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In this lesson, we are going to talk briefly about database preparation.

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So, as you know, a most of the artificial intelligence applications are based on data.

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And one of the main sources of data are databases.

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So one of the things that you will have to focus your attention in before, uh, launching a, an LMS

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application is the source of your, of your data.

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And sometimes the database preparation is one of the main keys, a, that is going to impact in the

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quality, the performance of your application.

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So there is a phase, a working phase which we can call database preparation which is going to be important.

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And when you are in the situation of preparing the launch of your application, this is something that

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you will want to spend some time on.

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When we are talking about database preparation, as you will see once you study this topic further,

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we are talking about different things.

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For example, one of the things that it is important to consider when you are working with databases

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is the size of the databases, the size of the database and the way you handle it is going to affect

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the performance of your application, and especially the speed and the cost.

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So it is very important for you to consider the alternatives and the different impacts they are going

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to have in your application.

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Remember that in this program we have used very small, uh, sources of data, uh, in order to, uh,

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demonstrate the different exercises in a very easy and fast way.

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But in the real world, especially when you are dealing with enterprise level companies or a mass,

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uh l.l.m. applications, uh, you will have to use a very big databases.

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So it is very important for you to consider the size and how do you handle it.

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And apart from the size, you have some other considerations regarding regarding the the data itself.

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For example, you will have to a be careful about data quality about things like duplicated data or

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personal private confidential data.

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You can uh, include uh, in the database by mistake.

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And also you will have to be prepared for things like lack of domain specific context regarding the

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database.

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So we are not going to, uh, go into detail, uh, with this, with these topics here.

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The only purpose of this lesson is just to give you a warning right now, before you go to the to the

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last phase of, uh, your professional Elm application, that there are some things that you will need

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to consider.

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All these things depend on the consideration you are going to to give to all these.

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And different things will depend on the size of your team, the size of your budget, the characteristics

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of your projects, and many other things.

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But in this last part of the program, we just want to highlight some things that will be important

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for you in the last phases of preparing a professional Elm application.

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So in the next lesson, we are going to talk a little bit more about one topic we have already covered,

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which is drag optimization.