Data Collection Methods used in Business Analytics

Business Analytics Jaro

When it comes to Data Science and Analytics, the most important thing is collecting data for analysis. Data collection is the second step in the data life cycle after data generation. Without data, the company has nothing to evaluate. According to a survey by IDC, the world’s data usage would grow to 175 zettabytes by 2025. This shows the crucial role played by data in Data Science for Business.

For professionals looking to excel in their professional career or a student looking to start his career in Data Science, pursuing professional Data Science degrees from reputed universities like IIM Nagpur  will help them excel in their professional career.

Ways to collect data for Data Science and Analytics

Table of Contents

Data Collection is a method of collecting information for a specific project. There are three types of consumer data.

  • First-party data – The data is collected directed from the person.
  • Second-party data – The data is collected from another source that has conducted the collection through first-party data.
  • Third-party data – The data collected or purchased from companies that have no connection with the leading company or its customers.
 

Things to know before collecting data

  • The question you need to get answers
  • The subjects from whom you need to collect the answers
  • The timeline for the collection of data
  • The data collection process.
  • Data Collection process
 

Let us look at different data collection processes used in Data Science. 

Surveys

This is done through physical or digital questionnaires to gather qualitative and quantitative data. As the data can be collected in a physical or digital medium, the surveys can be sent to a large group. This is inexpensive and a very effective mode of data collection. 

Interviews and Focus groups 

This data collection process involves direct interaction with the target audience. This can be conducted in groups or one-to-one. This method helps you in understanding the mindset of the audience by knowing their opinions and feelings towards a particular subject. But this process is time-consuming and is expensive as compared to surveys. 

Transactional tracking

People have shifted to online transactions, and that makes it easier for several companies to track the buying behaviour of their customers. This data collection is done by e-commerce websites to help them showcase products to the customers as per their buying behaviour.

Online tracking

This is used to track the online behaviour of the target audience while visiting a particular website. This data collection technique can help the company understand the user’s online behaviour. The company can implement it through cookies and pixels. This can help the company improve their services to their customers. There is a thin line between legal tracking and breaching the personal space of the target audience. The company needs to be careful while installing the cookies and pixels. 

Social media tracking

Nowadays, with the rise of social media, it has become a ground for companies to conduct data collection areas. They get the desired target audience to participate in the process and get the desired data for analysis for the Data Science For Business. Many companies take the services of a third party to pull more data from the target audience.

The one-year Data Science for Business Excellence and Innovation programme from IIM Nagpur equips the professionals with languages related to Data Science. This Programme focus on industry exposure and provide working executives s with real-life business problems. The course is structured keeping in mind the current market trends to make them ’ industry-ready. they provide the participants with the skill to understand and analyse the data through Data Science and Analytics. Undergoing the professional courses from such universities would benefit the students in their professional careers.

Conclusion

Without data collection, Data Science and Analytics is not workable. The Data scientists need the data to analyse and provide a report to the company. There are many ways to collect the data like surveys, online tracking, interviews, and others. To learn more about Data Science, visit here and enroll for the course.

FAQs

  • Is data science in demand in 2022?

With the rising competition, every company is looking to benefit from Data Science. The demand will be on the rise in 2023.

  • Is data science difficult to get into?

Several institutions and colleges are offering Data Science degrees. So it is not difficult to get into any institute. But if you are not pursuing the course from a reputed college, there is less chance of not getting noticed by reputed companies.

  • What’s the difference between data science and data mining?

Data Science is working with large amounts of data and analysing them to provide a report. Data mining is the process of extracting vital information from a larger database.

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