How can you ensure that your data model is flexible enough for domain changes?
Data models are essential for data science projects, as they define the structure, relationships, and constraints of the data. However, data models are not static, and they may need to adapt to changes in the domain, such as new business requirements, data sources, or user needs. How can you ensure that your data model is flexible enough for domain changes, without compromising its quality, performance, and usability? Here are some tips to help you design and maintain a robust and adaptable data model.
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Pawan ThakareCorporate Data Analyst | Data Analyst at Adani Corporate House | Microsoft Certified: Power BI Data Analyst Associate…
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Rifan KurniaVP of Data | Data & CyberSec Hybrid | Cybersecurity & Applied Statistics MSc
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Linda O.Data & Business Insights Analyst | Transforming Data into Actionable Insights that Drive Business Growth