History of Data Analytics

1800 - PRESENT

HISTORY OF

DATA ANALYTICS

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17th

1654

BLAISE PASCAL

Probability Theory, Pascal's Triangle, Binomial Expansion

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19th

1812

Pierre-Simon Laplace

Analytical Theory, Distribution

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1835

Adolphe Quetelet

"Average man", Quantitive Analysis in Social Sciences, Physical Characteristics and Population

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20th

1936

Alan Turing

Turing Machine, Computer Theory

YouTube - Turing Explained

2000s

Predictive Analytics

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Numerous journals and books set the stage for ML and Predictions.

2010s

AI and Deep Learning

Major companies like Google release frameworks for ML

Read about TensorFlow.

Pierre-Simon Laplace

Early Analytical Techniques

Pierre was an influential 18th-century mathematician, that made majro advancements in probability theory and statistical inference. His work on Bayesian probability and the Laplace transform was the early groundwork for modern statistics. Today, his's methods are foundational in fields like data analytics and machine learning, proving how early statistical theories remain vital in contemporary analytical practices.

• Pierre-Simon Laplace developed key methods in probability and Bayesian statistics.
• His techniques, like the Laplace transform, are essential for modern data analytics.

Alan Turing

Architect of Early Computing

Alan Turing, a pioneering 20th-century mathematician, developed the concept of the universal machine, which put forth, the foundation for modern computing. His theoretical work on algorithms and computation underpins today's data processing and analysis technologies. His ideas are central to the development of complex analytical systems, illustrating how early computing theories and CPU development have profoundly influenced contemporary data analytics and artificial intelligence.

• Turing introduced the concept of the universal machine and CPU, which is fundamental to the design of modern computers.
• He formed the basis for the data processing and analytical systems used in today's technology.

Adolphe Quetelet

Statistics in Social Sciences

Adolphe Quetelet, a 19th-century Belgian statistician, introduced the concept of the "average man" and applied statistical methods to social phenomena. His work established the basis for analyzing social trends and human behavior by way of using statistical tools. Today, Quetelet's innovative approach is a vital part of social science research and data analysis, demonstrating how early statistical methods continue to be used in the study of societal patterns.

• Quetelet introduced the concept of the "normal distribution" for social data, showing traits often cluster around an average.
• His work helped apply statistical averages to predict and analyze social behaviors and trends.

Blaise Pascal

Pioneer of Probability Theory

Blaise Pascal, a 17th-century French mathematician, pioneered probability theory with innovations like Pascal’s Triangle. His methods for calculating odds and uncertainties heaviliy influenced the foundation for modern statistics. These early principles are very important in fields such as data analytics and machine learning, proving how Pascal’s work continues to influence contemporary analytical techniques.

• Pascal's Triangle is a triangular arrangement where each number is the sum of the two above it.
• Pascal's Triangle helps calculate combinations and probabilities in various math problems.