Original subtitles

‫Hold on, you didn't learn anything in the last video.

‫Oh, boy, you're a tough cookie.

‫Don't worry, we will get into more and more advanced topics later in the course.

‫But let's finish our talk on database's because again, I want to connect the dots for us.

‫We learned that a database is essentially a computer with some database software on top.

‫In a way, if you've ever used something like Google Sheets or Excel, that's a database, right?

‫It's a way for us to store data.

‫And the Excel software allows us to manipulate that data.

‫In a way, a pen and paper is a database as well.

‫It's not digital, but it's a way for us to store data.

‫Now, the reason we always see these images as database's is because of this, this is called drum memory

‫and I'll link to this resource so you can read more about it.

‫But back in the day before we had disk drives, this is how we stored data.

‫It was called drum memory.

‫And as you can see, it's cylindrical.

‫And that's why for historical reasons, just like our save button on a computer is a floppy disk, this

‫drum memory represents usually databases.

‫But again, in this day and age, they're all just computers.

‫So because a database is just a computer and some software, are there many different types of databases?

‫Well beyond there are.

‫I mean, we talked about Excel, right?

‫Essentially, you can use a spreadsheet that you get in Excel to store data.

‫So why don't we just use that for all companies?

‫Why do we need something bigger, something like a database that we're going to talk about?

‫You see, the problem with things like Excel is that eventually you'll get to a point where you have

‫too much data where an Excel or a spreadsheet just can handle it.

‫And on top of that, there are many things that databases that will learn about in this course will

‫solve, such as making sure that database has integrity.

‫So that is not everybody can just modify data or delete a database.

‫You can store terabytes of data, you can combine different databases.

‫You can automate steps and use programs to do some really interesting things that you might not be able

‫to do on a spreadsheet.

‫Again, something we'll cover later on in the course.

‫But some of the most popular databases are here.

‫This is just a fraction of the databases out there because data is so different, because every company,

‫every user uses data in a different way.

‫We have different databases that do things differently, and each one of these have pros and cons.

‫Now, the beauty is that in this course, we're going to cover some of the main databases and way to

‫interact with them.

‫And later on, we'll learn about the pros and cons so you can decide which database you should use based

‫on your situation.

‫But let's take Kako Corp as an example.

‫How would Kako Corp or a company use a database?

‫Well, we mentioned that there's lots of data coming into a company and a company as big as Kako Corp.

‫has a lot of uses for data.

‫For example, you might have product managers and product managers always have to know the product that

‫they are working on.

‫For example, drones, they need to get data and learn about the products.

‫Health, whether a product is working properly, learn from data, learn from different information

‫to perhaps improve a product.

‫You have things like marketers and marketers, you need to find out information from data you want to

‫analyze business decision, give you insights about how to market a product.

‫Or you might be a web developer, a mobile app developer that creates apps on phone or on the Web,

‫and those apps usually have things like user signings or profiles that you need to store somewhere so

‫that when a user comes back onto your app, they're able to reload their information or maybe they're

‫playing a game and they need to start the game from their last saved location.

‫You also have things like data analysts or data scientists that understand data, that analyze data

‫of a company and make decisions such as perhaps even building machine learning models so that a company

‫can serve better information to a user, better products to a user, analyze different parts of the

‫company to maybe see which employees should get a raise, who to hire.

‫And then you also have data engineers or database administrators.

‫These are the people that actually help set up the databases and a company update software, install

‫things, make sure that databases are connected with one another.

‫They might use things like Hadoop, Facebook's Presto, Google's big query, Amazon Redshift and set

‫up all this infrastructure in place for other parts of the companies to use databases.

‫Now, as you can see, there's lots of data and more importantly, there's lots of different databases,

‫different people in a company that use databases in different ways.

‫But hold on a second.

‫All this data is used differently by different people, right?

‫Different operations, different options.

‫Each of these people are interested in different parts of data.

‫And this is why you're taking the course.

‫You're taking this course because you want to hopefully be able to work in any of these fields, and

‫the good news is that even though there's all sorts of databases, even though there's all sorts of

‫jobs, one of the most common ways to work with databases to ask a database, a question what we call

‫a query, to interact with it, to use that information that is so useful, we use ask you, well,

‫a way for us to interact or communicate with that database.

‫And that's what this course is all about.

‫Let's take a break and I'll see you in the next video.