Writers can produce a wide variety of content for the Web, from articles and reviews to game scripts.
Data aggregation is any process in which information is gathered and expressed in a summary form, for purposes such as statistical analysis. A common aggregation purpose is to get more information about particular groups based on specific variables such as age, profession, or income. The information about such groups can then be used for Web site personalization to choose content and advertising likely to appeal to an individual belonging to one or more groups for which data has been collected. For example, a site that sells music CDs might advertise certain CDs based on the age of the user and the data aggregate for their age group. Online analytic processing (OLAP) is a simple type of data aggregation in which the marketer uses an online reporting mechanism to process the information.
Data aggregation is the process of transforming scattered data from numerous sources into a single new one. The objective of data aggregation can be to combine sources together as such that the output is smaller than the input. This helps processing massive amounts of data in batch jobs and in real time applications.
Data collection is the process of gathering and measuring information on variables of interest, in an established systematic fashion that enables one to answer stated research questions, test hypotheses, and evaluate outcomes. The data collection component of research is common to all fields of study including physical and social sciences, humanities, business, etc. While methods vary by discipline, the emphasis on ensuring accurate and honest collection remains the same.
Data extraction is where data is analyzed and crawled through to retrieve relevant information from data sources (like a database) in a specific pattern. Further data processing is done, which involves adding metadata and other data integration; another process in the data workflow.
The majority of data extraction comes from unstructured data sources and different data formats. This unstructured data can be in any form, such as tables, indexes, and analytics.