How to download data from Domain Insights’ Snowflake account?
- Log in to Snowflake
Junge’s account (You may have your own login details):
Username: U_junge_1
Password: InvestorKit2153!!
- Go to Home>> Query Data
- Either follow this video (method 1) or follow the below steps (method 2).
- Use the below scripts to download each dataset, one line at a time. ❗️When copy-pasting the data, there might be format errors, be careful❗️
a. 20Y Historical Data
//Sold data access
SELECT * from DOMAIN_CLIENT_ANALYTICS.HISTORICAL.SOLD_SUBURB
SELECT * from DOMAIN_CLIENT_ANALYTICS.HISTORICAL.SOLD_POSTCODE
SELECT * from DOMAIN_CLIENT_ANALYTICS.HISTORICAL.SOLD_SA3
SELECT * from DOMAIN_CLIENT_ANALYTICS.HISTORICAL.SOLD_GCCSA
The suburb datasets are extremely large and Excel can’t handle them. It’s better to filter before downloading. Below is an example where I use “State” as a filter. Ask ChatGPT if you have any questions.
SELECT * from DOMAIN_CLIENT_ANALYTICS.HISTORICAL.SOLD_SUBURB
WHERE STATE = 'VIC’
//Rent data access
SELECT * from DOMAIN_CLIENT_ANALYTICS.HISTORICAL.RENT_SUBURB
SELECT * from DOMAIN_CLIENT_ANALYTICS.HISTORICAL.RENT_POSTCODE
SELECT * from DOMAIN_CLIENT_ANALYTICS.HISTORICAL.RENT_SA3
SELECT * from DOMAIN_CLIENT_ANALYTICS.HISTORICAL.RENT_GCCSA
//Days on market & Vendor discount data access
SELECT * from DOMAIN_CLIENT_ANALYTICS.HISTORICAL.DOMDISC_SUBURB
SELECT * from DOMAIN_CLIENT_ANALYTICS.HISTORICAL.DOMDISC_POSTCODE
SELECT * from DOMAIN_CLIENT_ANALYTICS.HISTORICAL.DOMDISC_SA3
SELECT * from DOMAIN_CLIENT_ANALYTICS.HISTORICAL.DOMDISC_GCCSA
//Rental yield data access
SELECT * from DOMAIN_CLIENT_ANALYTICS.HISTORICAL.RENTYIELD_SUBURB
SELECT * from DOMAIN_CLIENT_ANALYTICS.HISTORICAL.RENTYIELD_POSTCODE
SELECT * from DOMAIN_CLIENT_ANALYTICS.HISTORICAL.RENTYIELD_SA3
SELECT * from DOMAIN_CLIENT_ANALYTICS.HISTORICAL.RENTYIELD_GCCSA
b. Monthly data
//Sold data access
SELECT * from DOMAIN_CLIENT_ANALYTICS.SOLD.SOLD_SUBURB
SELECT * from DOMAIN_CLIENT_ANALYTICS.SOLD.SOLD_POSTCODE
SELECT * from DOMAIN_CLIENT_ANALYTICS.SOLD.SOLD_SA3
SELECT * from DOMAIN_CLIENT_ANALYTICS.SOLD.SOLD_GCCSA
//Rent data access
SELECT * from DOMAIN_CLIENT_ANALYTICS.RENT.RENT_SUBURB
SELECT * from DOMAIN_CLIENT_ANALYTICS.RENT.RENT_POSTCODE
SELECT * from DOMAIN_CLIENT_ANALYTICS.RENT.RENT_SA3
SELECT * from DOMAIN_CLIENT_ANALYTICS.RENT.RENT_GCCSA
//Days on market & Vendor discount data access
SELECT * from DOMAIN_CLIENT_ANALYTICS.DOMDISC.DOMDISC_SUBURB
SELECT * from DOMAIN_CLIENT_ANALYTICS.DOMDISC.DOMDISC_POSTCODE
SELECT * from DOMAIN_CLIENT_ANALYTICS.DOMDISC.DOMDISC_SA3
SELECT * from DOMAIN_CLIENT_ANALYTICS.DOMDISC.DOMDISC_GCCSA
//Rental yield data access
SELECT * from DOMAIN_CLIENT_ANALYTICS.RENTYIELD.RENTYIELD_SUBURB
SELECT * from DOMAIN_CLIENT_ANALYTICS.RENTYIELD.RENTYIELD_POSTCODE
SELECT * from DOMAIN_CLIENT_ANALYTICS.RENTYIELD.RENTYIELD_SA3
SELECT * from DOMAIN_CLIENT_ANALYTICS.RENTYIELD.RENTYIELD_GCCSA
//Vacancy rates data access
SELECT * from DOMAIN_CLIENT_ANALYTICS.MARKET_TRENDS.VR_SUBURB
SELECT * from DOMAIN_CLIENT_ANALYTICS.MARKET_TRENDS.VR_SA3
SELECT * from DOMAIN_CLIENT_ANALYTICS.MARKET_TRENDS.VR_GCCSA
//Domain Buyer Demand Index data access
SELECT * from DOMAIN_CLIENT_ANALYTICS.MARKET_TRENDS.BDI_SA3
SELECT * from DOMAIN_CLIENT_ANALYTICS.MARKET_TRENDS.BDI_CITY
//Domain Rental Demand Index data access
SELECT * from DOMAIN_CLIENT_ANALYTICS.MARKET_TRENDS.RDI_SA3
SELECT * from DOMAIN_CLIENT_ANALYTICS.MARKET_TRENDS.RDI_CITY
//Domain Listings
SELECT * from DOMAIN_CLIENT_ANALYTICS.MARKET_TRENDS.LISTINGS_GCCSA
SELECT * from DOMAIN_CLIENT_ANALYTICS.MARKET_TRENDS.LISTINGS_SUBURB
SELECT * from DOMAIN_CLIENT_ANALYTICS.MARKET_TRENDS.LISTINGS_SA3
How to download HtAG datasets from Snowflake? (02 May 25: pending full-access)
- Log in to InvestorKit Snowflake Account
Junge’s login details:
Username: jungema
Password: haw*chq8enh@WXU5qpu
How to download building approval data?
Here’s how to download Building Approval data at SA3 and SA2 level:
- Go to dataexplorer.abs.gov.au
- Search “Building Approval”
- From the search results, look for the below page:
- Click into the above link, you’ll enter the below page. From here change the filers to this:
Note: the Time Period can be any range you need, usually it’s last 1 month however sometimes you might need more months.
- Once the filters are applied, download the result as an Excel sheet as shown in the screenshot below.
- Then change SA3 in your filters to SA2, and download the result.
How to download Regional Internet Vacancy Index (Job Ad Numbers)?
- Go to
Internet Vacancy Index
- Scroll down to “Downloads” and expand “Data downloads”
- Download the XLS file named “Internet Vacancies, ANZSCO2 Occupations, IVI Regions - {month} {year}”
How to download State & GCCSA unemployment rates ?
- Go to the ABS Labour Force, Australia, Detailed page
- Scroll down slightly and find the dataset “Table 02. Labour force status by state, territory, greater capital city and rest of state (ASGS) and sex”. Download.
How to download LGA & SA2 unemployment rates?
- Go to JSA’s Small Area Labour Markets page.
- Go to the “Downloads” section.
- Download the SA2 Data Tables and the LGA Data Tables.
How to download home lending data by state?
- Go to the ABS Lending Indicators page
- Go to the “Data downloads” section and download the below 2 sheets:
- Table 4. Households; Housing finance; Owner occupiers; Total dwellings excluding refinancing; By state; New loan commitments; Numbers and values
- Table 14. Households; Housing finance; Investors; Total dwellings excluding refinancing; By state; New loan commitments; Numbers and values
How to update the non-Domain mastersheet (”000 Client Reports Update Master Dataset ”)
- Head to the first tab, and you’ll find the Update Checklist for this entire task (both this sheet and the Domain sheet)
- Untick all boxes in Column C, so you can start over the process.
- The first 14 items are tabs in this Dataset. Follow the videos in Column F to update each tab. The 15th item is for the Domain Dataset below.
- After finishing updating each tab, tick the box in Column C to market completion, and update Column G (Last update date) and H (Next data release date).
How to update the Domain mastersheet (”000 Client Reports Update Master Dataset - Domain Data 2024”)
As of Apr 2025, there are 19 tabs to be updated. Here’s an example of how to update the SA3 section in the first tab “20Y Sales Price_SA3&GCCSA”. The rest are very similar.
- Open the csv. file downloaded with the query DOMAIN_CLIENT_ANALYTICS.SOLD.SOLD_SA3.
- Save it as an xlsx. file.
- Select all cells and create a pivot table in a separate tab.
- Fill the PivotTable Fields as below:
- Filters = PROPERTYCATEGORISATION
- Columns = SA32021NAME
- Rows = Month
- Values = MEDIANPRICE_12M
- If you select “MONTH” as Rows, there would be a quarter level. Remove it.
- For Values here I’ve selected the 12m rolling median price. However, for other tabs, you may need to select 1m/3m/6m rolling ones or average instead of median. To find out, check one of the header cells, such as the one below:
Note:
5. In cell B1, untick “unit”, so the table only shows house data.
6. Expand the years to months, if not already.
7. Copy BOTH the SA3 name row AND the last month row (in the above screenshot, they would be Row 4 and 18), and paste them to the bottom of the tab we’re updating>
- Double-check if the newly pasted SA3 names match with the original SA3 name row (Row 2). This is because in some tabls there could be 1 or 2 extra or missing SA3s here and there. These SA3s are the national parks with close to 0 population, such as Blue Mountains - South.
- Once having made sure the SA3 names in the 2 rows match with each other, you can paste the prices to just beneath the previous month, and delete the newly added SA3 name row (Row 267 in the above screenshot).
- Then autofill the month numbers in Column A and B. And you get the updated SA3 data table like below:
Repeat this to update all tabs, just with different datasets.
How to update the region reports?
We currently use Prezi-based client reports. Before updating the region reports, make sure you have a free Prezi account registered with your InvestorKit email, and ask the Senior Research Analyst to share all region report files with you.
The manual below contains the updating instructions of almost everything. The only major change is the infrastructure downloading part.
How to upload a blog to the IK Website?
Loom Video: https://www.loom.com/share/14fa61aba09b42d98525641903de8352?sid=d52a25ea-2c93-424f-9287-fc541dc2d995
Tip: Play at 1.2x to 1.5x speed 😆
How to collect data and respond to suburb review requests (Helpdesk queries)?
- Follow this framework: RA_Help Desk Queries Framework
- You will need this sheet for calculation: RA_Help Desk Queries Calculator
- Find examples here. This is the Google Doc where the current research analyst puts all their response draftw.
How to quality control your work?
Follow the checklist on this page: link
How to decide whether to use house market data or unit market data for townhouse analysis?
Which market to use depends on the share if townhouses in the region/suburb’s unit market.
Step 1: Find the Census page of this region/suburb.
Eg. St Clair (SA), a suburb in Adelaide. You can google “St Clair SA, Census 2021”, and the below page will show up in search results:
Step 2: Scroll down to “Dwellings” - “Dwelling Structure”
Eg. the below is St Clair’s:
Step 3: Check how Semi-detached/Townhouse compares with Flat/Apartment.
- If Semi-detached/Townhouse is significantly higher than flat/apartment, then the unit market data should be dominated by townhouses, then we can use unit market data for townhouses.
- If flat/apartment is much higher than semi-detached, then the unit market data is dominated by apartments, then we should use house market data for townhouses.
Eg. In St Clair there are much more townhouses than apartments, we can just use unit market data.
Step 4: Double check for exceptions.
- If a specific townhouse’s price is closer to a similar sized house’s price, and is on a fairly large piece of land, we can use house market data regardless.
- If a townhouse has just 2 bedrooms, which is rare in houses, it’s probably more deemed as an apartment by everyone, so we use unit market data regardless.