Data Engineering - Data Collection

Data collection involves gathering and analyzing information from various sources to solve research problems, answer questions, and predict trends. This process is challenging for research, analysis, and decision making in social science, business, and healthcare. Data collection involves identifying data types, their sources, and the methods used to gather information. Many external systems such as Facebook, Google, Shopify, Hubspot, generate crucial customer data that the businesses depends on, in addition to the extensive data produced by internal applications.

Data collection specifies high-quality data, which is determined for accurate decision making and analysis. For data engineers, collecting data is the primary step, followed by setting up the data.

Data collection is a process that evolves with technology, providing more data in various forms than before. It supports decision-making through methods such as telephone surveys, in-person interviews, and mail-in comments. Data collection involves gathering accurate data for research, decision-making, and analysis across various sectors.

Primary Data Collection

Primary data collection involves gathering original data directly from the source or through direct interaction with respondents. This method provides information specific to research objectives.

• Structured surveys are designed to collect data from groups or individuals. These can be conducted through telephone calls, mails, face-to-face interviews, or online platforms.

• Interviews involve direct interaction between the researcher and the respondent. They can be conducted via video conferencing, in person, or over the phone.

• Observations involve recording and watching behaviors, actions, or events in their natural environment. This method is very effective for collecting data on human interactions and behavior.

Secondary Data Collection

Secondary data collection involves using data from the established sources. These sources include online databases, government and public data, and research studies.

• Online databases provide access to various types of secondary data, including economic data, social surveys, social surveys, and research articles.

• Available public data includes information shared by individuals, organizations, or communities on public platforms, social media and websites. This data can be processed and used for research purposes.

• Published data includes academic journals, books, government reports, newspapers, and other materials that provide relevant data for research.

Techniques for Data Extraction

The following can predict future outcomes and are categorized into different interview types −

• Sentence Completion: Users use the sentence completion to gain more information into respondents ideas. This method involves involves providing an incomplete sentences and observing how the respondent completes it.

• Mobile Surveys: Mobile collection surveys utilize mobile technology. They use devices like smartphones to conduct surveys via SMS or mobile apps.

• Observation: The simplest method is often the most effective. Researchers use direct observations to quickly access data with minimal intrusion or third-party specifications. This method is best suited for small-scale situations.

Importance of Data Collection

Accurate data collection is most determined research integrity, whether the study's subject involves quantitative data or not. Using appropriate and updated data gathering tools helps minimize errors.

The following are ineffective data collections −

• Decisions that compromise public policy.

• Incomplete conclusions waste the resources.

• Causing harm to humans or animal participants.

• Misleading other researchers into unproductive research path.

• The study's failure can be validated and replicated.