Data, Information and Knowledge

Data

• Data is comprised of raw, unconfirmed facts that have not been processed to reveal their meaning.
• Data has multiple potential interpretations and cannot be used for decision-making in its raw form.
• It's the foundation for information, which is the bedrock of knowledge.

Information

• Information results from processing raw data to reveal its meaning.
• The bedrock for decision-making.
• Information is utilized to uncover data's significance.
• Accurate, relevant, and timely information is key to good decision making.

Data Transformation to Information

• Data processing can range from simple organization to complex statistical modeling used for extracting forecasts or drawing inferences.
• Revealing meaning from data needs context.

Knowledge

• Knowledge implies familiarity, awareness, and understanding of data as it applies to an environment.
• Raw Data -> Information -> Knowledge.

Data vs. Information

• Data constitutes the individual parts of an ID, like course, year, student number, name, email, age, address, contact number, and picture.
• Information constitutes the entire ID.
• An ID is a representation of one information of one student
• Data is only a part of information.
• Information relies on data.

Usages of Data

• Scenario 1 describes a teacher wanting to know how many students are from Alabang.
• If the student address is on the ID, the teacher checks each ID and can verify the address.
• This process of checking the addresses represents extraction or processing.
• Scenario 2 explains the teacher wanting to know how many males and females are in your class.
• Names are not reliable to determine if a student is male or female.

Database

• A database is a shared, integrated computer structure that stores a collection of data and metadata.
• It's a container for data.
• End-user data are raw facts of interest to the end user.
• Metadata describes the data characteristics and relationships within the database.
• Database design activities focus on designing the database structure to store and manage end-user data.
• A database that meets user requirements requires careful design.

Database Design

• Just like a database design, you need to foresee the future, as the records in the database will continuesly increase.
• It is not good practice to keep restructuring your database every now and then.
• Important to note that it is rare that you need to delete records.

Core Entities

• Data is raw facts, such as telephone number, a birth date, a customer name, and a year-to-date (ytd) sales value.
• Field is a character or group of characters (alphabetic or numeric) that has a specific meaning and used to define and store data such as C_NAME, C_PHONE, C_ADDRESS.
• Record is a logically connected set of one or more fields that describes a person, place, or thing.

Business Rules

• A business rule provides a brief, precise, and unambiguous description of policy, procedure, or principle within an organization.
• They apply to any organization.
• Business rules are used to define entities, attributes, relationships, and constraints.
• These rules are sourced mainly from company managers, policy makers, department managers, and written documentation
• Direct interviews with end users also serve as a faster and more direct source.
• Noun translates into an entity in the model, verb translates into the relationships among the entities.
• Relationships are bidirectional and go both ways.
• Customer is the "1" side, and invoice is the "many" sides.
• Ask how many instances of B relate to one instance of A, and vice versa.