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Exploratory Data Analysis in SQL

4.3+
56 reviews
Intermediate

Learn how to explore what's available in a database: the tables, relationships between them, and data stored in them.

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4 Hours16 Videos58 Exercises
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Course Description

You have access to a database. Now what do you do? Building on your existing skills joining tables, using basic functions, grouping data, and using subqueries, the next step in your SQL journey is learning how to explore a database and the data in it. Using data from Stack Overflow, Fortune 500 companies, and 311 help requests from Evanston, IL, you'll get familiar with numeric, character, and date/time data types. You'll use functions to aggregate, summarize, and analyze data without leaving the database. Errors and inconsistencies in the data won't stop you! You'll learn common problems to look for and strategies to clean up messy data. By the end of this course, you'll be ready to start exploring your own PostgreSQL databases and analyzing the data in them.
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In the following Tracks

Certification Available

Associate Data Analyst in SQL

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SQL for Business Analysts

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  1. 1

    What's in the database?

    Free

    Start exploring a database by identifying the tables and the foreign keys that link them. Look for missing values, count the number of observations, and join tables to understand how they're related. Learn about coalescing and casting data along the way.

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    What's in the database?
    50 xp
    Explore table sizes
    50 xp
    Count missing values
    100 xp
    Join tables
    100 xp
    The keys to the database
    50 xp
    Foreign keys
    50 xp
    Read an entity relationship diagram
    100 xp
    Coalesce
    100 xp
    Coalesce with a self-join
    100 xp
    Column types and constraints
    50 xp
    Effects of casting
    100 xp
    Summarize the distribution of numeric values
    100 xp
  2. 2

    Summarizing and aggregating numeric data

    You'll build on functions like min and max to summarize numeric data in new ways. Add average, variance, correlation, and percentile functions to your toolkit, and learn how to truncate and round numeric values too. Build complex queries and save your results by creating temporary tables.

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  3. 3

    Exploring categorical data and unstructured text

    Text, or character, data can get messy, but you'll learn how to deal with inconsistencies in case, spacing, and delimiters. Learn how to use a temporary table to recode messy categorical data to standardized values you can count and aggregate. Extract new variables from unstructured text as you explore help requests submitted to the city of Evanston, IL.

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For Business

GroupTraining 2 or more people?

Get your team access to the full DataCamp library, with centralized reporting, assignments, projects and more

In the following Tracks

Certification Available

Associate Data Analyst in SQL

Go To Track

SQL for Business Analysts

Go To Track

Datasets

Stack Overflow Question CountsFortune 500 CompaniesEvanston 311 Help RequestsCourse Database Creation CodeCourse Database Entity Relationship Diagram

Collaborators

Collaborator's avatar
Chester Ismay
Collaborator's avatar
Mona Khalil
Collaborator's avatar
Adrián Soto
Christina Maimone HeadshotChristina Maimone

Data Scientist, Northwestern University

Christina Maimone leads Research Data Services at Northwestern University with the IT Research Computing Services group. She enables innovative research by providing data science, programming, and software development support for researchers. Through consultations, project collaborations, user groups, and workshops, the Research Data Services team ensures researchers have the resources, services, and skills they need to overcome challenges in their work. Christina regularly uses R, Python, and SQL but enjoys the challenge of using a wide range of programs and languages in her work. She has a PhD in political science and an MS in statistics from Stanford.
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Don’t just take our word for it

*4.3
from 56 reviews
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  • Павло Ф.
    3 months

    It is a well-structured course that is good for learning and knowledge refresh.

  • Sultan K.
    4 months

    Sometimes the correct solution gave an error, even when using a ready-made solution. Those. my decision and the teacher’s decision were the same, but the system did not allow me to proceed further. I had to reload the case to the previous one and back. That was the only way it helped.

  • Ben M.
    7 months

    I thought this was a good class. There was a large amount of overlap with the prior classes in the same tracks. It requires a bit of extra effort to understand the “why” for the things it teaches you to do; in other words, the motivation is not always obvious, even though the content itself is golden.

  • Vladyslav H.
    9 months

    The most engaging (and challenging!) course in the Data Analyst in SQL track.

  • Albert F.
    12 months

    Is very hard but like it!

"It is a well-structured course that is good for learning and knowledge refresh."

Павло Ф.

"Sometimes the correct solution gave an error, even when using a ready-made solution. Those. my decision and the teacher’s decision were the same, but the system did not allow me to proceed further. I had to reload the case to the previous one and back. That was the only way it helped."

Sultan K.

"I thought this was a good class. There was a large amount of overlap with the prior classes in the same tracks. It requires a bit of extra effort to understand the “why” for the things it teaches you to do; in other words, the motivation is not always obvious, even though the content itself is golden."

Ben M.

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