Progressive organizations recognize data as a strategic asset and rely upon it for critical decision making. Business intelligence spending has been steadily increasing and is forecast to be upwards of $16 billion worldwide in the next year. Major investment and effort are spent on data extraction, transformation and load (ETL) from source systems into data warehouses and data marts.
Still, incorrect decisions based on poor data can be disastrous. So how can we ensure that we are utilizing the proper data from the start? To be able to do so, we must be able to address the following data quality considerations:
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