高级会计系列培训 | Big Data Analytics 9月2-3日 墨尔本面授

2017年08月23日 Seed职业培训


Big Data Analytics
weekend 2nd & 3rd September 2017 Melbourne (face-to-face)


In this course, you will learn to import data from a variety of sources, and summarize data quickly and effectively in Power Pivot to deliver KPI report in minutes. You will also learn to use DAX formula language, time-intelligence functions and cube formulas to analyse data.

Key Modules Covered in the Course

Tour of the Power Pivot

- Why Power Pivot is great for accountant
Import million rows data into Power Pivot
Learn how to create linked table
Consolidate variety Data Tables with Power Pivot
Build Relationship for data analysis
Add Slicer to a Power Pivot Pivot Table

Use DAX (Data Analysis Expressions) formula to analyse data

Construct efficient databases and designs for Power Pivot analysis
Understand Power Pivot formula engine
Use DAX formula to create calculated columns
Use calculated columns as new filterable items for analysis
Build “or” and “and” relation in DAX formula
Compare Measure with Calculated Columns
Hide Power Pivot fields from Pivot table

Advanced DAX functions

Introduce the dramatic benefits of “Portable Formulas”
Use one Measure inside another Measure
Learn to use functions that filters before it CALCULATEs
Learn to use functions that calculate data which ignore ALL filters
Use disconnected tables for sophisticated data analysis

Time intelligence with DAX
Introduce Time Intelligence and Calendar Tables
Calculate current month, current quarter, year to date (YTD) information
Compare values from various time periods

Case Study: KPI variance report

Build the basic measures for your report
Protect time intelligence functions from discontinuous dates
Use unlinked tables to toggle thousands/millions
Use unlinked tables to toggle between sales, costs and profits
Highlight key performance indicators with KPI icons

Combine PivotTable Power with Formula Flexibility

Convert Power Pivot PivotTables to CUBE formulas
Extract a Slicer selection with CUBERANKEDMEMBER
Evaluate a measure for multiple members with CUBESET
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