Difference between Relational model and Dimensional Model

Relation Model

1) In relational modelling the focus is on identification of fundamental or strong entities involved in the execution of business transactions.

2) Relational model is widely used in relational databases in transactional systems.

3) The structure of the relational model shows the relationships of entities that are important in the execution of the transactions of the business process.


Dimensional Model

1) In dimensional modelling the focus is on identification of associative entities that carry business measures.

2) Dimensional model is prevalently used in data warehouses or decision support systems.

3) Dimension attributes describe the item in the dimension and are virtually constant over time.

4) The dimensional model is therefore an informational model because the data of the effects of the business process is modeled.

5) The structure of the dimensional model shows the relationships of entities (dimensions) that are important in modelling of business measures in the business process.

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Base SAS Vs SAS Data Integration Studio

BASE SAS	SAS DATA INTEGRATION STUDIO
Source data Adaptors, SAS can access just about any known data source through their native access engines and open standards approaches.	The same functionality is surfaced in SAS Data Integration Studio through metadata.
Base SAS has conditional logic support (if-then-else), so you can’t act on whatever observations or columns you wish.	Data Integration Studio Has a built in extract transformation
We have a tremendous amount of functionality at our disposal for doing the matching and retention of good values.	We have standard transformations as well as ability to create customer transformations that can be drooped onto the process editor.
We define surrogate key and simply increment the values each time a new record is added.	There is a surrogate key generator that will handle the creation of a new key for you when you load the table.

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SAS Data Integration Studio

About SAS Data Integration Studio

SAS Data Integration Studio is a tool that enables you to consolidate and manage enterprise data from a variety of source systems, applications, and technologies. This software enables you to create process flows that accomplish the following tasks:

• extract, transform, and load data for use in data warehouses and data marts
• cleanse, migrate, synchronize, replicate, and promote data for applications and business services.

SAS Data Integration Studio was formerly named SAS ETL Studio.

SAS Data Integration Environment

SAS Data Integration Environment

Administrators use SAS Management Console to connect to a SAS Metadata Server. They enter metadata about servers, libraries, and other resources on your network and save this metadata to a repository.

Users connect to the same metadata server and register any additional libraries and tables that they need.Then, they create process flows that read source tables and create target tables in physical storage.

Practical approach to extract, transform and loading

Importing externals delimited files

I am having a data set with 5 tables and each table accomplished with different table names and different sizes. It is a external data set saved in .excel and .csv format. Here i am showing how to import externals delimited files and upon registering them into SAS Dataset.

Select delimited external file from external folder of source designer and click on next.Browse the external file from the server location into sas. specify the delimiters and other parameters for reading the external file.

Define the columns contained in the external file by importing it and skip the 1st row if your column names are written. specify the folder location of the data set in repository to finish it.

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