Avoid pitfalls while implementing a data quality strategy
For any organization, data is an asset. For a business intelligence (BI) project to be successful, it’s imperative to maintain the quality of the data. Your BI implementation partner requires strong data to help you generate breakthrough reports that can be transformed into actionable insights. Data quality can help you enhance your decision-making capabilities.
Yet data quality is a common issue in a BI landscape, and implementing a data quality strategy is not simple. In this Industry Perspective, you can explore some of the major characteristics that make up data quality and discover the 10 pitfalls to avoid while implementing a data quality strategy.
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