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Innovations in Analytics: Elevating Data Quality with GenAI

Towards AI

Last Updated on October 31, 2024 by Editorial Team Author(s): Jonas Dieckmann Originally published on Towards AI. Data analytics has become a key driver of commercial success in recent years. The ability to turn large data sets into actionable insights can mean the difference between a successful campaign and missed opportunities.

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Tabular Data Exploration and Modelling with LLMs

Towards AI

Last Updated on January 12, 2024 by Editorial Team Author(s): Cornellius Yudha Wijaya Originally published on Towards AI. Exploring the way to perform tabular data science activity with LLMImage developed by DALL.E Every data professional learning Python would come across Pandas during their work.

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Data Workflows in Football Analytics: From Questions to Insights

Data Science Dojo

Explore the role and importance of data normalization You might come across certain matches that have missing data on shot outcomes, or any other metric. Correcting these issues ensures your analysis is based on clean, reliable data.

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Meet the Fellow: Jonathan Colner

NYU Center for Data Science

Colner received his PhD in Political Science from the University of California, Davis in 2024, and has a keen interest in leveraging data science to understand local political institutions. Colner’s research focuses on developing innovative tools for measuring the policy-making activities and outcomes of city councils.

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2024’s top Power BI interview questions simplified

Pickl AI

Optimising Power BI reports for performance ensures efficient data analysis. Power BI proficiency opens doors to lucrative data analytics and business intelligence opportunities, driving organisational success in today’s data-driven landscape. How does Power Query help in data preparation?

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Expert Insights for Your 2025 Data, Analytics, and AI Initiatives

Precisely

With the rise of cloud-based data management, many organizations face the challenge of accessing both on-premises and cloud-based data. Without a unified, clean data structure, leveraging these diverse data sources is often problematic. AI drives the demand for data integrity.

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Advanced SQL for Data Analysis —Part 1: Subqueries and CTE

Towards AI

Last Updated on May 1, 2024 by Editorial Team Author(s): Carlos da Costa Originally published on Towards AI. In the next example, we will use a CTE to create a separate table containing cleaned data. To address this, we create a CTE to cleanse the data, removing the dollar signs and converting the price to a decimal format.