DATABASE SECURITY

DATABASE SECURITY

This is a process of securing / Protecting a database from external threats which include: –
➢ Unauthorized access
➢ Unauthorized modification
➢ Unauthorized disclosures
➢ Destruction of data
➢ Loss of data though theft
➢ Loss of data through viruses
➢ Accidental loss of data
Controls that can be implemented to secure a database
1. Authorization rules: these are controls incorporated into the DBMS that restrict the access to the data and the action that people may take when they access the database. The users are granted permission or privilege to perform a specific task when they access the database.
2. Authentication mechanisms: It is a process of verifying the validity of a subject identify and approving that it is the real subject before allowing them to get access into the system. This can be done in the following ways:

i. Logical access – this is where the organization uses passwords and usernames which the computer uses to identify the legitimate user.
ii. Use of employee’s badges and cards – These are either shown or inserted into a slot. This identify the owner of batch or card as the legitimate owner.
iii. Biometric control – this is where the system enables computers to identify by the user’s fingerprints, voice pattern etc.

3. Data encryption – this involves changing of data into an un-meaningful form before transmission so that the is not interpreted by unauthorized users.
4. Checkpoint and recovery procedures – the programmer intervenes at regular intervals during the running of the program and dumps the entire memory on a backing file.
5. Log files – these are special files containing information of all database operations that has taken place as a reference point.
6. Integrity checks – this involves checking the database to ensure that it is accurate, consistent and up to date.
7. Administrative controls – these are controls put in place by the database administrator e.g. revoking the access of an employee who has left an organization.

DATA WAREHOUSE

This refers to a central source of data that has been extracted from various databases and has been cleaned, transformed and catalogued so that it can be used by managers and other professionals.
A Data Warehousing: is process for collecting and managing data from varied sources to provide meaningful business insights. A Data warehouse is typically used to connect and analyze business data from heterogeneous sources. The data warehouse is the core of the BI system which is built for data analysis and reporting.
Three main types of Data Warehouses are:
I. Enterprise Data Warehouse: is a centralized warehouse. It provides decision support service across the enterprise. It offers a unified approach for organizing and representing data. It also provides the ability to classify data according to the subject and give access according to those divisions.
II. Operational Data Store: Also called ODS, are nothing but data store required when neither Data warehouse nor OLTP systems support organizations reporting needs. In ODS, Data warehouse is refreshed in real time. Hence, it is widely preferred for routine activities like storing records of the Employees.
III. Data Mart: Is a subset of the data warehouse. It specially designed for a particular line of business, such as sales, finance, sales or finance. In an independent data mart, data can collect directly from sources.

Advantages of Data Warehouse:
i. Data warehouse allows business users to quickly access critical data from some sources all in one place.
ii. Data warehouse provides consistent information on various cross-functional activities. It is also supporting ad-hoc reporting and query.
iii. Data Warehouse helps to integrate many sources of data to reduce stress on the production system.
iv. Data warehouse helps to reduce total turnaround time for analysis and reporting.
v. Restructuring and Integration make it easier for the user to use for reporting and analysis.
vi. Data warehouse allows users to access critical data from the number of sources in a single place. Therefore, it saves user’s time of retrieving data from multiple sources.
vii. Data warehouse stores a large amount of historical data. This helps users to analyze different time periods and trends to make future predictions.
Disadvantages of Data Warehouse:
i. Not an ideal option for unstructured data.
ii. Creation and Implementation of Data Warehouse is surely time confusing affair.
iii. Data Warehouse can be outdated relatively quickly
iv. Difficult to make changes in data types and ranges, data source schema, indexes, and queries.
v. The data warehouse may seem easy, but actually, it is too complex for the average users.
vi. Despite best efforts at project management, data warehousing project scope will always increase.
vii. Sometime warehouse users will develop different business rules.
viii. Organizations need to spend lots of their resources for training and Implementation purpose.

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