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quintillion bytes of data which means an average person generates over 1.5 megabytes of data every second? Have you read any of the case studies involving how Netflix and Spotfy leverage big data for creating unique customerexperiences? They tell you how big data helped them create a mark in today’s world.
Relying on this data to power business decisions is like setting sail without a map. This is why organizations have effective datamanagement in place. But what exactly is datamanagement? What Is DataManagement? As businesses evolve, so does their data.
Some examples of areas of potential application for small and wide data are demand forecasting in retail, real-time behavioral and emotional intelligence in customer service applied to hyper-personalization, and customerexperience improvement. MasterData is key to the success of AI-driven insight.
For a successful merger, companies should make enterprise datamanagement a core part of the due diligence phase. This provides a clear roadmap for addressing data quality issues, identifying integration challenges, and assessing the potential value of the target company’s data.
This facilitates the real-time flow of data from data warehouse to reporting dashboards and operational analytics tools, accelerating data processing and providing business leaders with timely information. Impact on Business Facilitates data-driven decision-making through historical analysis and reporting.
It’s not just about fixing errors—the framework goes beyond cleaning data as it emphasizes preventing data quality issues throughout the data lifecycle. A data quality management framework is an important pillar of the overall data strategy and should be treated as such for effective datamanagement.
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