After doing these courses, I feel confident creating professional visualizations and dashboards
Shoebur RahmanProcurement Specialist, Giz Bangladesh
Course Description
SQL Server has a robust set of tools to prepare, aggregate, and query time series data. This course will show you how to build and work with dates, parse dates from strings (and deal with invalid strings), and format dates for reporting. From there, you will see how SQL Server's built-in aggregation operators and window functions can solve important business problems like calculating running totals, finding moving averages, and displaying month-over-month differences using realistic sample data sets. You will also see how taking a different perspective on your data can solve difficult problems.
Prerequisites
Curriculum
Course outline
1
Working with Dates and Times
This chapter covers date and time functionality in SQL Server, including building dates from component parts, formatting dates for reporting, and working with calendar tables.
- Building dates50 XP
- Break out a date into year, month, and day100 XP
- Break a date and time into component parts100 XP
- Date math and leap years100 XP
- Rounding dates100 XP
- Formatting dates for reporting50 XP
- Formatting dates with CAST() and CONVERT()100 XP
- Formatting dates with FORMAT()100 XP
- Working with calendar tables50 XP
- The benefits of calendar tables50 XP
- Try out a calendar table100 XP
- Joining to a calendar table100 XP
2
Converting to Dates and Times
Here, we'll be converting strings and other inputs to date and time data types.
3
Aggregating Time Series Data
In this chapter, we will learn techniques to aggregate data over time. We will briefly review aggregation functions and statistical aggregation functions. We will cover upsampling and downsampling of data. Finally, we will look at the grouping operators.
4
Answering Time Series Questions with Window Functions
In this chapter, we will learn how to use window functions to perform calculations over time, including calculating running totals and moving averages, calculating intervals, and finding the maximum levels of overlap.
S
Time Series Analysis in SQL Server
Course
Complete
