What is the difference between Type and Like?

TYPE, you assign datatype directly to the data object while declaring.
LIKE,you assign the datatype of another object to the declaring data object. The datatype is referenced indirectly.

Type is a keyword used to refer to a data type whereas Like is a keyword used to copy the existing properties of already existing data object.

Define Meta data, Master data and Transaction data ?

Meta Data: Data that describes the structure of data or MetaObjects is called Metadata. In other words data about data is known as Meta Data. Master Data: Master data is data that remains unchanged over a long period of time. It contains information that is always needed in the same way. Characteristics can bear master data in BW. With master data you are dealing with attributes, texts or hierarchies. Transaction data: Data relating to the day-to-day transactions is the Transaction data.

What are internal tables check table, value table, and transparent table?

Internal table: It is a standard data type object, which exists only during the runtime of the program. Check table: Check table will be at field level checking. Value table: Value table will be at domain level checking ex: scarr table is check table for carrid. Transparent table: – Exists with the same structure both in dictionary as well as in database exactly with the same data and fields.

What is the step by step process to create a table in data dictionary? 

 1: creating domains(data type, field length, range).

 2: creating data elements(properties and type for a table field).

3: creating tables(SE11).

What does an extract statement do in the ABAP program?

Once you have declared the possible record types as field groups and defined their structure, you can fill the extract dataset using the following statements: EXTRACT. When the first EXTRACT statement occurs in a program, the system creates the extract dataset and adds the first extract record to it. In each subsequent EXTRACT statement, the new extract record is added to the dataset EXTRACT HEADER. When you extract the data, the record is filled with the current values of the corresponding fields. As soon as the system has processed the first EXTRACT statement for a field group , the structure of the corresponding extract record in the extract dataset is fixed. You can no longer insert new fields into the field groups and HEADER. If you try to modify one of the field groups afterwards and use it in another EXTRACT statement, a runtime error occurs. By processing EXTRACT statements several times using different field groups, you fill the extract dataset with records of different length and structure. Since you can modify field groups dynamically up to their first usage in an EXTRACT statement, extract datasets provide the advantage that you need not determine the structure at the beginning of the program.