Time Series Analysis in SQL Server
| Course Details | ||||||||
|---|---|---|---|---|---|---|---|---|
|
||||||||
| Languages | ||||||||
|
||||||||
| Outcomes | ||||||||
|
||||||||
| Price & Terms | ||||||||
|
||||||||
| Technical | ||||||||
|
||||||||
| Specification | ||||||||
|
||||||||
Learn to convert, format and aggregate dates in SQL Server and use window functions for running totals, moving averages and period comparisons.
SQL Server has its own tools to prepare, aggregate and query time-stamped records. The lessons build dates from their parts, turn strings and time zone offsets into proper date and time types without failing on invalid input, roll records up to a daily or weekly grain, and use window functions to compute running totals, moving averages and the days elapsed between incidents, ending with a fraud analysis on client data.
What You Will Achieve
- Convert messy date strings and imported records into SQL Server date types without failing on invalid input
- Prepare dates for reports and summarize records by period with the help of a calendar table
- Produce summaries at several grouping levels in a single query
- Compare each period with earlier ones, track running totals and moving averages, and find peak overlap between events
Program Overview
Building, Converting and Formatting Dates
Creating dates and times out of their parts, splitting them apart again, and turning strings and offset values into proper types that SQL Server can query.
- Date parts, date math, leap years and rounding
- CAST(), CONVERT() and FORMAT() for reporting
- Calendar tables and joins against them
- Parsing strings, time zone offsets and invalid dates
Aggregating Time Series Data
Summarizing values over a time frame with standard and statistical aggregates, changing the grain of the data, and building several levels of totals at once.
- Distinct counts, filtered aggregates and the median
- Downsampling and upsampling to daily and weekly grain
- ROLLUP, CUBE and GROUPING SETS
Window Functions for Time Series Questions
Calculations that look across rows over time, closing with a fraud analysis built on a stream of client events.
- ROW_NUMBER(), RANK() and DENSE_RANK()
- Running totals, moving averages and window frames
- LAG() and LEAD() for prior periods and days elapsed
- Maximum overlap and a fraud analysis
Certificate Awarded (Paid)
Job Outlook
Date handling and window functions in SQL Server are used in reporting and data analysis work wherever sales, transactions or incidents are tracked over time and the questions concern trends, periods and changes between them.
Good for: Analysts working in SQL Server who need to answer date-based questions such as running totals, moving averages and month-over-month differences.
Keep in mind: Every function taught is SQL Server syntax; the ideas carry over to other SQL dialects, but the exact functions and their names may not.
Bottom line: A focused SQL Server course on date types, time-based aggregation and window functions that closes by applying them to a fraud analysis on client data.
Frequently Asked Questions
How does the course handle invalid date strings?
One chapter works with type-safe date functions that cope with bad input, then uses them to convert imported data with time zones and tests how those conversion functions perform.
Which window functions are covered?
ROW_NUMBER(), RANK() and DENSE_RANK() are contrasted, SUM() over a window builds running totals, window frames shape moving averages, and LAG() and LEAD() look at prior and future periods, including the prior three.
What is the fraud analysis at the end?
The closing lessons analyze client data for potential fraud: you build a stream of events, find the maximum level of overlap between them, and complete the analysis with the window functions covered earlier.
What role do calendar tables play in the lessons?
Calendar tables appear twice. The first chapter covers their benefits, lets you try one out and join data to it, and the aggregation chapter later uses one to downsample records.
User Reviews
Write your review
You must be logged in to post a review.
Reviews can only be posted by registered learners. Log in or create a free account, then you will return here to post.
There are no reviews yet.