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Sources of Data Acquisition
Data can be acquired from various sources, classified as either primary or secondary.
Primary Data Sources
The data generated from the experiment is an example of primary data. Some of the sources for primary data
include surveys, interviews, experiments, etc. Here is an Excel sheet showing the data collected for students of a class.
Secondary Data Sources
Secondary data sources are the external sources for collecting data, rather than generating it personally. Some sources
for secondary data collection are: Published Literature, Government Publications, Market research reports, etc.
• UCI is a collection of
• Countries like databases, domain
Australia, EU, India, theories, and data
New Zealand, and generators in
Singapore are openly collaboration with
sharing datasets on Dataset Search the University of
various portals
Massachusetts
• Kaggle is an online • This is a toolbox
community of data .gov by Google that can UCI
scientists where you search for data by
can access different datasets name Machine Learning Repository
types of data
Best Practices for Acquiring Data
Acquiring data effectively is crucial for ensuring its accuracy, reliability, and usability. Here are some best practices
for acquiring data:
1. Set Clear Goals: Understand why you need the data and what you want to achieve; specify the type, format,
and detail level required.
2. Identify Data Sources: Use primary data that you collect yourself (surveys, interviews) and secondary data
from others (reports, databases).
3. Evaluate Sources: Ensure data sources are trustworthy, relevant, accurate, and current; get necessary
permissions and respect privacy.
4. Collect and Prepare Data: Use surveys, interviews, sensors, and web scraping; clean data by fixing errors,
removing duplicates, and anonymising.
5. Validate, Document, and Store: Cross-check and sample for accuracy, keep detailed records and meta-
data, store data securely, and regularly update it while following laws and regulations.
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