This document discusses the differences between data quality and quantity for web analytics. It notes that data quality problems can include configuration issues, missing tracking codes, incomplete ecommerce data, and conflicting filters, while data quality inconsistencies involve inconsistent tagging, discrepancies, malformed filters, and misaligned goal assignments. Data quantity issues comprise irrelevant data, insufficient data, performance impacts, querying limitations, and challenges with data capture, storage, and statistical significance. The document also provides information about a web analytics meetup group that meets monthly in Canberra, Australia.

1. Web Analytics
Quantity vs Quality
3rd
Wednesday of the Month - August
http://wawcanberra.com

2. Data Quality
• Problems:
– Configuration Issues
– Missing Tracking Code
– Missing eCommerce Data
– Conflicting Filters
• Inconsistencies:
– Inconsistent Tagging
– Data discrepancies
– Malformed Filters
– Goal Assignment misalignment

3. Data Quantity
• Irrelevant data.
• Insufficient data
• Performance Issues
• Querying limits
• Data Capture and storage
• Statistical Significance

4. http://wawcanberra.com
• Meet 3rd
Wednesday of the month in
Canberra.
• Twitter #wawcanberra
• Give a Talk:
– http://wawcanberra.com/give-a-talk/
• Sponsor Us:
– http://wawcanberra.com/sponsor-us/