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We have detailed information only on 30% of our customer base, which was obtained through a campaign. How should we handle this in data Warehouse?

This page of 'Ask a question' is linked to: Data Warehousing, Data Quality, Data Analysis/OLAP, BI platform Tools Evaluation, Customer Relationship,

You should have a separate table/data mart containing the records of only these 30% customers. This is with the assumption that 70% of the records do not have data of any value. Given that you have only 30% of the records having data, it will not be a basis large enough to apply averages etc. for the empty records.

Are there any good publications on Execution-MiH? Make it inactive

The only recommendation I have is the Dmreview.com, which covers many areas as mentioned in Execution-MiH.

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Expert's Answers → Prime Purpose of a Data Warehouse → Expert's Answers → Online data feed to Data Warehouse. → Expert's Answers → Data Warehouse- Big Bang or Incremental → Expert's Answers → Dimensional model vs Relational model → Expert's Answers → Interview sequence for DW business requirements → Expert's Answers → Pre-configured reports- Do they work? → Expert's Answers → Business Intelligence vs Business Performance → Expert's Answers → Data Warehouse vs Business Intelligence → Expert's Answers → Refresh frequency of a Data Warehouse → Expert's Answers → Integrating Data Marts to Data Warehouse → Expert's Answers → EAI vs Data Warehouse → Expert's Answers → Sponsorship for Data Quality. → Expert's Answers → Ownership of Data Quality Initiative → Expert's Answers → Operational Data Store vs Data Warehouse → Expert's Answers → Source of Enterprise Reporting → Expert's Answers → Data Warehouse Source System approach → Expert's Answers → Excel export to Data Warehouse → Expert's Answers → Captive ERP reporting capability → Expert's Answers → ROI of Data Warehouse → Expert's Answers → CRM and Data Warehouse → Expert's Answers → Partial Customer Information → Expert's Answers → Starting A Data Quality Program → Expert's Answers → Source system re-writing in parallel to Data Warehouse → Expert's Answers → Alignment between Source Systems and Data Warehouse → Expert's Answers → Maximizing usage of Data Warehouse → Expert's Answers → Data Profiling tool for Data Quality → Expert's Answers → Statistical sampling for Data Quality. → Expert's Answers → Simultaneous launch of source system and Data Warehouse → Expert's Answers → Security Matrix of a Data Warehouse → Expert's Answers → Data Quality program prioritization. → Expert's Answers → ETL phase taking too long → Expert's Answers → Should Data Warehouse wait for Meta-Data initiative → Expert's Answers → Mismatch in Source vs Data Warehouse reporting. → Expert's Answers → Data Warehouse vs Data Mart vs Data Mining → Expert's Answers → Data Quality Assurance vs. Risk Assessment → Expert's Answers → Data Quality Business Ownership in high-transition environment → Expert's Answers → Including informal and small systems in your Data Quality scope → Expert's Answers → When to use what level of detail for DQ assurance tracking? → Expert's Answers → Level of usage of Data Quality Practice Tool-Kit → Expert's Answers → Evolution path for Data Quality Practice Tool-Kit → Expert's Answers → Data Management Standards for Data Quality → Expert's Answers → Data Quality Practice Kit in work-flow and collaboration → Expert's Answers → Data Quality Policy- Level of Coverage →

Relevant links to this page

Prime Purpose of a Data Warehouse
Online data feed to Data Warehouse.
Data Warehouse- Big Bang or Incremental
Dimensional model vs Relational model
Interview sequence for DW business requirements
Pre-configured reports- Do they work?
Business Intelligence vs Business Performance
Data Warehouse vs Business Intelligence
Refresh frequency of a Data Warehouse
Integrating Data Marts to Data Warehouse
EAI vs Data Warehouse
Sponsorship for Data Quality.
Ownership of Data Quality Initiative
Operational Data Store vs Data Warehouse
Source of Enterprise Reporting
Data Warehouse Source System approach
Excel export to Data Warehouse
Captive ERP reporting capability
ROI of Data Warehouse
CRM and Data Warehouse
Partial Customer Information
Starting A Data Quality Program
Source system re-writing in parallel to Data Warehouse
Alignment between Source Systems and Data Warehouse
Maximizing usage of Data Warehouse
Data Profiling tool for Data Quality
Statistical sampling for Data Quality.
Simultaneous launch of source system and Data Warehouse
Security Matrix of a Data Warehouse
Data Quality program prioritization.
ETL phase taking too long
Should Data Warehouse wait for Meta-Data initiative
Mismatch in Source vs Data Warehouse reporting.
Data Warehouse vs Data Mart vs Data Mining
Data Quality Assurance vs. Risk Assessment
Data Quality Business Ownership in high-transition environment
Including informal and small systems in your Data Quality scope
When to use what level of detail for DQ assurance tracking?
Level of usage of Data Quality Practice Tool-Kit
Evolution path for Data Quality Practice Tool-Kit
Data Management Standards for Data Quality
Data Quality Practice Kit in work-flow and collaboration
Data Quality Policy- Level of Coverage

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