Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated:
1
00:00:01,070 --> 00:00:04,980
What is a database hold on a second.
2
00:00:05,330 --> 00:00:11,210
Maybe you are a smarty pants and you know what a database is, but trust me, in this section you may
3
00:00:11,210 --> 00:00:13,630
learn a thing or two that will surprise you.
4
00:00:13,760 --> 00:00:19,820
So no matter what level of experience, just hang in there, promise we'll get to some really fun stuff.
5
00:00:20,300 --> 00:00:20,590
You see.
6
00:00:21,080 --> 00:00:28,070
I remember when I first learned about databases and Eskil, I couldn't understand how it was all connected
7
00:00:28,220 --> 00:00:29,180
with other fields.
8
00:00:29,690 --> 00:00:36,560
I would learn about web development or python or machine learning and had no idea how this school or
9
00:00:36,560 --> 00:00:39,550
databases really related to those fields.
10
00:00:40,220 --> 00:00:46,340
So I want us to always understand the big picture and connect the dots so that the things you learn
11
00:00:46,340 --> 00:00:51,620
in this course, you understand why it is useful and how we can use what we learn to do.
12
00:00:51,620 --> 00:00:54,840
Some really interesting things in the world of tech.
13
00:00:54,980 --> 00:00:57,500
So what is a database?
14
00:00:58,340 --> 00:01:06,380
A database is a collection of data and also a method for us to access and manipulate that data.
15
00:01:07,310 --> 00:01:09,230
So let's think about the statement.
16
00:01:09,920 --> 00:01:12,880
Data is everywhere, right?
17
00:01:13,250 --> 00:01:17,320
Data is now the most valuable commodity in the world.
18
00:01:17,900 --> 00:01:25,550
Companies that control data, companies that have a lot of data like Uber, like Alibaba, like Amazon,
19
00:01:25,730 --> 00:01:31,250
like Facebook, like Google, are some of the most valuable companies in the world because they have
20
00:01:31,250 --> 00:01:31,820
this data.
21
00:01:32,420 --> 00:01:36,590
And every day in our world, we produce data.
22
00:01:36,770 --> 00:01:37,250
Right.
23
00:01:37,850 --> 00:01:45,320
Whether it's drones with footages or location data, mobile phone apps, maybe website and web pages,
24
00:01:45,500 --> 00:01:47,330
even security cameras.
25
00:01:47,510 --> 00:01:49,300
We even have autonomous cars.
26
00:01:49,310 --> 00:01:51,650
All those things collect data.
27
00:01:51,950 --> 00:02:00,920
And the crazy part is that it's estimated we produce 2.5 quintillion bytes of data every year.
28
00:02:01,280 --> 00:02:04,490
And by the way, quintillion means this many zeros.
29
00:02:04,640 --> 00:02:05,690
It's a lot of zeros.
30
00:02:06,700 --> 00:02:12,050
More data is collected in the past two years than the entire human history.
31
00:02:12,910 --> 00:02:14,770
So where does all this data go?
32
00:02:15,040 --> 00:02:16,980
Does it just get stored in a notebook?
33
00:02:16,990 --> 00:02:19,290
Does somebody with pen and paper write it down?
34
00:02:19,990 --> 00:02:20,370
No.
35
00:02:20,380 --> 00:02:20,700
Right.
36
00:02:20,860 --> 00:02:26,260
And how can you really have that statement that more data has been generated in the last two years than
37
00:02:26,260 --> 00:02:28,130
all of human history combined?
38
00:02:28,330 --> 00:02:34,270
I mean, sure, there's more humans on Earth, but there's always been the same number of atoms in the
39
00:02:34,270 --> 00:02:34,930
universe.
40
00:02:35,060 --> 00:02:37,750
You can just create something out of nothing.
41
00:02:38,210 --> 00:02:44,560
When we say that data is being created more and more, the idea is that we're capturing this data.
42
00:02:44,980 --> 00:02:49,270
We're saving this data somewhere to be used in some way.
43
00:02:49,840 --> 00:02:52,600
Data is something that we as humans create.
44
00:02:52,810 --> 00:02:57,990
But without capturing that data or using it, it's completely useless.
45
00:02:58,570 --> 00:03:06,430
We use oil to power cars, but if we don't extract that oil, if we don't use that oil, it's completely
46
00:03:06,520 --> 00:03:07,210
useless.
47
00:03:08,020 --> 00:03:10,960
So we need a way to capture this data.
48
00:03:11,350 --> 00:03:13,570
And that's what databases do.
49
00:03:13,570 --> 00:03:16,900
They capture this data for us so that we can use it.
50
00:03:17,770 --> 00:03:22,840
And here's another crazy number, 40 for the digital universe.
51
00:03:22,840 --> 00:03:28,720
That is, the data that we store is estimated to be about 44 zettabytes of data.
52
00:03:28,880 --> 00:03:29,680
How many zeros?
53
00:03:30,310 --> 00:03:32,830
Once again, lots and lots of zeros.
54
00:03:33,860 --> 00:03:36,320
So all this data is being captured.
55
00:03:37,380 --> 00:03:44,190
In a database without a database, we wouldn't be able to store this massive amount of data and more
56
00:03:44,190 --> 00:03:47,550
importantly, we can do some useful things with this data.
57
00:03:48,240 --> 00:03:55,080
All those things we saw like autonomous cars, Instagram, Facebook, Google, without data, none of
58
00:03:55,080 --> 00:03:55,950
it would work.
59
00:03:56,580 --> 00:04:01,920
So without a database, the ability to query a database, that is to ask database information about
60
00:04:01,920 --> 00:04:05,070
its data, it would be impossible for us to do a lot of things.
61
00:04:05,200 --> 00:04:07,070
But here is a secret.
62
00:04:07,590 --> 00:04:14,910
We mentioned that a database is a collection of data, in a way, for us to access and manipulate that
63
00:04:14,910 --> 00:04:15,270
data.
64
00:04:16,240 --> 00:04:23,560
But the secret is that databases aren't anything special, they're just hardware and software, there's
65
00:04:23,560 --> 00:04:24,900
just computers.
66
00:04:25,660 --> 00:04:32,470
So a database, even though we always see this scary looking cylinders are just computers.
67
00:04:33,500 --> 00:04:40,340
We see images like this all the time representing databases, but they're just computers, it's hardware
68
00:04:40,640 --> 00:04:41,450
with software.
69
00:04:41,460 --> 00:04:47,690
So that is hardware is the mechanical part and the software is the actual code on top that allows us
70
00:04:47,690 --> 00:04:50,230
to collect and use the data really useful.
71
00:04:50,750 --> 00:04:57,740
So in this course, what you'll see is that we do the first step, which is one, we install software
72
00:04:57,980 --> 00:05:02,090
to turn our computer into a database so that we can all practice.
73
00:05:02,450 --> 00:05:08,030
And two, we add data to this database that we create with this software, and then we're going to start
74
00:05:08,030 --> 00:05:16,430
using it and analyzing it, because at the end of the day, a database is exactly this just a disk drive,
75
00:05:16,430 --> 00:05:20,420
a way for us to store ones and zeros on a computer?
76
00:05:21,710 --> 00:05:28,280
And the beautiful thing is that as long as we can install something, we have a computer, something
77
00:05:28,460 --> 00:05:35,090
with memory that we can store memory in, and we have a machine, a computer, we can create a database
78
00:05:35,090 --> 00:05:41,020
that is we can create a database, even on a mobile phone, on our desktops or on our laptops.
79
00:05:41,030 --> 00:05:42,790
And that's what we're going to do in the course.
80
00:05:42,800 --> 00:05:46,430
But when you see somebody having a database, that's all it means.
81
00:05:46,430 --> 00:05:53,330
They have a computer somewhere in the world with software installed for it to store and manipulate that
82
00:05:53,330 --> 00:05:53,690
data.
83
00:05:54,590 --> 00:05:56,660
Let's take a break and I'll see you in the next video.
8052
Can't find what you're looking for?
Get subtitles in any language from opensubtitles.com, and translate them here.
Afrikaans
Akan
Albanian
Amharic
Armenian
Azerbaijani
Basque
Belarusian
Bemba
Bengali
Bihari
Bosnian
Breton
Bulgarian
Cambodian
Catalan
Cebuano
Cherokee
Chichewa
Chinese (Simplified)
Chinese (Traditional)
Corsican
Croatian
Czech
Danish
Dutch
English
Esperanto
Estonian
Faroese
Finnish
Galician
Georgian
German
Greek
Guarani
Haitian Creole
Hausa
Hawaiian
Hebrew
Hmong
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Kazakh
Kinyarwanda
Kirundi
Kongo
Korean
Krio (Sierra Leone)
Kurdish
Kyrgyz
Laothian
Latin
Latvian
Lithuanian
Luganda
Luo
Luxembourgish
Macedonian
Malagasy
Malay
Maltese
Maori
Mauritian Creole
Moldavian
Mongolian
Myanmar (Burmese)
Montenegrin
Nepali
Norwegian
Pashto
Persian
Polish
Portuguese (Brazil)
Portuguese (Portugal)
Quechua
Romanian
Romansh
Russian
Samoan
Scots Gaelic
Serbian
Sesotho
Setswana
Seychellois Creole
Shona
Sindhi
Sinhalese
Slovak
Slovenian
Somali
Spanish
Swedish
Tajik
Thai
Tigrinya
Tonga
Turkish
Turkmen
Ukrainian
Uzbek
Vietnamese
Welsh
Wolof