All language subtitles for 003 WHO Data Files_en

af Afrikaans
ak Akan
sq Albanian
am Amharic
ar Arabic
hy Armenian
az Azerbaijani
eu Basque
be Belarusian
bem Bemba
bn Bengali
bh Bihari
bs Bosnian
br Breton
bg Bulgarian
km Cambodian
ca Catalan
ceb Cebuano
chr Cherokee
ny Chichewa
zh-CN Chinese (Simplified)
zh-TW Chinese (Traditional)
co Corsican
hr Croatian
cs Czech
da Danish
nl Dutch
en English
eo Esperanto
et Estonian
ee Ewe
fo Faroese
tl Filipino
fi Finnish
fr French Download
fy Frisian
gaa Ga
gl Galician
ka Georgian
de German
el Greek
gn Guarani
gu Gujarati
ht Haitian Creole
ha Hausa
haw Hawaiian
iw Hebrew
hi Hindi
hmn Hmong
hu Hungarian
is Icelandic
ig Igbo
id Indonesian
ia Interlingua
ga Irish
it Italian
ja Japanese
jw Javanese
kn Kannada
kk Kazakh
rw Kinyarwanda
rn Kirundi
kg Kongo
ko Korean
kri Krio (Sierra Leone)
ku Kurdish
ckb Kurdish (Soranî)
ky Kyrgyz
lo Laothian
la Latin
lv Latvian
ln Lingala
lt Lithuanian
loz Lozi
lg Luganda
ach Luo
lb Luxembourgish
mk Macedonian
mg Malagasy
ms Malay
ml Malayalam
mt Maltese
mi Maori
mr Marathi
mfe Mauritian Creole
mo Moldavian
mn Mongolian
my Myanmar (Burmese)
sr-ME Montenegrin
ne Nepali
pcm Nigerian Pidgin
nso Northern Sotho
no Norwegian
nn Norwegian (Nynorsk)
oc Occitan
or Oriya
om Oromo
ps Pashto
fa Persian
pl Polish
pt-BR Portuguese (Brazil)
pt Portuguese (Portugal)
pa Punjabi
qu Quechua
ro Romanian
rm Romansh
nyn Runyakitara
ru Russian
sm Samoan
gd Scots Gaelic
sr Serbian
sh Serbo-Croatian
st Sesotho
tn Setswana
crs Seychellois Creole
sn Shona
sd Sindhi
si Sinhalese
sk Slovak
sl Slovenian
so Somali
es Spanish
es-419 Spanish (Latin American)
su Sundanese
sw Swahili
sv Swedish
tg Tajik
ta Tamil
tt Tatar
te Telugu
th Thai
ti Tigrinya
to Tonga
lua Tshiluba
tum Tumbuka
tr Turkish
tk Turkmen
tw Twi
ug Uighur
uk Ukrainian
ur Urdu
uz Uzbek
vi Vietnamese
cy Welsh
wo Wolof
xh Xhosa
yi Yiddish
yo Yoruba
zu Zulu
Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: 1 00:00:05,210 --> 00:00:06,740 Welcome to this case study. 2 00:00:07,070 --> 00:00:13,760 So when the coronavirus started to make an impact upon the world's population, I decided to get the 3 00:00:13,760 --> 00:00:17,780 information from the World Health Organization, put together a report. 4 00:00:17,960 --> 00:00:23,270 And basically, over the time since then, World Health Organization keeps producing a new file each 5 00:00:23,270 --> 00:00:23,750 day. 6 00:00:23,750 --> 00:00:25,360 So basically, I try every day. 7 00:00:25,370 --> 00:00:30,120 Don't always get it right, but we try every day to download the file, refresh the actual files. 8 00:00:30,140 --> 00:00:34,630 So obviously, this has been going on for quite a bit of time now since pandemic started. 9 00:00:34,640 --> 00:00:39,770 So what I wanted to do, though, in this case study was just run you through quickly exactly what we 10 00:00:39,770 --> 00:00:45,380 kind of doing and the report that we've produced and also how we make it available on the website. 11 00:00:45,380 --> 00:00:49,340 So as I say, this is just a little bit of a case study just to take you through how we do this. 12 00:00:49,370 --> 00:00:54,800 Now, please note over time, the way that the World Health Organization has produced its data and also 13 00:00:54,800 --> 00:00:56,960 produce the results has changed as well. 14 00:00:56,960 --> 00:01:02,330 So this has gone through a few evolutions in terms of the way that it works At the moment, it's actually 15 00:01:02,330 --> 00:01:02,990 pretty easy. 16 00:01:02,990 --> 00:01:07,610 Basically what I do is I go to the World Health Organization that can see on the screen at the moment 17 00:01:07,610 --> 00:01:09,650 and they have an option called data. 18 00:01:09,680 --> 00:01:12,860 Now, there is a link to this in the in the actual course notes. 19 00:01:12,860 --> 00:01:14,240 So you can go straight to this. 20 00:01:14,240 --> 00:01:17,420 And basically if you go down, you'll see an option called data download. 21 00:01:17,630 --> 00:01:21,170 When I select this, I am actually using this file at the moment. 22 00:01:21,170 --> 00:01:25,700 Delhi cases and deaths by data reported to the World Health Organization. 23 00:01:25,700 --> 00:01:27,200 So this is the file that I'm using. 24 00:01:27,200 --> 00:01:28,460 It's a CSV file. 25 00:01:28,490 --> 00:01:32,870 I download this file and basically then take it into power by now. 26 00:01:32,870 --> 00:01:37,400 In the next lesson, I'm going to show you the Power BI desktop report that I'm using and just show 27 00:01:37,400 --> 00:01:39,950 you some of the ideas that I had when I was putting it together. 28 00:01:39,950 --> 00:01:43,520 Just some of the thoughts that I was thinking at the time of putting it together. 29 00:01:43,610 --> 00:01:47,060 Before we get there, though, just while you're on the screen, there's a couple of things that you 30 00:01:47,060 --> 00:01:49,160 may want to actually just explore yourself. 31 00:01:49,190 --> 00:01:54,260 What you will find is the World Health Organization have also done their own data analysis, and some 32 00:01:54,260 --> 00:01:55,550 of it can be really interesting. 33 00:01:55,550 --> 00:01:56,690 So worth looking at. 34 00:01:56,720 --> 00:02:00,650 If you go to the beginning, you'll see that there is actually an overview and you can see that there 35 00:02:00,650 --> 00:02:05,060 is a map around the world just giving you an understanding of the sort of number of cases. 36 00:02:05,060 --> 00:02:08,000 The totals does give you the option to be able to change things. 37 00:02:08,000 --> 00:02:12,950 So you can say look at the death side of things, vaccination side of things as well, and get an overview 38 00:02:12,950 --> 00:02:13,820 of the world. 39 00:02:13,850 --> 00:02:16,190 Quite a nice map that they've got here also. 40 00:02:16,190 --> 00:02:18,770 Then they've got some key metrics, sort of trend graphs. 41 00:02:18,770 --> 00:02:22,580 They're showing a key metric here and then a trend graph of how things are changing. 42 00:02:22,730 --> 00:02:26,750 Also, the total numbers that are associated with it by the different regions. 43 00:02:27,230 --> 00:02:32,210 As you can see, you can go through this quite a lot of data to be able to look at and then then go 44 00:02:32,210 --> 00:02:37,310 to some key countries as well, just showing the totals that have been confirmed. 45 00:02:38,300 --> 00:02:40,520 Also see that they've got a number of different measures. 46 00:02:40,520 --> 00:02:44,060 So if you wanted to go in this, you can see some different information on that as well. 47 00:02:44,060 --> 00:02:47,040 And also a table view as well that can have a look at. 48 00:02:47,060 --> 00:02:49,610 So as I say, quite a bit of interesting information. 49 00:02:49,610 --> 00:02:53,900 They do update this, they do change this, but well worth having a look at. 50 00:02:54,230 --> 00:02:54,380 Okay. 51 00:02:54,380 --> 00:02:55,940 We're going to conclude the lesson here. 52 00:02:55,940 --> 00:03:00,380 We're going to move into the Power BI desktop and the next one, just to show you an example of a report 53 00:03:00,380 --> 00:03:04,850 I put together, it was quite some time ago now, but I'll show you some of the thinking that I had 54 00:03:04,850 --> 00:03:06,260 at the time of putting it together. 5663

Can't find what you're looking for?
Get subtitles in any language from opensubtitles.com, and translate them here.