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LLMs are enabling computers to understand and generate human-like text, making them indispensable in industries ranging from customer service to content creation. The global market for LLMs is expected to skyrocket from $1.59 billion%20market%20size%20in%20terms%20of,79.80%25%20during%202024%2D2030.) in 2023 to $259.8 billion by 2030, with North America alone projected to hit $105.545 million by 2030. The dominance of the top five LLM developers, who currently hold 88.22% of the market revenue,
Published: September 4, 2024
Predictive analytics uses historical data and techniques like statistical modeling and machine learning to predict future outcomes. It provides accurate forecasts, helping organizations predict trends and behaviors from milliseconds to years ahead. The global predictive analytics market was valued at 14.71 billion U.S. dollars in 2023 and is projected to grow from 18.02 billion U.S. dollars in 2024 to 95.30 billion U.S. dollars by 2032, with a compound annual growth rate (CAGR) of 23.1% during
Published: June 12, 2024
What are the central parts of any data-driven story, and how to apply the Gestalt laws to your data visualization reports? What role does context play in your data story? We are dwelling on these questions and providing you with a list of the best books and tools for stunning data visualization. Check it out! First, let us start from the central part of any good data story — the data-ink ratio. You’ve probably heard of or read something from Edward Tufte, the father of data visualization, who ha
Published: December 9, 2021
In his speech at Web Summit 2018, Yves Bernaert, the Senior Managing Director at Accenture, declared the quest for data veracity that will become increasingly important for getting sense of Big Data. In short, Data Science is about to turn from data quantity to data quality. It is true, that data veracity, though always present in Data Science, was outshined by other three big V’s: Volume, Velocity and Variety. For Data Analysis we need enormous volumes of data. Luckily, today data is provided n
Published: July 11, 2019
No matter how intelligent and sophisticated your technology is, what you ultimately need for Big Data Analysis is data. Lots of data. Versatile and coming from many sources in different formats. In many cases, your data will come in a machine-readable format ready for processing — data from sensors is an example. Such formats and protocols for automated data transfer are rigidly structured, well-documented and easily parsed. But what if you need to analyze information meant for humans? What if a
Published: May 8, 2019
