What is Data?
In our daily life, you can see everybody is dealing with information and data to analyze things. Data can be of different forms and can be converted to the required form. Data is everywhere. It is a collection of facts.
For example, we give information to the computer that can be understood by a person, and the information is converted into data in the computer because it treats the information as a character or as a symbol that has been encoded as binary sequence code, which is understandable by the computer.
Data: The word data is derived from the Latin word "Datum," which means something that is given. Data has no specific meaning, but it has a purpose.
It is the raw form of information, which needs to be processed, which means it is an unorganized fact. Data is useless until it is organized, and it is of simple form only. For data, there is always a need for further analysis, and data does not depend on the information. It Relies on Data.
The data comes in the form of numbers, figures, statistics, etc.
Example for data: Test result of a student.
To get a clear picture of data, it is also important to have a clear picture of information.
Information: The word Information is derived from the Latin word "information," which means formation or conception. Information has a specific meaning, and it has a purpose.
Information is an organized one that has meaning and can be easily understood by anyone. It is a processed form of data, organized and structured. Information is dependent on data and does not rely on the information. It is in the form of words, thoughts, and ideas. It always follows an order.
Example for information: Average score of a class.
In the given explanation for information and data, we may come across many differences, which are also important while learning.
In our daily life, we also come across the word BIG DATA, which matters a lot to us. As we are discussing data, it is also important to discuss data.
Big Data
Big Data is an enormous amount of data that consist of different data which are of different formats that are accessible to the user. Data may be in different formats like PDF, Audio, Video, text, Images, etc.
One of the best examples of Big Data is social media because a large number of posts of messages, photos, and videos are done that have been stored in the databases of social media servers.
Data can provide a good amount of Intelligence which means boosting machines that are intelligent behavior in the machine. AI and ML are very much related, and both are about constructing intelligent computer programs.
Data analysts do research on data which is a kind of big data.
Data can alone run a machine because when we feed or store information or task in the form of data in a machine or a robot, it follows the instructions which are given in the form of information.
Big Data is Boosting Intelligent Behaviour in Machine, which means data can change or can make a revolution in building modern society that is by developing robots that can perform tasks.
Every machine has its own memory, which will perform a certain task with the data available to it. Data always requires a space to store, and that can be allocated.
Advantages of Big Data
- It reduces the cost of storing and increases processing speed.
- To examine the current market situation.
- enhances artificial Intelligence and machine learning by providing data.
- It used in voice recognition devices like Alexa, Siri, etc.
Disadvantages of Big Data
- It is unstructured or unordered.
- Mismatch of required data can occur while finding.
- Big data takes more time to analyze things.
- It can have privacy issues for companies storing a large amount of data.
These are the major advantages and disadvantages of Big Data.
Different types of Data
There are two main types of data:
- Qualitative Data
- Nominal Data
- Ordinal Data
- Quantitative Data
- Discrete Data
- Continuous Data
1) Qualitative Data
Qualitative Data is non-numerical data. It can be used to classify or categorize something. This type of data is not depicted in numerical terms. Example, music and art.
- Nominal Data: It is used to label the variables without providing the numerical value for them. It is a subcategory of qualitative Data. Example, it defines the adjective, or the other example, is humans can have different eye color and hair color. Also, yes or no type of questions comes under the Nominal Data.
- Ordinal Data: The Data which follows a natural order of a specific type is known as Ordinal Data. Example, when we take feedback, we scale it from 0 to 5 or 0 to 10, which is an example of Ordinal Data.
2) Quantitative Data
The Data which can be measured and is not observable is known as Quantitative Data. For this kind of data, we can take a measurement that can be recorded numerically and can be represented. In quantitative Data, we can represent numerical data. Example, Daily Temperature.
In this Data, there are two types that are also important
- Discrete Data: The data which is having clear spaces in between them and the values. It cannot attain a range of values, and it can be represented in bar chart. Example, the number of chocolates in a box and the number of toys in a toy store.
- Continuous Data: This information which comes under a continuous series. Continuous data can be tabulated in a frequency distribution table, and the information is also in histography. Example: Daily temperature readings of a place and Daily calories burn in the human body.
Data is useful for data scientists who are specialized in data science, and it is also useful for data analysts.
In statistics, we use data to get an appropriate graph or a pie chart that will relate to which we are working.
Statistically, data can be defined as a set of information or a value. Data is a plural thing, and datum is a singular thing per the reference. The collection of Data plays a significant role in daily life.
As per the statistical analysis, Data is of two types:
- Primary data
- Secondary Data
Primary data
The Data that are collected for the first time through your knowledge by your personal experiences or the research on a particular thing is known as Primary Data. It is also described as first-handed data or raw Data that needs modification in the future.
For example, let us take a group of scientists who are working on a thing that has not existed in the present time and existed in the past, and nobody knows about it. The research on that gives some information, and that particular information is known as first handed information or primary data.
Secondary data
The Data which is collected already and that needs a modification, and that might require additional research work is known as Secondary Data. It is also referred to as second handed data. The second handed Data is mostly used at the times of essay writings in school, for study purposes, and for research purposes. Sometimes these kinds of data may have copyrights. This kind of Data is in finished forms.
For example, if we want to know the census report of our country for that, we need to research, which requires lots of money and patience. But we can access the census report in another way, that is, we can take it from government websites that already collected the information.
There are some major differences between Primary Data and Secondary Data that are as listed below:
- Time and money.
- In terms of definition.
- Reliability and sustainability.
- In terms of definition.
- The type of data obtained.
- In terms of examples.
These are the major differences between primary data and secondary data.
Conclusion
Hence, we concluded that Data is important for our lives, like in the economical business, social media companies, etc., so everyone tends to save data. In our systems or computers and mobile phones, we tend to save lots of data which is important to us. Most of the time, we depend on data or rely on data. There are lots of opportunities to get a job as a data scientist and data analyst. Mainly Data plays a special role in Big Data. Most social media platforms use this to store confidential data and have privacy.