Data Mining Data Modelling Data Quality Data Requirement 
Astera
JANUARY 23, 2024
Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. Traditional data warehouses with predefined data models and schemas are rigid, making it difficult to adapt to evolving data requirements.
The BAWorld
NOVEMBER 22, 2021
Completeness is a data quality dimension and measures the existence of required data attributes in the source in data analytics terms, checks that the data includes what is expected and nothing is missing. Consistency is a data quality dimension and tells us how reliable the data is in data analytics terms.
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