A database is similar to a data file in that it is a storage place for data. Like a data file, a database does not present information directly to a user; the user runs an application that accesses data from the database and presents it to the user in an understandable format.Database systems are more powerful than data files in that data is more highly organized. In a well-designed database, there are no duplicate pieces of data that the user or application must update at the same time. Related pieces of data are grouped together in a single structure or record, and relationships can be defined between these structures and records.When working with data files, an application must be coded to work with the specific structure of each data file. In contrast, a database contains a catalog that applications use to determine how data is organized. Generic database applications can use the catalog to present users with data from different databases dynamically, without being tied to a specific data format. A database typically has two main parts: first, the files holding the physical database and second, the database management system (DBMS) software that applications use to access data. The DBMS is responsible for enforcing the database structure, including: Maintaining relationships between data in the database. Ensuring that data is stored correctly, and that the rules defining data relationships are not violated. · Recovering all data to a point of known consistency in case of system failures.

Although there are different ways to organize data in a database, relational databases are one of the most effective. Relational database systems are an application of mathematical set theory to the problem of effectively organizing data. In a relational database, data is collected into tables (called relations in relational theory). A table represents some class of objects that are important to an organization. For example, a company may have a database with a table for employees, another table for customers, and another for stores. Each table is built of columns and rows (called attributes and tuples in relational theory). Each column represents some attribute of the object represented by the table. For example, an Employee table would typically have columns for attributes such as first name, last name, employee ID, department, pay grade, and job title. Each row represents an instance of the object represented by the table. For example, one row in the Employee table represents the employee who has employee ID 12345. When organizing data into tables, you can usually find many different ways to define tables. Relational database theory defines a process called normalization, which ensures that the set of tables you define will organize your data effectively.

Enforcing data integrity ensures the quality of the data in the database. For example, if an employee is entered with an employee_id value of 123, the database should not allow another employee to have an ID with the same value. If you have an employee_rating column intended to have values ranging from 1 to 5, the database should not accept a value of 6. If the table has a dept_id column that stores the department number for the employee, the database should allow only values that are valid for the department numbers in the company. Two important steps in planning tables are to identify valid values for a column and to decide how to enforce the integrity of the data in the column. Data integrity falls into these categories:
1) Entity integrity
2) Domain integrity
3) Referential integrity
4) User-defined integrity

DBCC stands for database consistency checker. We use these commands to check the consistency of the databases, i.e., maintenance, validation task and status checks.DBCC CHECKDB - Ensures that tables in the db and the indexes are correctly linked.and DBCC CHECKALLOC To check that all pages in a db are correctly allocated. DBCC SQLPERF - It gives report on current usage of transaction log in percentage. DBCC CHECKFILEGROUP - Checks all tables file group for any damage.

Having Clause is basically used only with the GROUP BY function in a query. WHERE Clause is applied to each row before they are part of the GROUP BY function in a query.

SQL Profiler utility allows us to basically track Connections to the SQL Server and also determine activities such as which SQL Scripts are running, failed jobs etc.

SQL SERVER - is for running the databases SQL AGENT - is for automation such as Jobs, DB Maintenance, Backups DTC - Is for linking and connecting to other SQL Servers.