Certificate in Data Collection

Data Collection

About Data Collection

Data collection is the process of gathering quantitative and qualitative information on specific variables with the aim of evaluating outcomes or gleaning actionable insights. Good data collection requires a clear process to ensure the data you collect is clean, consistent, and reliable.

Establishing that process, however, can be tricky. It involves taking stock of your objectives, identifying your data requirements, deciding on a method of data collection, and finally organizing a data collection plan that synthesizes the most important aspects of your program.

Data collection involves steps such as

•    Define your project objectives
•    Identify your data requirements
•    Determine your method of data collection
•    Organize your data collection plan

Why is Data Collection important?

Data collection enables a person or organization to answer relevant questions, evaluate outcomes and make predictions about future probabilities and trends. Accurate data collection is essential to maintaining the integrity of research, making informed business decisions, and ensuring quality assurance.

•    Data empowers you to make informed decisions
•    Data helps you identify problems
•    Data allows you to develop accurate theories
•    Data will back up your arguments
•    Data tells you what you’re doing well
•    Find Solutions To Problems
•    Keep Track Of It All

Who should take the Data Collection Exam?

•    Professionals engaged in research or quality management
•    Innovators
•    Anyone who wants to assess their data collection skills
•    Research managers and senior executives
•    Professionals working in outsourced companies responsible for market research, consumer research, or any research-related activity
•    Anyone interested in data collection
•    Individuals who encounter data collection within their day-to-day job
•    Students

Data Collection Certification Course Outline

1. The Research Process
2. Scientific Method and Research Design
3. Research and Data Objectives
4. Research Communication
5. Primary Data Collection
6. Secondary Data Collection
7. Sampling and Hypothesis
8. Data Processing and Analysis