Best practices for combining piblic dis relief data with socieconimic metrics
Hy everyone! I am participatin in a university hachathon where we are analyzing public disaster relief funds alongside socieconomic indicators like HDI and population size.
As a data analysis student, I`d like to ask: What are the best practices or recommended data modeling techniques in Qlik Sense to combine public financial records with demographic indicators without causing synthetic keys or circular references? Thanks in advance!
Identify the grain – Decide the level of each dataset, e.g., relief transactions by Country–Year and socioeconomic data by Country–Year.
Create a unique key – Build a controlled key such as:
AutoNumber(Country & '|' & Year) as GeoYearKey
Create a Geography/Socioeconomic dimension – Keep fields such as Country, Region, HDI and Population in one dimension table.
Keep disaster relief as a fact table – Store Relief Amount, Disaster Type, Date, Beneficiaries, and GeoYearKey separately.
Use only one association key – Avoid having Country, Region and Year simultaneously connecting multiple tables, which can create synthetic keys.
Avoid unnecessary JOINs – Prefer Qlik's associative model or ApplyMap() for simple lookups to prevent row multiplication and data duplication.
Check the Data Model Viewer – Look for $Syn tables and circular references. Rename/drop unintended common fields.
Validate your measures – Test KPIs such as Relief per Capita, Relief vs HDI, Total Relief by Region, and Relief by Disaster Type to ensure the associations produce correct results.
Identify the grain – Decide the level of each dataset, e.g., relief transactions by Country–Year and socioeconomic data by Country–Year.
Create a unique key – Build a controlled key such as:
AutoNumber(Country & '|' & Year) as GeoYearKey
Create a Geography/Socioeconomic dimension – Keep fields such as Country, Region, HDI and Population in one dimension table.
Keep disaster relief as a fact table – Store Relief Amount, Disaster Type, Date, Beneficiaries, and GeoYearKey separately.
Use only one association key – Avoid having Country, Region and Year simultaneously connecting multiple tables, which can create synthetic keys.
Avoid unnecessary JOINs – Prefer Qlik's associative model or ApplyMap() for simple lookups to prevent row multiplication and data duplication.
Check the Data Model Viewer – Look for $Syn tables and circular references. Rename/drop unintended common fields.
Validate your measures – Test KPIs such as Relief per Capita, Relief vs HDI, Total Relief by Region, and Relief by Disaster Type to ensure the associations produce correct results.
Hi, in most cases, Qlik Replicate manages these control tables automatically as part of its normal operation, so manual flushing or maintenance usually isn’t necessary. However, it’s worth checking the specific table behavior and retention settings for your Replicate version and configuration before making any changes. www voyafinancial com
Thank you so much, Chanty4u! This step-by-step model is extremely helpful for our project structure. Creating the concatenated key with AutoNumber and keeping dimensions separated will definitely keep our model clean and performance-friendly. I appreciate your expert guidance!
