Have you ever filled forms for any online mock test? If yes, then you may experience that the website is asking for some basic details of yourself like your name, age, qualification, location etc.
Have you ever bought anything online? If yes, then you must have provided your name, address and payment details.
I guess almost everyone of us has at-least one account in any social networking site or any email service providing site. To open that account you have given facts about yourself like your name, DOB, gender, hobbies etc.
Now the questions which may strike in our mind are where these facts and figures are going into or what those are used for.
These unorganized facts of every user of individual website, which may be shopping website or social networking site or any other email provider site, are known as Data. In our everyday life, whenever you start any online activity, you may experience that you are compelled to provide data regarding yourself.
Therefore in the definition it can be said that Data is a collection of unorganized facts, likely a number, any word, observation etc. that can be arranged in an organized way so that computer can process.
In general English, data is simply a synonym for information. But in computing purpose data only means machine readable information as opposed to human readable information.
Human Readable vs. Machine Readable information
Human readable information is such kind of information, say for example- an image or a block of text etc., that only human can study and interpret. It may or may not have uniform structure.
On the other-hand, Machine readable information refers to a set of information which can be processed by computer programming. Computer program is a set of instruction that can take machine readable information as an input, and gives us output after processing the input data. Eventually we also call computer program as Software. To maintain uniformity in the performance of those software worldwide, machine readable information must have arranged in some uniform structure.
Classification of Machine Readable information
In computer world we can divide the data into following categories:
Personal Data: It is anything that depicts you. Your DOB, location, email id, phone no etc. all these data are personal data. There are a lot of companies, who collect personal data from various social or shopping sites, to provide you personalized suggestions after analysing those. In many of the cases, these data are also sold to other companies mainly for advertising and competitive research purpose.
Transactional Data: It is a kind of information generated by monitoring and storing every activity of each potential customer who visits those websites. Transactional data helps to plan the marketing strategies.
Web Data: When users search for any information in any search engine, it gives a list of some related websites. The users visit only those websites which are relevant to them, and retrieve information for analysing and frame their marketing strategies. These data accumulatively are called Web Data. It is very much useful for monitoring potential customers, studying the actions of competitors, creating new apps etc.
Sensor Data: It is set of facts which are sensed from physical environment. With the help of IoT (Internet of Things) devices sensor data can be generated to analyse the characteristic behaviour of any physical or anthropogenic events. Say for example- sensors of weather instruments usually record data for various weather components like temperature, relative humidity, wind speed and direction etc., and send those to data center for analysing purpose.
Needs for Data Collection
Data collection is a process of collecting and measuring the information.
- Data collection helps to study the market scenario.
- With the help of Data collection process companies are able to track the demand and supply of various commodities.
- It also helps to adopt new marketing strategies to increase their business revenue.
- It is very helpful for establishing new start-ups.
- Data collection also helps student for their research purpose also.
Conclusion
As the importance of Data collection is increasing rapidly in business or research, there are very high demands for data analysts in almost every sector. In the year of 2019, there were almost 97K job positions available for data analysts. Top industries like e-commerce and telecom sectors are hiring data analysts and there has been a noticeable increase in job positions. So it is my suggestion to all aspiring data analysts, opt to study computer science engineering or computer science application in those universities who are providing big data analysis, machine learning in their syllabi. Adamas University is one of those, who is encouraging all data science aspirants by facilitating all the specializations in syllabus. Hope this initiative taken by our university may enhance efficiency of students who want to pursue data science as their career and may widen scope in job market.
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