Menggunakan DAX di Power BI Desktop

Menengah
App Maker
Analis Data
Power BI

Jalur pembelajaran ini memperkenalkan Ekspresi Analisis Data (DAX) dan memberi Anda keterampilan dasar yang diperlukan untuk meningkatkan model data dengan perhitungan.

Jalur pembelajaran ini dimulai dengan menjelaskan model Power BI Desktop dan bagaimana cara meningkatkannya dengan perhitungan DAX. Kemudian menjelaskan bagaimana Anda bisa menulis rumus DAX dan jenis perhitungan model yang berbeda, termasuk tabel terhitung, kolom terhitung, dan pengukuran. Konteks evaluasi akan diperkenalkan, dan pelajaran selanjutnya menjelaskan cara menulis rumus DAX yang memodifikasi konteks filter. Terakhir, Anda belajar menulis ekspresi DAX dengan menggunakan fungsi kecerdasan waktu dan fungsi iterator.

Prasyarat

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Modul dalam jalur pembelajaran ini

In this module, you'll learn about the Power BI Desktop model structure, star schema design basics, analytics queries, and report visual configuration. This module provides a strong foundation on which you can learn to optimize model designs and add model calculations.

In this module, you'll learn how to write DAX formulas to create calculated tables, calculated columns, and measures, which are different types of model calculations. Additionally, you'll learn how to write and format DAX formulas, which consist of expressions that use functions, operators, references to model objects, constants, and variables.

By the end of this module, you'll be able to add calculated tables and calculated columns to your data model. You'll also be able to describe row context, which is used to evaluated calculated column formulas. Because it's possible to add columns to a table using Power Query, you'll also learn when it's best to create calculated columns instead of Power Query custom columns.

In this module, you'll learn how to work with implicit and explicit measures. You'll start by creating simple measures, which summarize a single column or table. Then, you'll create more complex measures based on other measures in the model. Additionally, you'll learn about the similarities of, and differences between, a calculated column and a measure.

By the end of this module, you'll learn about what the family of iterator functions can do and how to use them in your DAX calculations. Calculations will include custom summarizations, ranking, and concatenation.

By the end of this module, you'll be able to describe and work with filter context, which is used to evaluate measure formulas.

By the end of this module, you'll learn the meaning of time intelligence and how to add time intelligence DAX calculations to your model.

Occasionally, you might need to add many similar measures to your model. For example, consider that your model includes measures for sales, cost, and profit. You then want to create a report that shows year-to-date (YTD) sales, YTD cost, and YTD profit, in addition to prior year (PY) sales, PY cost, and PY profit. Adding numerous measures can be time-consuming and can clutter the Fields pane with an overwhelming number of fields. Instead of creating each YTD and PY measure, you can quickly add these measures to your model by creating a Data Analysis Expressions (DAX) calculation group.

In this module, you’ll solve three different business problems by optimizing the data model and creating Data Analysis Expressions (DAX) calculations. You’ll have an opportunity to create:

  • An airline on-time performance (OTP) report.
  • DAX calculations to scale measure values.
  • DAX calculations to dynamically classify products.