Generally, materials that have been published within the past 10 years are considered to be credible sources for research. Another important factor to consider is the author — if they are well known and respected in their specific fields, that’s also generally a sign that the article is credible.

The most common credible sources are scholarly journals, conference papers and books because these have been peer-reviewed (read and approved for publication by other authors). However, there are good websites that can be used; generally ending in . gov / . edu / .

Popular magazines are not considered to be a very credible source type because there is no peer review, and there are very few citations. Trade or professional journals bridge the gap between scholarly and popular sources in that they are aimed at a quite specific audience, yet can be enjoyed by the layman.

Google is not an academic source, or indeed, a source at all. “Google” should never be cited as a source. Rather, Google is a search engine designed to help find materials that are available on the internet.

Answer: some are not – it’s up to you to evaluate, but the answer is Yes because there is no search result if reliable sources doesn’t exist. Explanation: A reliable source is one that provides a thorough, well-reasoned theory, argument, discussion, etc.

A data source is simply the source of the data. It can be a file, a particular database on a DBMS, or even a live data feed. The data might be located on the same computer as the program, or on another computer somewhere on a network.

7. What are the three types of diverse data sources?

• Information Networks, Map Data, and People.
• Machine Data, Map Data, and Social Media.
• Machine Data, Organizational Data, and People.
• Sensor Data, Organizational Data, and Social Media.

5. What are the challenges of data with high variety?

• Hard to perform emergent behavior analysis.
• The quality of data is low.
• Hard in utilizing group event detection.
• Hard to integrate.

Examples of machine data are the numerous system logs generated by the operating system and other infrastructure software in the normal course of the day, as well as Web page request and clickstream logs produced by Web servers. Network management logs and telecom call detail records are also machine-generated data.

Once the data is collected, it then enters the data preparation stage. Data preparation, often referred to as “pre-processing” is the stage at which raw data is cleaned up and organized for the following stage of data processing. During preparation, raw data is diligently checked for any errors.