Explore
For Enterprise
Join for Free
Log In

Explorar
Buscar
For Enterprise
Inicia Sesión
Únete de forma gratuita

Introduction to Databases

Loading...

Introduction to Clinical Data Science

Sistema Universitario de Colorado

4.7 (142 calificaciones) | 3.5K estudiantes inscritos

Curso 1 de 6 en Clinical Data Science Programa Especializado

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.

Revisiones

4.7 (142 calificaciones)

5 stars
99 ratings
4 stars
39 ratings
3 stars
4 ratings

FM

Feb 12, 2019

Easy to understand, very professional and studying material is clear and relevant. I definitely recommend this course to jump into the clinical and healthcare data science world.

SK

Jul 10, 2019

I encourage people to take this course.\n\nits real time and it equips with real skill.\n\nthe instructor is also so much great and into the point.

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

Impartido por:

Laura K. Wiley, PhD
Assistant Professor

Transcripción

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.

Explora nuestro catálogo

Inscríbete de manera gratuita y obtén recomendaciones personalizadas, actualizaciones y ofertas.

Coursera provides universal access to the world’s best education, partnering with top universities and organizations to offer courses online.

© 2019 Coursera Inc. Todos los derechos reservados.

Consíguelo en Google Play

Coursera
Acerca de
Liderazgo
Empleo
Catálogo
Certificados
Certificados MasterTrack™
Grados
For Enterprise
For Government
Para el campus

Comunidad
Learners
Partners
Developers
Beta Testers
Translators

Conectar
Blog
Facebook
LinkedIn
Twitter
Instagram
Youtube
Blog de Tecnología

Más
Términos
Privacidad
Ayuda
Accesibilidad
Prensa
Contacto
Directorio
Afiliados