Introduction to Databases

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Del curso dictado por University of Colorado System

Introduction to Clinical Data Science

10 calificaciones

University of Colorado System

Introduction to Clinical Data Science

10 calificaciones

Curso 1 de 6 en SpecializationClinical Data Science

This course will prepare you to complete all parts of the Clinical Data Science Specialization. In this course you will learn how clinical data are generated, the format of these data, and the ethical and legal restrictions on these data. You will also learn enough SQL and R programming skills to be able to complete the entire Specialization - even if you are a beginner programmer. While you are taking this course you will have access to an actual clinical data set and a free, online computational environment for data science hosted by our Industry Partner Google Cloud. At the end of this course you will be prepared to embark on your clinical data science education journey, learning how to take data created by the healthcare system and improve the health of tomorrow's patients.

De la lección

Tools: SQL

Develop basic skills in SQL (Structured Query Language) and query the real clinical data set used in the Clinical Data Science Specialization.

Introduction to Databases3:36

Conoce a los instructores

Laura K. Wiley, PhD
Assistant Professor
Division of Biomedical Informatics and Personalized Medicine, Anschutz Medical Campus

Databases, specifically relational databases, are a powerful and

efficient way to store and access massive amounts of data.

You are all probably familiar with spreadsheet tools, like Excel or

Google Sheets.

In spreadsheets, you have a table with rows and columns.

For example, let's say that each row is a patient and

each column contains some data elements about the patient.

Their name or date of birth.

This format was really well when there is only one to insert each column for

each patient.

But this does not work so well when you have multiple events.

Imagine that one of the columns is date of clinic visit,

but Mister Smith has visited the clinic multiple times.

Which date should go in the column?

One option would be to make more columns and

label them visit one, visit two, and so on.

Another option would be to make a new row that

duplicates all the information that is the same,

or you can simply move to a relational database.

Relational databases have multiple tables that in some way relate to one another.

Let's take our previous example, and

see how that data could be represented in a relational database.

First, we could create a patient table that has the patient's name,

and date of birth, plus a unique code that identifies them.

This table then will only have one row for each patient.

To record the clinic visits, we could create a table called encounters.

This table has a row for each encounter.

So a patient with multiple encounters will have multiple rows,

one for each time they were seen.

In this table, we will record which patient had the encounter,

when that encounter occurred, and any other relevant details.

We can also include a unique code for each encounter.

Because I have the column Patient_ID in both tables,

I can combine them based on that value.

This is the relational part of relational databases.

And this allows me to answer the question, who was seen in the clinic yesterday?

I can simply match the visit record with the patient names.

In addition to this structural difference between spreadsheets and

databases, there is one other major difference you should know about.

In spreadsheets, you can type anything into any field that you like.

You can type a word, a date, or a number,

even if it doesn't make sense as an answer for that column.

This is not possible in databases.

Each column in a database has a particular type,

like a number, character, or time stamp.

If your data does not follow the format in a particular column,

it can not be entered into the database.

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