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Calculations in Sigma

基础技能水平

更新时间 2025年12月

Build dynamic Sigma calculations to explore data, automate logic, and uncover trends with practical business examples.

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SigmaData Manipulation

2小时

12 视频

36 道练习

2,750 XP

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课程描述

Boost your analytics skills with the Calculations in Sigma course. You’ll learn to create dynamic, business-ready calculations that help teams explore data, automate logic, and surface meaningful trends. We’ll cover single-row logic with IF and SWITCH, conditional aggregations like SUMIF and AVGIF, rolling and cumulative analysis using window functions, and period-over-period comparisons to track performance over time.You’ll also learn how to enrich datasets using Sigma’s Lookup modal and understand how Sigma handles data types, grouped tables, and syntax. By the end, you’ll be ready to build accurate, efficient calculations and apply them to real business scenarios in Sigma.

先决条件

Introduction to Sigma

1

Foundations of Sigma Calculations

This chapter introduces the core building blocks that make Sigma calculations accurate and dependable. You’ll learn how syntax cues, data types, and logical expressions shape the results you compute. Then you’ll progress from IF and SWITCH logic to conditional aggregations and window functions to build calculations that answer real business questions.

Sigma data and column types

Understanding Sigma function rules

Troubleshooting function errors and warnings

Basic IF functions in Sigma

Flagging customer groups with If functions

Assigning categories with nested If functions

Standardizing naming conventions with Switch

Aggregate IF functions

Building conditional KPIs with CountIf and AvgIf

Leveraging logical columns in calculations

Window functions

Recognizing window functions in Sigma

Calculating rolling interest rates with MovingAvg

Calculating cumulative sums on un-aggregated data

2

Period-Over-Period Analysis

This chapter focuses on how Sigma streamlines period-over-period analysis for real business reporting. You’ll learn how to set up valid date fields, choose the right time granularity, and use Sigma’s automated MoM, QoQ, and YoY comparison tools. You’ll then expand into flexible techniques like DateLookBack and InDateRange to support rolling windows and custom time periods.

What is Period-over-Period analysis?

Understanding the purpose of PoP analysis

Understanding what PoP analysis needs to work

Adding a quick PoP comparison to a grouped table

Sigma’s PoP (Period-over-Period) comparison menu

Calculating new loans approved since last quarter

Comparing growth of loan types year-over-year

InDateRange formula for custom PoP analysis

Identifying upcoming loan maturities

Trailing 12-month account openings

3

Enriching Data with Lookups

This chapter explores how Sigma’s Lookup tools let you enrich tables by bringing in data from other sources without writing SQL. You’ll learn when to use lookups instead of joins, how to configure them correctly, and how to return aggregated values through the Lookup wizard. You’ll also learn to troubleshoot multiple-match issues and perform multi-key lookups for complex datasets.

Add Lookup modal

Understanding lookup requirements in Sigma

Configuring a Lookup in Sigma

Looking up account balances by customer

Labeling transactions with account type

Aggregating lookup results

Averaging credit scores for customer groups

Evaluating loan officer performance

Lookups with multiple key columns

Calculating monthly loan approval rates by type

Tracking customer credit journeys

Congratulations

Calculations in Sigma

课程完成

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