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Data Governance and Data Quality in HR
Merging two companies with different data platforms and business models presented significant challenges:
- Data Quality Standards During Transformation: Ensuring data quality amid new employees, changing roles, and ongoing data maintenance.
- Data Accessibility and Silos: Difficulty accessing files stored in SharePoint for analytics, leading to delays and inaccuracies.
- Scalability Issues: Existing data processes couldn't handle increasing volumes and diversity.
- Data Availability: Inability to perform timely analytics and reporting due to integration limitation
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Patient Visualization of Real-World Data for Digital Biomarker Discovery
In the pharmaceutical industry, identifying digital biomarkers is crucial for developing innovative treatments and improving patient outcomes. Real-world patient data offers immense potential, but the challenge lies in extracting meaningful insights from large, complex datasets. Without sophisticated analysis and visualization tools, valuable patterns may remain hidden, slowing the pace of medical advancements.
Traditional approaches to analyzing patient data have been slow, hampered by the sheer volume, variability, and sensitivity of the information. Effective visualization tools are essential to unlock the full potential of this data and push the boundaries of personalized medicine.
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Enhancing Customer Experience and Revenue with Data Science in e-Commerce
The client was facing significant challenges in delivering personalized experiences to their diverse user base. With millions of users browsing daily, understanding individual customer preferences and providing relevant recommendations was becoming increasingly complex. This lack of personalization was leading to lower conversion rates, high cart abandonment, and reduced customer lifetime value. Additionally, the client needed to optimize pricing strategies and improve inventory management based on customer behavior and demand forecasting.
