Simply put, data analysis is the process of discovering valuable information through evaluation. The process involves inspecting, cleaning and transforming data, as well as modelling it.
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Big data
In the early 2000s, the concept of Big Data, which is data that is large, complex or fast that it’s difficult to process with traditional methods, gained momentum.
- Volume – organisations collect data continuously. It used to be a big problem storing data, but now it is easy and cheap.
- Velocity – Data received must be processed in a timely fashion. The Internet of Things is growing, which means that data can be coming in at an unprecedented rate.
- Variety – organisations collect and store data in many different forms. These range from structured data (traditional numerical data) to unstructured data, such as emails, videos and audio.
Metadata
It is a type of data that contains information about another data, like an image. You can find out this information by right-clicking a file within a folder, then selecting “Get Info”. This will give you details such as the file type, size, and date of creation.
Real-time data
Data is displayed as soon as they are acquired. This is best demonstrated by a stock ticket that provides real-time information about the most active stocks.
Quantitative data and qualitative data
Quantitative data, also known as structured data, may be displayed as a traditional database with rows and columns. Qualitative data, also known as unstructured information, is any other type of data which does not fit into columns and rows. This can include images, text and videos.