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Beyond the hype: Do you really need an LLM for your data?

CIO Business Intelligence

They promise to revolutionize how we interact with data, generating human-quality text, understanding natural language and transforming data in ways we never thought possible. From automating tedious tasks to unlocking insights from unstructured data, the potential seems limitless.

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The Data Behind Tokyo 2020: The Evolution of the Olympic Games

Sisense

Not only does it support the successful planning and delivery of each edition of the Games, but it also helps each successive OCOG to develop its own vision, to understand how a host city and its citizens can benefit from the long-lasting impact and legacy of the Games, and to manage the opportunities and risks created.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

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Data Visualization and Visual Analytics: Seeing the World of Data

Sisense

Our BI Best Practices demystify the analytics world and empower you with actionable how-to guidance. In a world increasingly dominated by data, users of all kinds are gathering, managing, visualizing, and analyzing data in a wide variety of ways. Visualizations: past, present, and future.

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10 Best Big Data Analytics Tools You Need To Know in 2023

FineReport

Big Data Tools are essential in managing and processing large data sets. The value of Big Data is not solely dependent on the volume of data available, but on how it is utilized. The Big Data ecosystem is rapidly evolving, offering various analytical approaches to support different functions within a business.

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Data trust and the evolution of enterprise analytics in the age of AI

CIO Business Intelligence

Without rock-solid data foundations, even the most advanced ML models merely provide artful analysis. Getting the right data governance significantly affects operational efficiency and risk as well. This capability has become increasingly more critical as organizations incorporate more unstructured data into their data warehouses.