What is Big Data?
Big data refers to larger and more complex datasets and is a concept that has grown particularly prominent with the rise of the internet. Big data is characterised by the three V's:
- Volume: The amount of data is enormous.
- Velocity: The speed at which new data arrives is very high.
- Variation: A large variety of data is available.
Big data definition
Big data is a difficult concept to define. But at its core, it is vast amounts of diverse data, with great variation, that constantly flows in.
What do companies use Big Data for?
What a company can use big data for depends largely on the nature of the business. Broadly speaking, the use of big data can be divided into the following major clusters:
- Product development: For example, large companies can use big data to predict and spot trends, emerging trends and demands, and respond by expanding with new products and the like.
- Customer experience and marketing: Companies can use big data, collected from social media, search engines and more, to market themselves in a targeted, more precise and personalised way.
- Maintenance: Through big data, companies can maintain machines, software and more based on errors, data and so on, thereby optimising operations and getting ahead of potential issues.
In other words, how you can use big data depends 100% on your company.
How is Big Data used in relation to marketing?
We will now go in depth on how big data can be used in connection with marketing.
As the use of social media and search engines grows enormously — often used multiple times and for hours by individuals every day — the amount of data generated from these sources increases. All of this data is collected and can be used in connection with marketing.
This enables companies to better target their ads in terms of audience and personalisation on social media and more. And for the consumer, it means they receive more targeted and personalised marketing. For some, a win/win — while others feel surveilled. A much-debated topic.
What is Thick Data?
In contrast to big data, thick data is characterised by its qualitative nature and its ability to provide insight into people's behaviour, attitudes, motivations and feelings.
Thick data provides a deeper understanding of the context in which data is generated -> it includes information about the circumstances under which data was collected, and the social, cultural and emotional factors that influence human actions. Compared to big data, it often contains raw numerical information without deeper understanding.
Thick data can therefore:
- Provide in-depth insights into people's behaviour and experiences
- Answer "why" questions by exploring the underlying causes and motives behind a given behaviour
- Be more oriented towards "what" and "how" questions and often focuses on patterns and correlations
These dimensions are important for achieving a deeper understanding of human aspects — something big data does not contain.
By combining "big data" with "thick data", companies can gain more nuanced insights and make better-informed decisions.
