- Packt’s new report Data Quality in the Age of AI underlines the importance of prioritizing data quality in order to drive business growth with AI.
- With real-world case studies, the report offers strategies to ensure data is accurate, complete, consistent, and relevant.
- The report highlights how to embed a data culture within organizations by ensuring collaboration among teams, having the right decentralized governance practices, and using the right tools.
In the age of AI, data quality is paramount, yet many organizations struggle to define, measure, and maintain the quality of their data. This gap between the need for quality data and the challenges in achieving it, hinders the full potential of AI.
Packt’s new report Data Quality in the Age of AI emphasizes that data quality extends beyond mere accuracy. It involves ensuring that data is complete, consistent, timely, and relevant to the specific use case. The report highlights how the cost of poor data quality is substantial, potentially leading to inaccurate insights, biased algorithms, and missed opportunities.
Data Quality in the Age of AI equips data leaders, decision makers, and key stakeholders with the insights and strategies needed to navigate the complexities of data quality in the AI era.
With case studies from DoorDash and Checkout.com, the report highlights transformative effects of investing in a culture that values data quality. Here are some key strategies outlined for achieving this goal:
- Prioritize and integrate data quality: Tailor metrics to specific use cases, emphasizing quality over quantity. Enhance data quality from its source and distribute data collection responsibilities.
- Establish clear accountability: Define clear roles and responsibilities for data management and implement robust governance practices.
- Invest in collaboration and tools: Encourage cross-team collaboration to align objectives and invest in tools to streamline quality checks.
Data Quality in the Age of AI equips data leaders, decision makers, and key stakeholders with the insights and strategies needed to navigate the complexities of data quality in the AI era. By understanding the significance of data quality, the costs associated with poor data, and the strategies for improvement, readers can confidently lead their organizations in establishing a robust data culture. This report serves as a roadmap to unlock the full potential of AI, foster innovation, and gain a competitive advantage through data-driven decision making.
Ready to improve your content strategy? Contact Packt to license the report or explore partnership opportunities to create bespoke content that aligns with your organization’s unique needs.
