Database Table Normalization - Exercise Result

Here are two possiblities:

1. An employee table that contains the employee ID number and last name
2. A task assignment table that contains the task ID number, the employee ID number, and the due date

Data analysis is the act of transforming data with the aim of extracting useful information and facilitating conclusions.
Depending on the type of data and the question, this might include

1. application of statistical methods,
2. curve fitting,
3. selecting or discarding certain subsets based on specific criteria, or
4. other techniques.

In contrast to Data mining, data analysis is usually more narrowly intended as not aiming to the discovery of unforeseen patterns hidden in the data, but to the verification or disproval of an existing model, or to the extraction of parameters necessary to adapt a theoretical model to (experimental) reality.
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The connection between database table normalization, extracting useful information, and eliminating inefficiencies is discussed below. Normalization doesn't directly extract information but creates a structure that makes information extraction more efficient and reliable. It eliminates inefficiencies by:

1. Reducing Redundancy: By organizing data into separate, related tables, normalization prevents duplication of information. This saves storage space and reduces the likelihood of inconsistencies when updating data.
2. Improving Data Integrity: Normalization enforces data integrity rules, ensuring that data is accurate, consistent, and reliable. This is crucial for making informed decisions based on the data.
3. Enhancing Data Updates: Normalized tables make updates easier and more efficient. Changes to a piece of information need to be made in only one place, rather than multiple tables.
4. Minimizing Insertion, Deletion, and Update Anomalies: These anomalies occur when data isn't properly structured. Normalization ensures that adding, removing, or modifying data doesn't lead to inconsistencies or unintended side effects.
5. Simplifying Data Retrieval: Normalized tables have clear relationships, making it easier to retrieve specific information through well-defined queries. This improves the efficiency of data analysis and reporting.
6. Reducing Data Anomalies: By removing redundant data, normalization decreases the chance of errors and inconsistencies. This leads to a more reliable and trustworthy database.
7. Enhancing Data Security: Normalization can improve data security by controlling access to sensitive information and reducing the attack surface for potential breaches.

In essence, normalization doesn't directly extract information but creates a well-organized structure that facilitates efficient and reliable information extraction while reducing inefficiencies and ensuring data integrity.