Data science, and all that jazz

  • May 23rd, 2018
  • Kate Land

What is data science?

A lot of people are talking about data science at the moment, but they aren’t always clear about what they mean. Here at Havelock London, we consider data science to be the activity of collecting and processing data, to gain insight and guide decisions, often within a business. A data scientist combines computing, statistics, and domain knowledge – in our case, knowledge of investment management – to identify where and how data can be useful.

You mean AI, big data, machine learning and all that jazz?

Not necessarily. Whilst the ‘data science’ term is new, what it is describing is not. Scientists have always made discoveries about the natural world from observations, and there is a long history of ‘quants’ working in finance and businesses employing analysts. What has changed is the amount of data that most businesses can now access, and an increased demand for people who can identify ways to leverage this data.
The technical activities data scientists are involved in vary with the domain, but the goal is usually to improve the effectiveness of decisions, or to automate them. In some areas useful contributions come in the form of technology that can capture and organise data. In other areas advances are made by better understanding complex data that already exists.

Ok, so what has data science got to do with long-term investing?

Let’s start by identifying some of the challenges faced by an investor:

Too much data, too much noise!

Someone making an investment decision today does not lack data; there are newspapers, TV channels, websites, businesses and individuals dedicated to providing data and commentary about the financial markets. What is difficult is knowing which pieces are relevant. Investors need to know how to filter the massive amounts of information at their disposal.

Vast amounts of uncertainty

No one knows exactly what is going to happen in the markets tomorrow, let alone over the next few years. Some events are more likely than others but there always remains the possibility that you will lose money. An investor needs to be able to understand the range of potential outcomes that they face.

As for the solutions… watch this space!

Kate Land

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