Topic

Big Data

Why to be sceptical about the rise of AI startups

Barely a week passes without the announcement of yet another (seed) funding round for a startup, which claims to utilize “artificial intelligence”, “deep learning”, “machine learning” or “proprietary algorithms”. Algorithms, it seems, are at the core of almost all ventures these days – is that really the case?

How Parties can Leverage Data in this Year’s Federal Election Campaign

How predictable is voter behavior? Could big data really swing an election? The past US presidential campaign and the debate about the effectiveness of Cambridge Analytica have fueled the discourse about the role of data in election campaigning.

Data Science for Pharma – A Short Case Study

Open data in biomedicine is a gold mine that can strengthen innovation in pharmaceutical R&D. In combination with the right analytics, public data helps identify therapeutic targets and ligands, enhance clinical development, and boost portfolio management efficiency. The challenge is to purposefully integrate abundant and heterogeneous data scattered across data sources.

Big Data and the United Nations’ 2030 Agenda

The volume of data in the world is increasing exponentially, and with it the opportunity to take on the many environmental, social and developmental challenges facing the world. In other words, big data represents a catalyst for achieving the Sustainable Development Goals, as set by the United Nations (UN). The opportunity is there for governments, business, academia and civil society to drive forward this movement. And the UN is looking to be of enabling forefront of this movement.

Trend Detection – Delineating possibilities and utopia

In times where seemingly every second “The Economist” Special Report focuses on either Artificial Intelligence (AI) or Big Data, general expectations regarding current technological capabilities are higher than ever. Rightly so, as there have been so many notable advances in recent years. What does this mean for trend detection?

Cambridge Analytica: Beyond the Hype

The story immediately went viral: Big Data company Cambridge Analytica and its sophisticated psychographic models helped Donald Trump to secure the victory in the 2016 presidential election. The story played to all prevalent fears in the age of big data: privacy, microtargeting, behavioural steering. But now – with far less media buzz – the company admits that it was never really involved in the Trump campaign. What can we learn from this ‘scam’?

(Errors in) Communicating Statistics: Base rate neglect

When the results were in on last June 26th, most of those watching were surprised or even shocked that a majority of Britons had just voted to leave the EU. Even among those who cast their vote for “Leave”, many said they had not anticipated the vote to come out in their favour, and some even stated they had “not wanted it to happen”.

The Power of Open Data for Pharmaceutical R&D

Biomedicine is a central driving force of the rise of big data. High-throughput screening and the increase of computing power have led to the generation of vast amounts of data, opening new avenues for analytics.

Data Science Rapid Proof-of-Concept Projects

Data Science projects are complex and always inherit the risk of not being feasible. As opposed to large-scale IT projects though, there are ways to quickly act on ideas in a sandbox environment.