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Reporting in SQL

Learn how to build your very own dashboard by applying all the SQL concepts and functions you have learned in previous courses.

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4 Hours15 Videos54 Exercises21,453 Learners4450 XPSQL for Business Analysts Track

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Course Description

Become a master at building complex reports! In this course, you will apply all the SQL concepts and functions you have learned in previous courses to build out your very own dashboard. By navigating through an Olympics database, you will become an expert data explorer and learn how to understand novel database quickly and effectively. Since data is never perfect, you will gain valuable strategies to deal with real-world issues commonly found with SQL, including how to remove data duplication and how to turn messy data into clean, organized reports. Lastly, you’ll conquer complex calculations using window functions and layered calculations, all within the same report. This is a perfect class for anyone who will be commonly pulling data from databases and is a great complement for those who use R or Python for data science.

  1. 1

    Exploring the Olympics Dataset

    Free

    Before you can start building out reports to answer specific questions, you should get familiar with the data. In this chapter, you will learn how to use E:R diagrams and data exploration techniques to get a solid understanding of the data to better answer business-related questions.

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    Case study
    50 xp
    Identifying the base report
    50 xp
    Building the base report
    100 xp
    Athletes vs events by sport
    100 xp
    The Olympics dataset
    50 xp
    Planning queries with an E:R diagram
    50 xp
    Age of oldest athlete by region
    100 xp
    Number of events in each sport
    100 xp
    Exploring our data
    50 xp
    Exploring summer_games
    100 xp
    Validating our query
    100 xp
    Report 1: Most decorated summer athletes
    100 xp
  2. 2

    Creating Reports

    Queries can get large, fast. It's important to take a logical approach when building more complicated queries. In this chapter, you will take a step-by-step approach to plan and build a complex query that requires you to combine tables in multiple ways and create different types of fields.

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    Planning the query
    50 xp
    Planning the SELECT statement
    50 xp
    Planning the filter
    100 xp
    Combining tables
    50 xp
    JOIN then UNION query
    100 xp
    UNION then JOIN query
    100 xp
    Creating custom fields
    50 xp
    CASE statement refresher
    100 xp
    BMI bucket by sport
    100 xp
    Troubleshooting CASE statements
    100 xp
    Filtering and finishing touches
    50 xp
    Filtering with a JOIN
    100 xp
    Filtering with a subquery
    100 xp
    Report 2: Top athletes in nobel-prized countries
    100 xp
  3. 3

    Cleaning & Validation

    Although it would be nice, data in the real-world is rarely stored in an ideal way. Simply put: data can get messy. In chapter 3, you will learn how to deal with this messy data by fixing data type issues, cleaning messy strings, handling nulls, and removing duplication.

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    Converting data types
    50 xp
    Identifying data types
    100 xp
    Interpreting error messages
    100 xp
    Using date functions on strings
    100 xp
    Cleaning strings
    50 xp
    String functions
    100 xp
    Replacing and removing substrings
    100 xp
    Fixing incorrect groupings
    100 xp
    Dealing with nulls
    50 xp
    Filtering out nulls
    100 xp
    Fixing calculations with coalesce
    100 xp
    Report duplication
    50 xp
    Identifying duplication
    100 xp
    Fixing duplication through a JOIN
    100 xp
    Report 3: Countries with high medal rates
    100 xp
  4. 4

    Complex Calculations

    The value of reporting really shows when presenting not-so-obvious insights through complex calculations. In this chapter, you will learn how to build more complicated fields by leveraging window functions and layered calculations. You will gain hands-on experience building two advanced calculations in particular: the percent of a total calculation and the performance index calculation.

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    Building complex calculations
    50 xp
    Testing out window functions
    100 xp
    Average total country medals by region
    100 xp
    Most decorated athlete per region
    100 xp
    Comparing groups
    50 xp
    Volume vs efficiency metrics
    50 xp
    Percent of gdp per country
    100 xp
    GDP per capita performance index
    100 xp
    Comparing dates
    50 xp
    Month-over-month comparison
    100 xp
    Week-over-week comparison
    100 xp
    Report 4: Tallest athletes and % GDP by region
    100 xp
    Course summary
    50 xp

In the following tracks

SQL for Business Analysts

Datasets

Course Database Entity Relationship DiagramCourse Database Creation CodeAthletesCountriesCountry StatsSummer GamesWinter Games

Collaborators

sara-billen
Sara Billen
mona-kay
Mona Khalil

Prerequisites

Data Manipulation in SQL
Tyler Pernes Headshot

Tyler Pernes

Learning & Development Consultant

As a learning & development consultant by day and a freelancer by night, Tyler has two clear passions in life: teaching and data. After receiving a bachelor's in biophysics at Johns Hopkins University, he moved into the world of data and began working in the ad-tech industry, leading two business intelligence teams in the process. He specializes in SQL, data visualization, data modeling, and data analysis.
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