What is the difference data-mining and data warehouses

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Reference no: EM131184824

Assignment

QUESTION 1

A Database needs to be secured in order to ensure integrity and consistency of the data that is stored in it. Database administrator plays an important role by making sure that access to the database is granted to the rightful users. Granting access to the rightful users can help avoid unauthorised access. Security of database involves protecting the database against the unauthorised disclosures, alterations and destructions.

Discuss the computer and non-computer based methods that can be used to implement Database Security by the Database administrator.

QUESTION 2

Database Management Systems (DBMS) handles the requests generated from SQL interface, producing or modifying data in response to these requests. Requests are processed according to the levels. Describe and analyse the different processing levels that are found in the level structure that processes the SQL. Use a process diagram to enhance your answer.

QUESTION 3

Generally, data mining (sometimes called data or knowledge discovery) is the process of analysing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases.

What is the difference Data-mining and Data Warehouses?

How does data mining works?

What technological infrastructure is required?

QUESTION 4

You are to construct a star schema for Simplified Automobile Insurance Company. The relevant dimensions, dimension attributes, and dimension sizes are as follow:

• Insured Party. Attributes: Insured_Party_ID, Name. There is an average of two insured parties for each policy and covered item.
• Coverage Item. Attributes: Coverage_Key, Description. There is an average of ten covered items per policy.
• Agent. Attributes: Agent_ID, Agent_Name. There is one agent for each policy and covered item.
• Policy. Attributes: Policy_ID, Type. The company has approximately one million policies at the present time.
• Period. Attributes: Date_Key, Fiscal_Period.

Facts to be recorded for each combination of these dimensions are Policy_Premium, Deductible, and Number_of_Transactions.

Design a star schema for this problem with database modeling tool (Xcase).
Estimate the number of rows in the fact table, using the assumptions stated above.
Estimate the total size of the fact table (in bytes), assuming an average of 5 bytes per field.

Reference no: EM131184824

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