What is Data Science?
The meaning and added value of data science
- Article
- Data Science
Everywhere at events and online, stories are told about what 'data science' is all about. Definitions are anything but consistent. They go from 'getting something of value out of data' to 'it's basically the same as statistics'. And a Data Scientist is 'a data analyst who lives in Silicon Valley' or 'a socially skilled IT person who does something with data'. But what is it really?
Let's start with the 'why's'
In what ways can you really extract value from 'Data Science stuff' for your organisation? Knowing this allows you to draw a definition and actually do something with it.
What things would you like data scientists to do for you? We call these things together Data Science.
When Data Science can provide added value: 6 scenarios
1. You want to support your strategic management with decision making.
A Data Scientist can generate insights an Analyst could not come up with. He uses advanced technical and mathematical techniques for this.
Data Science can also make the difference when making terms that are difficult to express in numbers measurable. For example, many organisations have difficulty managing 'the customer experience', or 'empathy'.
2. You want to create a tool or system that can (automated) do something that cannot be done in real-time or on a large scale by humans.
Think, for example, of a system for recommendations or automatic hazard recognition from image recognition. You can also automate manual actions using scripts.
3. You want to work with huge amounts of data.
When there is too much data to process with ordinary equipment and programs, you are dealing with big data. To work with big data, you need more advanced techniques.
4. You want to see connections one cannot see with the naked eye.
Even if you know many different things about a certain event or customer, you can call it big data. A Data Scientist can make connections from this an Analyst cannot see with his normal toolbox.
5. You want to work with unstructured or special types of data.
- Think about:
- Studying and exploring available data for analysis or infrastructure
- Getting big insights from small amounts of data
- Analyses of unstructured texts or geodata
- Insights from (moving) images or 3D images
6. You want to create advanced visualisations that are not possible with Data Analysts' usual toolboxes.
Think about:
- Process mining
- Interactive visualisations and forecasts
- Visualisation based on unstructured data
What is Data Science? The definition
If we want to summarise these needs and activities into a definition or meaning of 'Data Science', we arrive at the following:
Data Science are applications with data at the intersection of domain/organisational knowledge, statistics, and IT.
Getting started with Data Science
Do you recognise the situations mentioned above where Data Science can offer added value, but you don't have the right people available? Or do you want help choosing the right approach?
Our Data Scientists are happy to get to work for you. Contact us directly for more information.
Receive data insights, use cases and behind-the-scenes peeks once a month?
Sign up for our email list and stay 'up to data':