Data Science in Economics and Finance for Decision Makers
First published:
ISBN: 978-1-78272-394-3
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Introduction
Introduction
Foreword
Introduction
Digitalisation and transformation in economics and finance
Big data for policymaking in economics and finance: the potential and challenges
Quality matters: for insightful quality advice, get to know your big data
Statistics and machine learning: variations on a theme
Advanced statistical analysis of large-scale Web-based data
Text analysis
Prudential stress testing in financial networks
Data visualization: developing capabilities to make decisions and communicate
Data science in economics and finance: tools, infrastructure and challenges
Data science and machine learning for a data-driven central bank
Large-scale commercial data for economic analysis
Artificial intelligence and data are transforming the modern newsroom: a Bloomberg case study
Implementing big data solutions
A borderless market for digital data
Legal/ethical aspects and privacy: enabling free data flows
Assessing the trustworthiness of artificial intelligence
“Big tech”, journalism and the future of knowledge
Data is the new gold in modern society. Throughout history there have always been many gold prospectors and gold miners. Unlike gold, raw data does not itself have real value; to be truly important or useful data needs to be “mined”: put into context, analysed, assessed and used in documentation for policy proposals and policy actions.
The digital transformation of data into information, the expression of the associated knowledge this generates and the subsequent insights we can glean have revolutionised our economy, including the financial system. We often refer to the investigation of this digital data as the exploration of our digital footprints.
For the past 26 years of my professional career, I have worked with data that has been used as an input into policymaking decisions. I was part of the small team that created the European Central Bank from scratch, contributing to the development of the methodology, the collection of the necessary economic and financial data from all corners of the globe and the construction of the indicators for both national and European policymaking.
When I was approached by Risk Books to write a book on data science, I had to step back and
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