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Top 5 Challenges faced by Data Scientists

Pickl AI

Data Science is the process in which collecting, analysing and interpreting large volumes of data helps solve complex business problems. A Data Scientist is responsible for analysing and interpreting the data, ensuring it provides valuable insights that help in decision-making.

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Overcoming hurdles in end-to-end AI project design

Tableau

Principal Product Manager, AI, Tableau. Tableau Product Manager, Augmented Analytics. Data scientists often have a gap in understanding the nuances of what data represents and how it’s generated. Check out our conversation about AI projects on LinkedIn, or learn more about Tableau AI analytics.

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Overcoming hurdles in end-to-end AI project design

Tableau

Principal Product Manager, AI, Tableau. Tableau Product Manager, Augmented Analytics. Data scientists often have a gap in understanding the nuances of what data represents and how it’s generated. Check out our conversation about AI projects on LinkedIn, or learn more about Tableau AI analytics.

AI 98
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Expanding augmented analytics to help more people get answers from their data

Tableau

Chief Product Officer, Tableau. When it comes to asking questions of their data, how comfortable are most people in your organization? Even with a deep understanding of the business, if your users can’t find the right data or navigate dashboards to answer their questions, they aren’t likely to embrace analytics for making decisions.

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Expanding augmented analytics to help more people get answers from their data

Tableau

Chief Product Officer, Tableau. When it comes to asking questions of their data, how comfortable are most people in your organization? Even with a deep understanding of the business, if your users can’t find the right data or navigate dashboards to answer their questions, they aren’t likely to embrace analytics for making decisions.

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Predicting the Future of Data Science

Pickl AI

Summary: The future of Data Science is shaped by emerging trends such as advanced AI and Machine Learning, augmented analytics, and automated processes. As industries increasingly rely on data-driven insights, ethical considerations regarding data privacy and bias mitigation will become paramount.

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Three ways to help everyone make fast, data-driven decisions with modern BI

Tableau

Vice President, Product, Tableau. This is the second post in a three-part series about transformational modern analytics. In case you missed it, read the first post to learn how governance and data management enable your digital business. Bring advanced analytics capabilities to more problem-solvers with AI. Loreal Lynch.

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