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Organizations today face overwhelming amounts of data, with many failing to utilize 60% to 73% of it for analytics. Poor data quality can lead to significant financial losses, averaging $12.9 million annually for companies. Effective data management processes are essential to ensure that the data used for analytics is valid and meaningful, preventing disorganization and conflicting datasets.
Transitioning to comprehensive data systems like Microsoft Dynamics can help organizations consolidate and standardize their data. Master Data Management (MDM) is crucial for maintaining data accuracy and consistency, especially during mergers and acquisitions. By focusing on data quality, governance, and integration, companies can enhance their AI and Business Intelligence (BI) initiatives, ultimately driving better decision-making and operational efficiency.
• Organizations lose $12.9 million annually due to poor data quality.
• Master Data Management ensures data accuracy and consistency across systems.
Data management involves defining processes to ensure data validity and meaningfulness in analytics.
MDM is a business initiative that ensures uniformity and accuracy of shared data assets.
BI initiatives rely on high-quality data to drive informed decision-making and operational efficiency.
Microsoft's Intelligent Data Platform combines AI with analytics to help businesses govern their data effectively.
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