Data collection, or data collecting, is the process of discovering and developing data for the purposes of data analysis. This can involve research to collect existing data and initiatives to develop new data. The following are common examples of data collection.
Academic Papers
Academic Publications
Artifacts
Behavioral Data
Blogs
Books / Ebooks
Business Journals
Clinical Trials
Communications
Corporate Publications (e.g. Financial Reports)
Database Queries
Documents
ETL
Event Data
Experiments
Focus Groups
Geographical Data
Government Publications / Datasets
Industry Publications / Datasets
Institutional Publications / Datasets
Interviews
Logs
Machine Data
Measurements
Media
Metadata
Observations
Podcasts
Press Releases
Questionnaires
Records
Reference Data
Sensors
Social Media
Surveys
Time Series
Transactional Data
Transcripts
Unstructured Data
User Input
Vlogs
White Papers
Artifact is a broad term for any document or physical thing that captures information. For example, an old letter, photograph or relic.Behavioral data is the process of monitoring people. For example, an advertising platform that tracks a user as they use different mobile apps.ETL is short for "extra, transform and load." This is a class of software that is used to extract and combine data from different data sources, particularly databases. Data collection often involves combining different databases so that they can be queried as one.Event data are notifications that something has occurred. For example, a door in a retail location that reports every time someone walks through it.A focus group is the practice of interviewing people as a group.Machine data is information generated by machines, particularly machines that are perceived as non-computer devices. For example, performance data generated by a jet engine.Metadata is data that describes data. For example, a photograph that includes the geographical coordinates of where the camera was positioned when the photo was taken.Logs are files generated by software that often contain event data, behavioral data, transactional data and information about software performance and errors.Reference data is foundational information that seldom changes. For example, the periodic table of elements.Sensors are devices that record the physical world.Transactional data describes an agreement, interaction or exchange. For example, sales receipts from a shop.Transcripts are a textual recording of verbal communication.Unstructured data is any data that isn't specifically formatted for machines to automatically analyze. For example, an audio recording. Structured data refers to databases and files that are specifically structured to be processed efficiently.
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