Data Modeling and the DW

SQL, DATA WAREHOUSE, AND DATA MARTS-Module 4 SLP: Data Modeling and the DW
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Part 1
Creating SQL queries
SQL queries are the statements that allow users to identify specific data from a database table, and this then forms the result table. The result-sets represented in the result tables depict the information that is selected by using queries. Databases store information in one central location, while also allowing for information sharing. Since it is possible to recollect specific information in a database, queries help to identify the information needed. Queries may contain conditions, whereby one chooses fields from the specified table as well as comparison values and the conditional operators. Office.Org Base also provides a report that contains the related tables, while also allowing one to view various data tables.
SQL> SELECT* FROM STUDENTS;
SQL> SELECT* FROM COURSE;
SQL> SELECT STUDENT ID, NAME, STATE FROM STUDENTS
SQL> SELECT, ITM 440 COURSE FORM COURSE
Part II






Data Modeling and the DW
Data modeling
Data Modeling relates to the graphical representation of data created for the purposes of analysis and design. Data models include data warehouses, as they follow the same design process while designing the architecture for data warehousing. Data modeling tools make it easier to visualize the data, and various software use graphical capabilities to represent the data. The ER diagram is one of the data modelers that helps to visualize situations and dimensional modeling have improved capability to visualize more abstract concepts. Hence, the data models are guidelines to the implementation of the data warehouse. They are consolidated before implementation to improve the effectiveness of data warehouses.
Data modeling extends to business intelligence, with analytic operations necessary to highlight the use of query to organize data. Since the data models also rely on rules to govern the data, data modeling tools are essential to organizing the database. The first part is the logical design while the other part is the physical design. The top-down approach relies on understanding business requirements while the bottom-up approach relies on creating data models from databases which have no data model (Wang, 2008). The concept of normalizing and de-normalizing data is also important during data modeling, as they are a blueprint to the database requirements. There are also constraints, columns, tables and relationships that give a clearer picture depicting the ‘map’ of the database.
Data warehousing
Data warehouses support the decision-making in an organization, integrating data into a large repository, while allowing for knowledge extraction. However, one does not have the right tools it is difficult to extract the information. Data extraction, transformation uploading the data and the integrating data into the data warehouses are the main phases (Ania & Cuevas, 2012). Data developers and architects recognize that data warehousing is a valuable enterprise asset that meets proper management. The data warehouse provides potential value as a repository of data, but there is a need to first assess the models ag...