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SQL Serverで学ぶ時系列分析

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更新日 2025/11

SQL Serverで日時データの扱い方を学び、時系列分析に活用する方法を探る

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SQLData Manipulation

5時間

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60 演習

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コース説明

SQL Server には、時系列データの準備、集計、クエリに役立つ強力な機能がそろっています。本コースでは、日付の作成、文字列からの日付のパース（無効な文字列への対応を含む）、レポート向けの日付の書式設定を学びます。さらに、SQL Server に組み込まれた集計演算子やウィンドウ関数を使って、累積合計の計算、移動平均の算出、月次差分の表示といったビジネス上重要な課題を、実践的なサンプルデータで解決する方法を紹介します。データの見方を変えることで、難しい問題を解決できることも体験します。

前提条件

Intermediate SQL Server

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 dates

Break out a date into year, month, and day

Break a date and time into component parts

Date math and leap years

Rounding dates

Formatting dates for reporting

Formatting dates with CAST() and CONVERT()

Formatting dates with FORMAT()

Working with calendar tables

The benefits of calendar tables

Try out a calendar table

Joining to a calendar table

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2

Converting to Dates and Times

Here, we'll be converting strings and other inputs to date and time data types.

Building dates from parts

Build dates from parts

Build dates and times from parts

Build dates and times with offsets from parts

Translating date strings

Cast strings to dates

Convert strings to dates

Parse strings to dates

Working with offsets

Changing a date's offset

Using the time zone DMV to look up times

Converting to a date offset

Handling invalid dates

Try out type-safe date functions

Convert imported data to dates with time zones

Test type-safe conversion function performance

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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.

Basic aggregate functions

Summarize data over a time frame

Calculating distinct counts

Calculating filtered aggregates

Statistical aggregate functions

Working with statistical aggregate functions

Calculating median in SQL Server

Downsampling and upsampling data

Downsample to a daily grain

Downsample to a weekly grain

Downsample using a calendar table

Grouping by ROLLUP, CUBE, and GROUPING SETS

Generate a summary with ROLLUP

View all aggregations with CUBE

Generate custom groupings with GROUPING SETS

Combine multiple aggregations in one query

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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.

Using aggregation functions over windows

Contrasting ROW_NUMBER(), RANK(), and DENSE_RANK()

Aggregate window functions

Calculating running totals and moving averages

Running totals with SUM()

Investigating window frames

Calculating moving averages

Working with LAG() and LEAD()

Seeing prior and future periods

Seeing the prior three periods

Calculating days elapsed between incidents

Finding maximum levels of overlap

Analyze client data for potential fraud

Build a stream of events

Complete the fraud analysis

Wrapping up

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SQL Serverで学ぶ時系列分析

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