Power Pivot sample workbook - NSW Residential Property Price Growth

Key Points

  • Power Pivot is a FREE Excel Add In from Microsoft
  • Download this sample Power Pivot model and have some fun analysing property price trends in NSW
  • The Power Pivot model demonstrates how a simple data model can provide insight and usability
  • The model demonstrates the basics of Power Pivot but also some more complex DAX calculations

Kick-start your understanding of Power Pivot with this sample model from CMBI. The model uses 25 years of NSW property sales data and demonstrates some of the key features of Power Pivot.

About CMBI

Download the sample Power Pivot model

CMBI's Colin McGowan has developed this NSW Residential Sales Property Growth Power Pivot model using Excel 2010 with the Power Pivot 2012 SP1 Add In which is FREE from Microsoft. For your convenience you can download a pre-converted Excel 2013 model too.

Introduction to NSW Residental Sales Property Growth Power Pivot Model

The NSW Residential Sales Property Growth Power Pivot model demonstrates some key features of Power Pivot modelling, DAX calculations, and Excel visualisation using data that is engaging yet relatively straightforward to understand. The workbook contains a number of worksheets which are briefly described below.

Overview sheet

The Overview sheet allows you to analyse sales property growth for houses, units, or all property in NSW for any period between 1991 and Q1 2015. The data is grouped by Local Government Area (LGA) and can be filtered by Rings which are defined by their proximity to the CBD. The Overview sheet uses the following features

  • Excel Pivot Table linked to Power Pivot model
  • Conditional formatting linked to Pivot Table measure in Power Pivot model
  • DAX time intelligence and advanced DAX calculations using CALCULATE statement for measures and calculated columns
  • Slicers linked to the Pivot Table which act as parameters for viewing different data cuts


NSW Property Trends in Excel Pivot Table with conditional formatting

Price Trend sheet

The Price Trend sheet allows you to visualise growth for one of more LGAs. The Excel Chart is linked to the Power Pivot model via a Pivot Table in a hidden sheet. Interact with the Slicers to add or remove one or more LGAs


NSW Property Trends in Excel Pivot Chart

Growth sheet

The Growth sheet uses Excel conditional formatting to provide a Heat Map effect for visualising growth for NSW Residential Property. The user can adjust the time period or see more LGAs in the table on the right of the sheet by interacting with the Slicers


NSW Property Growth statistics in Excel Pivot Table with heat-map style conditional formatting

Time Intelligence sheet

Time Intelligence is a key feature of Power Pivot. DAX Time Intelligence functions are used in many of the calculations in this model. This Time Intelligence sheet makes it easier for users to see the behaviour of different combinations of DAX Time Intelligence functions against a single value


NSW Property Growth statistics using DAX Time Intelligence functions

Technical details about the sample Power Pivot model

The workbook is unprotected and you are free to add your own visualisations and calculations to the model. If you have any feedback about the model or notice any errors or points for improvement please contact colin@cmbi.com.au

Power Pivot model data

The model uses data from the NSW FCS Government Department website. You can obtain the original data here. CMBI have manipulated this raw data using Power Query to create the final tables seen in the model. These tables are:

  • Area Region - which is a list of geographic regions at various levels within NSW
  • Median Sales Price Residential Property - this table contains all the median sale price data for each quarter in the period and for each Area Region
  • Date - a distinct list of quarter end dates used for the median sale price data

The median price data in the model is non-aggregatable. It is not valid to add two median values together. Instead the calculations focus on comparing these median values over time. Although we cannot aggregate the median prices, the Area Region table contains geographic regions at various levels and the median prices for these aggregate region-levels are contained in the data set as pre-calculated values.


NSW Property Growth Excel Pivot Pivot Model Diagram view

Power Pivot model calculations

The model defines a number of calculations using DAX. DAX is similar to Excel formulas but more powerful for advanced modelling scenarios. You can inspect the formula behind any of the values in the Pivot Tables by opening the Power Pivot window and selecting the Median Sales Price Residental Property sheet in the Data View from the Home tab. The bottom panel of this screen shows all the calculations and clicking on one will show the DAX formula in the formula bar


Power Pivot window showing a DAX calculation in the formula bar

DAX formulas are very powerful and can be used to solve most modelling and analytics requirements. Some features include

  • Time Intelligence which can be used to calculated YTD, parallel periods, growth, and opening and closing balances
  • CALCULATE statement that can manipulate the context of a calculation for complex set based analysis or advanced comparisons and correlations
  • Text manipulation to add groupings, concatenate columns, or create additional descriptive attributes
  • Most Excel formulas can be translated into DAX formulas. DAX also has capability beyond standard Excel formulas.


Power Pivot formula bar showing DAX calculation using the CALCULATE statement

Want to learn more about Power Pivot?

CMBI's Colin McGowan provides onsite training for all levels of Power Pivot users and developers. Please contact colin@cmbi.com.au to arrange a training sesssion or learn more about training and mentoring options with Power Pivot and other BI tools

About CMBI

CMBI designs and develops business intelligence and analytics solutions for clients in Sydney and regional NSW. CMBI technology expertise includes Power BI, Power Pivot, Excel, SQL Server, Analysis Services, SharePoint BI, and Tableau

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