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Three types of data sources

1. Social media The proliferation of social media has had a profound impact on the way we communicate and interact with each other. It has also had a significant effect on the way businesses collect and use data. Social media platforms like Facebook, Twitter, and Instagram Are all data sources? This data can be used help to understand people's opinions, behaviors, and interests. This data can be precious to businesses, as it can target marketing campaigns, understand customer sentiment, and predict future trends. However, it is essential to note that social media data is often unstructured and challenging to analyze. Businesses must be careful about using this data, which can be easily misinterpreted. Social media data is a valuable tool be used to gain insights into customer behavior and trends. However, businesses need to be aware of the limitations of this data and use it wisely. Social media: https://www.facebook.com/

2. Government data The United Nations defines data as "facts and statistics collected together for reference or analysis." Governments collect data for various reasons, including understanding trends, making policy decisions, and improving services. There are many different types of data that governments collect. Population data is used to understand the size and growth of a country's population. Economy data is used to understand a country's economic activity and performance. Health data is used to understand a population's health and plan and deliver health services. Education data is used to understand the educational attainment of a population and to plan and deliver education services. Data is a valuable resource for governments. It allows them to understand their population's needs and make informed decisions about how to serve their citizens best. Government datum: https://www.data.gov/

3. Commercial data Companies collect customer data, sales, and operations for various reasons. This data can be used help to understand consumer behavior, optimize marketing, and improve efficiency. Data on customers can be used to segment them into groups for targeted marketing, understand what products or services they are interested in, and predict future behavior. Sales data can be used to track trends, understand what products are selling well, and adjust inventory accordingly. Operational data can be used identify inefficiencies and bottlenecks in the company's processes and make improvements. Collecting data on customers, sales, and operations can be extremely helpful for companies in understanding their business and making improvements. Commercial datum: https://www.oracle.com/analytics/index.html

Types of data in terms of (Quantitative vs qualitative, Structured vs unstructured data)

Social media:

1. Facebook: Quantitative data such as likes, shares, and comments; qualitative data such as posts and status updates.

2. Twitter: Quantitative data such as tweets, retweets, and favorites; qualitative data such as tweets' replies.

3. Instagram: Quantitative data such as likes, comments, and shares; qualitative data such as posts and captions.

4. Snapchat Quantitative data such as snaps, views, and screenshots; qualitative data such as snaps' filters.

5. LinkedIn Quantitative data such as connections' views; qualitative data such as profile information posts.

Government datum:

1. Census datum: Quantitative data such as population, age, gender, and race; qualitative data such as address and family size. 2. Crime data: Quantitative data, such as the number of crime types of crimes; qualitative data, such as location and time.

3. Weather datum: Quantitative data such as temperature and precipitation; qualitative data such as predictions.

Commercial data:

1. Sales data: Qualitative data, such as the number of sales types of products sold; qualitative data, such as location and time.

2. Customer data: Qualitative data such as the number and types of customers.

The data could be used for several things, such as: -To create targeted marketing campaigns.

-To create targeted advertising.

-To track and monitor user behavior.

-To Improve user experience. -To create custom algorithms.

-To target specific users with specific content.

-To Store and analyze user data.

References Chambers, O., Cohen, R., Grossman, M. R., & Chen, Q. (2022). undefined. Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization. https://doi.org/10.1145/3511047.3537678

Cusatis, R., & Garbarski, D. (2018). Which activities count? Using experimental data to understand conceptualizations of physical activity. SSM - Population, Health, pp. 6, 286-294. https://doi.org/10.1016/j.ssmph.2018.10.002

Undefined. (2002). Analyzing Qualitative Data, 103-124. https://doi.org/10.4324/9780203413081-10

Undefined. (2019). https://doi.org/10.4135/9781526492883 Undefined. (2019). ORMS News Group. https://doi.org/10.1287/orma.2019.01.18n 1