In our daily life, we see a lot of numerical as well as non-numerical figures being generated in some form or the other. Let us consider the simple case of the fitness bands that most of us are wearing. The bands record out heartbeat, the total number of steps that we take, the total calories we burn, the total distance we cover and a lot more.
Another example is that we are consistently posting out views on social media sites, talking about our experiences, events, giving reviews about various things and a lot more. All these things are a form of data.
What is data?
So, talking technically, data can be defined as a collection of facts such as some numbers, measurements, some type of observations or simply a description of things.
Types of data:
Data can be classified into two broad categories:
1. Quantitative Data:
Quantitative data can be defined as the numerical information that is, something that can be expressed in numbers.
Example, the ratings that we give to a movie like 1,2,3,4 or 5
Quantitative data is further of 2 types:
a. Discrete Data:
Discrete data is the one that can only take a finite number of values.
Example: 1,8, 12 etc.
Or in other words, these values can be in the form of whole numbers only.
b. Continuous Data:
Continuous data can have infinite number of values. In other words, it can comprise of decimal values.
Example: Temperature can take the values: 27.6 °C, 29.4 °C etc.
2. Qualitative Data:
Qualitative data is the one that gives us a description of something. This data is non-quantifiable, that is, it cannot be expressed in numbers.
Example: Our thoughts or views about something like, “It was a great movie!!”
Importance and uses of data:
We see that a huge amount of data is being generated every day and it is growing at an exponential rate since a long time. This data being generated which is being generate is raw but if it is analysed properly, it can help us get some useful insights which can help the organization and the society at large.
For example, a company that wants to boost its sales can study their various marketing channels and with the help of previously generated data, it can analyse which channel has been the most effective for increasing the sales and then work accordingly by splitting the marketing budged in an accurate manner thereafter.
Another example we have at hand is that of the pandemic COVID-19 that has hit the world. By studying the various patterns of the data generated by the most affected countries, the lesser affected countries took measures beforehand to minimize the spread of the pandemic like they analysed how many new hospitals would be required and stared working on building more hospitals and centers if they were short of it.
These few examples explain why data and its analysis is important and I would like to conclude by saying that data if used effectively and efficiently and if analysed properly can help us gain important information about the various patterns and trends that affect the societies, organisations and the society at large and helps us to work for the betterment of all.