5 Questions
What are some common causes of bad data quality at source?
Operational system defects, human errors, environmental stability
How can bad data quality be introduced during transformation and aggregation?
Defects, errors, incorrect algorithms
What is one of the consequences of poor understanding of source data?
Suboptimal data models
Why is master data management important in handling data from multiple sources?
To ensure consistent common definitions for all data
Which factor can lead to inaccurate analytics results?
Inconsistent data models
Explore the challenges related to data quality management including volume, variety, veracity of data, bad data introduction at the source, and issues with data transformation and aggregation. Understand how inconsistent data models and poor understanding of source data can impact data quality.
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