- 關於definitely中文 在 D.A. Facebook 的精選貼文
- 關於definitely中文 在 D.A. Facebook 的最佳解答
- 關於definitely中文 在 kottaso cook【kottaso Recipe】 Youtube 的最佳解答
- 關於definitely中文 在 長笛玩家鄭宇泰 Youtube 的最讚貼文
- 關於definitely中文 在 CH Music Channel Youtube 的精選貼文
- 關於definitely中文 在 【老皮實況】Definitely Not Fried Chicken #0119 - YouTube 的評價
- 關於definitely中文 在 IRyS在直播上對Ina做出了史上最大的情感傷害...【Hololive中文】 的評價
- 關於definitely中文 在 definitely yes中文的推薦與評價,YOUTUBE - 居家網紅推薦指南 的評價
- 關於definitely中文 在 Bridging the gap between Google Analytics UI and BigQuery ... 的評價
definitely中文 在 D.A. Facebook 的精選貼文
-(中文版本往下滑!)
@lauramercier base makeup for the day!
💯Pure canvas primer hydrating
It’s the new version! I love the old one already 😍! What I look for primers is nothing but hydration, and this definitely gets the job done ✔️! Has a great scent!
💯Tinted moisturizer 1W1
The shade is too dark and orange on me🤣🤣but I like that it can be blend out by my fingers, without using brushes or sponges. Has a coverage that tinted moisturizer should be, I like more coverage so I’ll add some concealer after applying this. Super moisturized by itself that I barely need to put any skincare on before this. Oxidized a bit!
💯Translucent loose setting powder
It’s a classic that I finally get to have the chance to put my hands on it! I was kind of worried if it’s going to be too dry for me, but it’s not!!! The parts where I get oil still tends to get oil after a day 🤣 But I do like this product! ❤️
Have you tried any of their products before? What are thoughts on them?
Let me know in the comments below:)
Wish you all a lovely day!☺️
More pics👉👉👉
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蘿拉蜜思底妝特輯!
#鎖水藍管 煥顏凝露保濕款
舊版就是我的愛用~以我一個不常使用狀前產品的人來說,妝前對我最重要的目的就是保濕!畢竟妝前保濕的重要性真的不可或缺!底妝成敗的關鍵常常要看保濕做的好不好!如果奢侈一點也可以當保養品用啦🤣有好聞的香味,肌膚可以快速吸收並且留下保濕的觸感!
#懶人霜 保濕潤色美妝蜜清爽型1W1
色號對我來說偏深偏橘🍊了一點(雖然是我自己挑的🤣,會稍微氧化,大家可以的話還是靠櫃試一下顏色啊🥺)
有化妝品原料的味道,對味道敏感的人可以去聞看看~
我最喜歡的地方是用手就可以推均勻!
不用刷具或美妝蛋~因為很保濕、延展力也很好~保濕程度是可以乾肌不用上妝前的那種🥰上完就有一種自然的光澤感~
妝感屬於自然,想打造偽素顏或是好皮膚、只想均勻膚色的人很適合!一些痘疤跟暗沈斑點沒辦法遮住,不過局部再加遮瑕就可以完成很乾淨又自然的妝容!
如果想和高遮瑕的粉底混合使用也是可以的❤️
#冠軍蜜粉 煥顏透明蜜粉
這真的無人不知無人不曉吧!
經典產品!不會改變底妝顏色!
用之前有一點點擔心乾肌會不會太乾,但完!全!不!會!
粉真的超級細會飄~的那種~
妝感很美可以很完善的定妝!
乾肌真的一點也不用擔心!(尤其現在都戴口罩很悶熱蜜粉真的不可少!)
你們有用過lauramercier的彩妝嗎?
歡迎在留言區和我分享❤️
祝大家有美好的一天~~💕
更多照片👉👉👉
#makeupklever #化粧 #アイメイク #motd💋 #dailymakeup #아이메이크업 #메이크업아티스트 #오늘의화장 #눈화장 #makeupkontent #makeupidea #makeuptoday #100daysofmakeupchallenge #wakeupandmakeupsweeps #美妝 #美妝分享 #蘿拉蜜思 #夏日鎖水運動會 #煥顏凝露 #保濕潤色美妝蜜 #煥顏透明蜜粉 #lauramercier #settingpowder #tintedmoisturizer #primer #oilfree
definitely中文 在 D.A. Facebook 的最佳解答
-(中文版本往下滑!)
All matte look for today!
It’s definitely a fall look! Even though autumn 🍂 is not coming yet here in Taiwan 🇹🇼, but it’s fine to start with the looks!
I’m using the shades from @inglot_cosmetics freedom system palette in the shade 285 283 281 , I love them so much that I’ll be posting another post mainly talking about the palette! (With great shots too🤣) These are warm tone shades with red and browns in it!
Have you started fall looks yet?
Let me know in the comments below:)
Wish you all a lovely day!☺️
More pics👉👉👉
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全霧面初秋眼妝🍁
紅棕色系的完全就是秋天的顏色!
雖然現在還熱的像夏天,不過可以從妝容開始變換起😆
使用的是 #inglot 自組盤的單顆眼影 285 283 281 這三個顏色~
這盤超級美之後會用另外一篇貼文+美照介紹!❤️敬請期待😚
你們開始畫秋天的妝容了嗎?
歡迎在留言區和我分享❤️
祝大家有美好的一天~~💕
更多照片👉👉👉
#makeupklever #化妝教學 #化粧 #アイメイク #motd💋 #dailymakeup #아이메이크업 #메이크업아티스트 #오늘의화장 #눈화장 #makeupkontent #makeupidea #makeuptoday #eyelooktutorial #100daysofmakeupchallenge #wakeupandmakeupsweeps #眼妝 #美妝 #美妝分享 #messymakeup #eyelooks #eyelookoftheday #eyelookideas #eyelookmakeup #眼妝分享 #popdaily波波黛莉的異想世界
definitely中文 在 kottaso cook【kottaso Recipe】 Youtube 的最佳解答
English subtitles are available. Click the subtitle button on the screen.
有中文字幕。請按下畫面上的字幕按鈕選擇。
한국어 자막이 있습니다. 화면의 자막버튼에서 한국어를 선택해주세요.
◆こっタソ動物園チャンネル
新しいチャンネルです!こちらもおヒマな時にどぞ。
⇒https://www.youtube.com/c/こっタソ動物園-kottasoanimals
ご視聴ありがとうございます。
Thank you for watching
I want to deliver delicious Japanese-food recipes to the world
【材料】
●素麺:200g
●みりん:大さじ2
●醤油:大さじ2
●丸鶏がらスープ:小さじ2
●創味シャンタン:小さじ1(ウェイパーでもOK)
●砂糖:小さじ1(ラカントとかにすればより糖質が抑えられます)
●豆板醤:小さじ1(コチュジャンでもOK)
●かつお粉:小さじ1~小さじ2
●鶏油もしくはごま油:お好み量
●水:約350ml(お湯と水合わせた量)
●お好みでブラックペッパー、ホワイトペッパー、小葱、ラー油
※味の濃さは350ml足した後に味見してからお好みに調整して下さい。
※辛みが苦手な方は豆板醤を味噌に変えてもOK
※鶏油は温度が低いと固まってしまうのでスープを冷蔵保存する場合や氷で冷やす場合は食べる直前にかけて下さい。(冷蔵で約1か月保存可能です)
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素麺で作る最高の冷やしラーメン!
『やみつき無限そうめん』を作りました。
たった3分で出来たと思えない深い旨味とコク、それなのに超あっさり、ヘルシーで毎日食べても飽きない、最高にやみつきなスープになってます。
これを食べた人全員にこんな美味しい素麺料理は食べた事がない…と何度も言われた、この夏オススメしたい自慢のレシピです♪
スープと素麺だけでも凄く美味しいですし、もちろん中華麺で食べても最高に美味しいです🤤
簡単過ぎるくらい簡単なので是非一度お試しください。
マジでラーメン屋さんに負けてないですよ♪
驚くほどウマすぎて、もはや飲み物ですw
時間がある場合は鶏ハム(サラダチキン)や鶏油も是非作ってみてね!
[Ingredients]
● Somen noodles: 200g
● Mirin: 2 tablespoons
● Soy sauce: 2 tablespoons
● Chicken broth: 2 teaspoons
● SOMI shantung: 1 teaspoon (you can also use Weipa)
● Sugar: 1 teaspoon (you can use lakanto to reduce the sugar content)
● Dou ban jiang: 1 teaspoon (gochujang is also okay)
● Bonito powder: 1 to 2 teaspoons
● Chicken oil or sesame oil: as desired
● Water: About 350ml (hot and cold water combined)
● Black pepper, white pepper, small green onion, Ra-yu to taste
※Taste after adding 350ml and adjust the taste to your liking.
※If you don't like the spiciness, you can replace Dou ban jiang with miso.
※Chicken oil hardens at low temperatures, so if you refrigerate it, pour it over the soup just before eating. (It can be refrigerated for about a month)
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This is the best chilled ramen made with somen noodles!
I made "Yamitsuki Mugen Soumen".
It has a deep flavor and richness that you can't believe it was made in just 3 minutes, yet it's super light, healthy, and the most addictive soup that you can eat every day and never get tired of.
This is a recipe that I am proud to recommend to everyone who has tried it, and I have been told many times that they have never had such a delicious somen dish♪
It tastes great with just the soup and somen, and of course it tastes great with Chinese noodles too.
It's too easy to make, so please give it a try.
It's really as good as a ramen restaurant♪
It's so amazingly good that it's almost like a drink lol
And if you have time, definitely try making some chicken ham (salad chicken) and chicken oil too!
●Instagram
⇒https://www.instagram.com/kossarishuntaso/
●twitter
⇒https://twitter.com/kottaso_recipe
●連絡先
⇒kossarisyuntaso@gmail.com
#こっタソの自由気ままに #やみつき無限そうめん #JapaneseCuisine #Ramen #JapaneseCooking #ラーメン #サラダチキン #ヘルシー #鶏ハム #むね肉柔らかく #揖保乃糸 #油そうめん #拉麵 #라면 #龍鬚麵 #소면 #아부라소바 #減肥 #低糖質おつまみ #糖質制限レシピ #ヤセ筋 #低糖質レシピ #ヘルシー #ダイエットレシピ #激痩せ #ロカボレシピ #dietfood #lowcarbdiet #dietrecipe #晩ごはんレシピ #ご飯泥棒 #おかず #極上レシピ #ワンパンレシピ #時短レシピ #おうちごはん #至福の料理 #ご飯のお供 #太らないレシピ #やみつきレシピ #酒のつまみ #簡単つまみ #こっタソレシピ #男飯レシピ #mukbang #먹방 #男子ごはん #HomeCooking #StayHome #大食い #男ウケ料理 #晩酌 #自炊 #酒の肴 #簡単レシピ #弁当 #作り置き #Bento #recipesfordinner #マツコの知らない世界 #WithMe #Eazyrecipe #モッパン #から揚げ #唯一無二の絶品レシピ #こっタソ動物園
definitely中文 在 長笛玩家鄭宇泰 Youtube 的最讚貼文
I just arranged the most famous old animation cartoon "THE PINK PANTHER" into beatbox flute trio and piano. Work with these incredible students of mine is definitely the most lovely thing to do. Hope you guys enjoy the video and don't forget to give us a BIG "LIKE" 👍 to encourage them moving forward during this tough time, and subscribe now! Thank you guys!
Original song by Henri Mancini
Arranged by Yu-Tai Cheng (Flute Gamer Studio)
Get the Sheet Music: https://bit.ly/FGSheetMusic
Subscribe to my channel for more videos: http://bit.ly/subscribeflutegamer
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Please email for business enquiries only: myrllincheng@gmail.com
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#線上合奏
孩童長笛重奏團很講究固定練團,原本每週六下午在台北復興功學社的團練已經暫停快一個月了!我們每一次的曲目都會依照程度分成3~4個聲部,只要有進步、有自信可以吹得更好,就可以一次一次往高一個聲部升級,節奏和音型當然也越來越複雜,而最厲害的要全部的聲部都要會吹。
.
然而,疫情把大家鎖在家裡,老師沒有辦法現場指導整體的重奏感,只好緊急製作了正在練習的長笛重奏曲目的伴奏帶,附加節拍器的聲音在音檔內,並傳給家長讓孩子在家也能自我練習,
.
這一切都是老師為了孩子能夠持續自主學習而自掏腰包花費大量時間製作而成的產品,實際檢驗的過程意外的發現:
“孩子們更懂得如何聽聲音,如何當個稱職的主奏者和更好的和聲小幫手。”
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如果你也想加入我們的團隊,成為孩團這麼好玩的線上合奏的成員之一,在影片內秀出你吹奏的實力,同時開始學習 beatbox flute - 21世紀最好玩、最值得學習的長笛演奏法,趕快在底下留言,你就很有可能加入我們下一屆的冠軍成員喔!
喜歡這部影片請按下訂閱,這樣以後有新的有趣又好玩的beatbox長笛重奏影片就會在第一時間通知你囉!
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精彩影片回顧
- The Pink Panther [Beatbox Flute Trio] 頑皮豹 長笛重奏
https://youtu.be/RuTIu3BJ4P0
- Shakira - Try Everything (Zootopia) - Beatbox Flute Cover | 長笛玩家 feat. 孩童絕技長笛團
https://youtu.be/_BiKIcAhab8
- Ariana Grande - POV - flute duet
https://youtu.be/-ojdcI3-v5A
- Eminem - Rap God - Flute cover
https://youtu.be/YxJJyHDDhm8
- 刻在我心底的名字 Flute cover
https://youtu.be/m6374PHM-_o
- 循環換氣怎麼做?長笛教學10分鐘解密 所有管樂都通用的「循環呼吸」秘訣免費大公開
https://youtu.be/9FGNXhdoryc
- 【長笛四重奏全部自己吹】一人樂團,Beatbox flute “Mission Incredible” one man band at home
https://youtu.be/AgeBH34FpK4
- Beatbox flute《Beat Beats》flute duo 長笛二重奏 | 長笛玩家工作室
https://youtu.be/-2Sb_yn79-c
- 最好玩的跨界長笛演奏、最完整的長笛教學|長笛玩家工作室
https://youtu.be/X2XaKjhv1sE
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CONNECT WITH ME ON SOCIAL MEDIA
#長笛玩家工作室 #FluteGamerStudio
▸ YouTube: https://www.youtube.com/c/FluteGamer
▸ Facebook: https://www.facebook.com/myrflute
▸ Instagram: https://instagram.com/flutegamer
▸ Website: https://myrflute.com
▸ TikTok: https://tiktok.com/@flutegamer (NOT my main account)
▸ E-mail: flutegamer@myrflute.com
definitely中文 在 CH Music Channel Youtube 的精選貼文
《Walpurgis》
ever after / 從今以後,永不分離
作詞 / Lyricist:aimerrhythm
作曲 / Composer:百田留衣、玉井健二
編曲 / Arranger:玉井健二、 釣俊輔
歌 / Singer:Aimer
翻譯:澄野(CH Music Channel)
意譯:CH(CH Music Channel)
English Translation: CH(CH Music Channel)
背景 / Background - 曇のち - 荻pote:
https://www.pixiv.net/artworks/84907990
上傳你的字幕吧!/ Submit your subtitles here!
https://forms.gle/MSsAM2WHpT31UuUh8
版權聲明:
本頻道不握有任何音樂所有權,亦無任何營利,一切僅為推廣用途。音樂所有權歸原始創作者所有。請支持正版。
Copyright Info:
Be aware this channel is for promotion purposes only without any illegal profit. All music's ownership belongs to the original creators.
Please support the original creator.
すべての権利は正当な所有者/作成者に帰属します。あなたがこの音楽(または画像)の作成者で、この動画に使用されたくない場合はメッセージまたはこのYoutubeチャンネルの概要のメールアドレスにご連絡ください。私はすぐに削除します。
如果你喜歡我的影片,不妨按下喜歡和訂閱,你的支持就是我創作的最大原動力!
If you like my videos, please click like and subscribe! Thx :)
粉絲團隨時獲得最新訊息!
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中文翻譯 / Chinese Translation :
https://home.gamer.com.tw/creationDetail.php?sn=5130288
日文歌詞 / Japanese Lyrics :
あと少しでいいから ここにいて
それくらい いいでしょ? 気づいてよ
振り返るたび いつもまぶしくて
あなたの笑顔が よく見えない
かけがえのない時間(とき) これからもずっと
続いていけるような
ありふれた願い抱えた手を
零さないように 重ねて
ただ笑ってたくて そばにいて欲しくて
誰よりもその心に触れたくて
あなたの優しい声 聴かせて欲しいんだよ
目を閉じてほら 消えないように包みこんでいて欲しいんだよ
無理しなくていいから 窓開けて
ひとりにしないから はなしてよ
握り返せないほど 凍えた
指先をそっと とかすように
当たり前の奇跡 忘れてしまうほど
満たされてる日々を
白みゆく夜を見送るたび
想いだしていたいよ 何度も
ただ笑ってたくて そばにいて欲しくて
探してしまう 心に触れたくて
吐息をたしかめて ぬくもり分け合って
それだけでいい この手を離さないでいて いつまでも
擦り切れそうな言葉とか 剥き出しのままの欠片に
その瞳(め)が滲んでも ここに ここにいるよ ずっと
ただ笑ってたくて そばにいて欲しくて
誰よりもその心に触れたくて
あなたの優しい声 聴かせて欲しいんだよ
目を閉じてほら 消えないように包みこんでいて欲しいんだよ
中文歌詞 / Chinese Lyrics :
即使是短暫的片刻也好,陪在我身邊吧
只是任性一下並不過分吧?快察覺呀
回首看見的一切總是如此絢麗耀眼
燦爛得令我無法看清你的笑容
彷彿這段最珍貴的時光與點滴
從今以後仍能持續
為了不讓滿溢的願望自手中遺落
兩人彼此雙手相疊,十指緊扣
只願能與你相笑、願你能與我相伴
比任何人還更渴望知悉你的心意
我只想聽聽你那溫柔的聲音
我只希望在我閉上眼之後,你仍能緊抱著我,不再放手
可以不用再勉強了,打開窗戶吧
我不會再讓你感到孤獨了,敞開心扉吧
如靜靜地融化你那——
冰冷至無法握緊的雙手與指尖般
早已快遺忘,猶如理所當然般的奇蹟
每度過一天充實的時間
每見證一次漸明的夜晚
不論多少次,我都想憶起,那份彼此相遇的奇蹟
只願能與你相笑、願你能與我相伴
渴望知悉你的心意而不禁起身探尋
配合彼此的呼吸、分享兩人的溫暖
我不多奢求,僅渴望不放開繫起的雙手,永遠不放開
漸漸磨損消逝的話語,與剝落顯現出的片刻點滴
即使那雙眸已因此濕潤朦朧,但我在這、我就在這呀,永不離去
只願能與你相笑、願你能與我相伴
比任何人還更渴望知悉你的所有一切
我只想再聽聽你那溫柔的聲音
我只希望在我閉上眼之後,你仍能緊抱著我,不再放手
英文歌詞 / English Lyrics :
A little bit is enough, please stay by my side.
It's not too much and wilful, right? Just notice me!
Turning around, your smile is dazzling.
So bright that I can't see you well.
From now on, those irreplaceable times will definitely,
Last forever after.
Putting our hands together, so that these ordinary desires wouldn't slip through and spill out.
I just want to smile with you, wanting to stay by your side.
I want to know all your heart more than everyone else.
I want to hear your gentle voice.
I want you to hold me tightly so that everything won't disappear while I close my eyes.
No need to force yourself, just open the windows.
You're not alone, just share your feelings with me.
As if I gently melting your frozen fingers that can't be grasped.
My days are so satisfying that I've completely forgotten the miracle I took for granted.
Every time I see the dawn illuminates the night,
I want to remember it, more and more.
I just want to smile with you, wanting to stay by your side.
I want to search for your heart.
Checking our breaths, sharing our warmth.
Those are good enough. I just want you to hold my hand tightly so that we won't let go forever ever after.
Frayed words and unconcealed pieces,
are making those eyes blurred in tears.
Hey, I'm here, always be here for you, forever ever after.
I just want to smile with you, wanting to stay by your side.
I want to know all your heart more than everyone else.
I want to hear your gentle voice.
I want you to hold me tightly so that everything won't disappear while I close my eyes.
definitely中文 在 IRyS在直播上對Ina做出了史上最大的情感傷害...【Hololive中文】 的推薦價格和值得買嗎?
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definitely中文 在 Bridging the gap between Google Analytics UI and BigQuery ... 的推薦價格和值得買嗎?
Minhaz Kazi, Developer Advocate, Google Analytics – April
2023
"But why won't the numbers match with the UI?"
If you have worked with the BigQuery event export data for your GA4 property,
you definitely have asked this question at some point. Or worse - someone else
asked you this. And while trying to answer it, you probably have been asked the
dreaded followup question:
"And where does it say that?"
With this post, we will try to shed light on both.
Before we go into details of how the numbers vary, it is important to understand
the intended purpose of the BigQuery event export data. Google Analytics users
send their collected data to GA via one of the collection methods - Google
Tag, Google Tag Manager, Measurement Protocol, SDKs, and Data Import.
Based on the GA property's settings, Google Analytics does significant value
addition to the collected data before it reaches the standard reporting surfaces
including standard reports, Explorations, and the Data API. These value
additions can include inclusion of Google Signals, modeling, traffic
attribution, prediction etc.
The standard reporting surfaces aim to provide the maximum value to GA users at
the lowest friction. However, we understand that on the broad spectrum of users,
some might want to supplement the value additions by Google Analytics or even do
something completely customized. For these users, BigQuery event export is the
intended starting point. BigQuery event export will have collected data,
which is sent from the client or app to Google Analytics. BigQuery event export
will not contain granular data on most value additions mentioned above.
Thus, for a large number of use cases, the standard reporting surfaces and the
BigQuery export data aren't expected to be reconcilable when it comes to these
value addition parts. If there is internal consistency in both and they match
with what you are collecting, you should be good to go.
Now let's get into some of the specific reasons for the differences and explore
ways for mitigating them when possible. This post focuses on the BigQuery
Daily event export only and not the Streaming export.
For accurate comparison of your BigQuery export data with standard reports, Data
API reports, or Exploration reports, confirm they are not based on sampled data.
Data Sampling in GA4 provides further details and ways to address sampling.
If you count all the users who have logged at least one event on your GA4
property, you will get the Total Users metric. Although the Total Users
metric is available in Explorations in GA4 UI, the primary user metric used for
reporting in GA4 is Active Users. In GA4 UI and in reports, if only Users
is mentioned, that usually refers to Active Users. So when calculating user
count from BigQuery data, you will need to filter and keep only the active users
to make the numbers comparable to the GA UI. The calculation method will also
vary based on your selected Reporting Identity.
In BigQuery event export data, if you count the number of distinct User IDs, you
will get the Total Users count. Here's a sample query that shows both Total
Users and New Users based on user_pseudo_id
:
-- Example: Get 'Total User' count and 'New User' count.WITH
UserInfo AS (
SELECT
user_pseudo_id,
MAX(IF(event_name IN ('first_visit', 'first_open'), 1, 0)) AS is_new_user
-- Replace table name.
FROM `bigquery-public-data.ga4_obfuscated_sample_ecommerce.events_*`
-- Replace date range.
WHERE _TABLE_SUFFIX BETWEEN '20201101' AND '20201130'
GROUP BY 1
)
SELECT
COUNT(*) AS user_count,
SUM(is_new_user) AS new_user_count
FROM UserInfo;
To select only active users, limit your query to events where is_active_user
is true
:
-- Example: Get exact and approximate Active User count.WITH
ActiveUsers AS (
SELECT
user_pseudo_id
-- Replace table name.
FROM `bigquery-public-data.ga4_obfuscated_sample_ecommerce.events_*`
-- Replace date range.
WHERE _TABLE_SUFFIX BETWEEN '20201101' AND '20201130'
AND is_active_user
GROUP BY 1
)
SELECT
COUNT(DISTINCT user_pseudo_id) AS exact_active_user_count,
APPROX_COUNT_DISTINCT(user_pseudo_id) AS approx_active_user_count
FROM ActiveUsers;
HyperLogLog++
Google Analytics uses HyperLogLog++ (HLL++) algorithm to estimate cardinality
for common metrics including Active Users and Sessions. That means when you view
the unique count of these metrics in the UI or via the API, they are an
approximation with a certain precision. In BigQuery, since you have access to
the granular data, you can calculate the exact cardinality for these metrics. So
metrics can vary by a small percentage. At 95% confidence interval, the
precision might be ±1.63% for session count. The precision levels will vary for
different metrics and will change according to the confidence intervals. See
HLL++ Sketches for the precision levels at different confidence intervals for
different precision parameters of HLL++.
See Unique count approximation in Google Analytics to understand how HLL++
implemented in Google Analytics and how you can replicate the functionality
using BigQuery queries.
The daily export tables are created after GA collects all events for the day.
The daily tables can get updated up to 72 hours beyond the date of the table
with events that are time-stamped with the date of the table. Read details
about this and see examples. This is more of an issue if
your Firebase SDK or Measurement Protocol implementation sends in offline or
delayed events. Depending on when the standard reporting surface and BigQuery
are updated within those 72 hours, you might see differences
between them. For such implementation, comparisons should be made on data older
than 72 hours.
Assume you are viewing a report through standard reports or the Data API.
The report surfaces a large amount of data and has dimensions with high
cardinality. High cardinality dimensions might cause the report to exceed the
cardinality limit for the underlying table. When this happens, Google Analytics
will group less frequent values and label them as (other).
Using a simplified and small scale example, if the cardinality limit for the
underlying table is 10 row, this is what you can expect to happen:
As you can see, the total number of events remains unchanged. However, less
frequent values get grouped together and you cannot re-aggregate the table based
on any dimension (e.g. you can't take the aggregate table and derive the total
event count for a specific city with high precision). The example gets more
profound if you filter the aggregate data based on any of the dimensions.
This grouping of the (other) row happens only in the reporting module and the
Data API when the report crosses the cardinality limit. If you do your
calculations from BigQuery, you will always end up with the ground-truth data -
the most granular rows. Read more about the (other) row and best practices on
how to avoid it.
Activating Google Signals on your GA4 property has several benefits including
deduplicating users across platforms and devices. If you don't collect user
IDs or activate Google Signals and a person views your website on three
different web browsers, then Google Analytics attributes that activity to three
different users, and BigQuery export will have three separate user_pseudo_id
s.
In contrast, with Google Signals activated and the person logged into their
single Google Account in all three browsers, Google Analytics attributes that
activity to one user and reflects that count in standard reporting surfaces.
However, BigQuery will still show three separate user_pseudo_id
s because
Google Signals information is not available in the BigQuery export. Thus,
reports with Google Signals data will most likely have less user count compared
to BigQuery export.
The best way to lessen this effect is to implement User-IDs in your GA4
property along with activating Google Signals. This will ensure that the
deduplication happens first based on user_id
. For signed in users, user_id
field will be populated in BigQuery and can be used for calculation purposes.
However, for users that are not signed in (i.e., sessions without user_id
),
Google Signals will still be used for deduplication.
Also note that certain reports in standard reporting surfaces might have
thresholding applied and not return certain data. Most information that can be
subject to thresholding usually is not available in the BigQuery export.
Consent mode on websites and mobile apps lets you communicate your users'
cookie or app identifier consent status to Google. When visitors deny consent,
GA4 fills the data collection gaps with key event modeling and behavioral
modeling. None of the modeled data is available in the BigQuery event export.
When consent mode is implemented, BigQuery dataset will contain cookieless pings
collected by GA and each session will have a different user_pseudo_id
. Due to
modeling, there will be differences between the standard reporting surfaces and
the granular data in BigQuery. For example, due to behavioral modeling, you
might see less number of active users compared to the BigQuery export as
modeling might try to predict the multiple sessions from individual consentless
users.
Again, to reduce the effect of this, you should implement User-IDs in your GA4
property. user_id
and custom dimensions are exported to BigQuery regardless of
the consent status of your users.
In BigQuery traffic attribution data is available at user (first visit) and
event level. These are the collected data. However, since Google Analytics
implements its own attribution model at session level, that information is
neither directly available in BigQuery export nor can it be calculated with full
accuracy with the available data. Depending on your use case, you can consider
joining the BigQuery dataset with any relevant first party data and building
your own attribution model. In the future, additional collected data for traffic
attribution might be available through BigQuery event export.
Calculation method: When calculating different metrics in BigQuery,
ensure you are using the correct methodology. For example:
The standard method of counting sessions for Google Analytics 4
properties is counting the unique combinations of
user_pseudo_id
/user_id
and ga_session_id
regardless of thetimeframe. In Universal Analytics, sessions would reset at midnight. If
you follow the UA model, calculate sessions for each day, and add them
up to get a total session count, you would be double counting the
sessions that span across multiple days.
Depending on your selected Reporting Identity, the user count
calculation method will have to be updated.
Dimension and metric scope: Ensure that your calculations use the
correct user, session, item, or event level scope.
Time Zone: In BigQuery export,
event_date
is for the reporting timezone while
event_timestamp
is an UTC timestamp in microseconds. Soideally, if one uses
event_timestamp
in a query, it has to be adjusted forthe correct reporting time zone when comparing with UI numbers.
Data filtering and Export limits: If you have setup Data Filtering for
your BigQuery event export or your daily event export volume has exceeded
the limit, the BigQuery event export data will not match with the standard
reporting surfaces.
WITH all that, there is a bit to UNNEST in this post. Hopefully you can SELECT
the right solutions for your DISTINCT project FROM the guidelines here. If you
have questions, JOIN the GA Discord server WHERE queries are most welcome!
... <看更多>
definitely中文 在 【老皮實況】Definitely Not Fried Chicken #0119 - YouTube 的推薦價格和值得買嗎?
歡迎來到Op Channel 老皮實況喜歡,就讚爆它好嗎?·Facebook· http://facebook.com/opchanneltw·Twitch· http://twitch.tv/mobilmobil如果喜歡老 ... ... <看更多>