SQL databases have been around since the 1970s. Some of the smartest people in the world worked on making it easy to slice, dice, fetch and manipulate data quickly and efficiently. SQL databases have come such a long way that many developers and data scientists have lost track of what they can do with plain SQL.
In this course, you will learn advanced concepts and techniques for analyzing data using SQL. You will obtain hands-on experience in producing descriptive statistics, breaking a large query into multiple steps and samples, and cleaning and preparing data for analysis. You will learn how to produce aggregate results and subtotals, analyze a time series using cumulative and window frames, how to handle and fill missing data, and how to produce buckets and histograms.
After completing this course, you will be able to gain actionable insight from your data using nothing but SQL!
SQL databases have been around since the 1970s. Some of the smartest people in the world worked on making it easy to slice, dice...Show More
WHAT YOU'LL LEARN
Familiarity with advanced concepts and techniques for analyzing data using SQL
The ability to generate random data for training and benchmarking
Familiarity with datasets through descriptive statistics and histograms
Working knowledge of binning techniques and time series analysis
The ability to produce cumulative aggregation, subtotals, cubes, pivot tables, and data summaries for analysis
The ability to clean and prepare data with interpolation and linear regression
Familiarity with advanced concepts and techniques for analyzing data using SQL
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TAKEAWAY SKILLS
Content
2.
Basic SQL for Data Analysis
8 Lessons
Get started with basic SQL query structure, data generation, and creating CTEs for analysis.
3.
Descriptive Statistics
3 Lessons
Examine descriptive statistics using SQL for numerical and categorical series analysis.
4.
Grouping and Subtotals
4 Lessons
Apply your skills to aggregate, analyze, and generate detailed subtotals using SQL techniques.
5.
Running and Cumulative Aggregation
5 Lessons
Dig deeper into running and cumulative aggregation techniques using SQL window functions.
6.
Interpolation
4 Lessons
Focus on handling missing values, filling techniques, and linear interpolation for data accuracy.
7.
Binning
4 Lessons
Approach data binning, including equal-height and equal-width techniques, for effective categorization.
Certificate of Completion
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