Data collection is the process of gathering data for use in business decision-making, strategic planning, research and other purposes. It's a crucial part of data analytics applications and research projects: Effective data collection provides the information that's needed to answer questions, analyze business performance or other outcomes, and predict future trends, actions and scenarios.
In businesses, data collection happens on multiple levels. IT systems regularly collect data on customers, employees, sales and other aspects of business operations when transactions are processed and data is entered. Companies also conduct surveys and track social media to get feedback from customers. Data scientists, other analysts and business users then collect relevant data to analyze from internal systems, plus external data sources if needed. The latter task is the first step in data preparation, which involves gathering data and preparing it for use in business intelligence (BI) and analytics applications.
For research in science, medicine, higher education and other fields, data collection is often a more specialized process, in which researchers create and implement measures to collect specific sets of data. In both the business and research contexts, though, the collected data must be accurate to ensure that analytics findings and research results are valid.
Data can be collected from one or more sources as needed to provide the information that's being sought. For example, to analyze sales and the effectiveness of its marketing campaigns, a retailer might collect customer data from transaction records, website visits, mobile applications, its loyalty program and an online survey.
The methods used to collect data vary based on the type of application. Some involve the use of technology, while others are manual procedures. The following are some common data collection methods:
Some of the challenges often faced when collecting data include the following:
Well-designed data collection processes include the following steps:
There are two primary types of data that can be collected: quantitative data and qualitative data. The former is numerical -- for example, prices, amounts, statistics and percentages. Qualitative data is descriptive in nature -- e.g., color, smell, appearance and opinion.
Organizations also make use of secondary data from external sources to help drive business decisions. For example, manufacturers and retailers might use U.S. census data to aid in planning their marketing strategies and campaigns. Companies might also use government health statistics and outside healthcare studies to analyze and optimize their medical insurance plans.
The European Union's General Data Protection Regulation (GDPR) and other privacy laws enacted in recent years make data privacy and security bigger considerations when collecting data, particularly if it contains personal information about customers. An organization's data governance program should include policies to ensure that data collection practices comply with laws such as GDPR.
Other data collection best practices include the following:
02 Feb 2022