Page 41 - DCAP302_ENTERPRISE_RESOURCE_PLANNING
P. 41

Unit 2: ERP and Related Technology




          relational Databases                                                                  notes

          A  database  system  or  a  Database  Management  System  (DBMS)  consists  of  a  collection  of
          interrelated data, known as a database, and a set of software programs to manage and access the
          data. The software programs involve the following functions:
          Mechanisms to create the definition of database structures:

          1.   Data storage
          2.   Concurrency control
          3.   Sharing of data
          4.   Distribution of data access
          5.   Ensuring data consistency

          6.   Security  of  the  information  stored,  despite  system  crashes  or  attempts  at  unauthorised
               access.
          A relational database is a collection of tables, each of which is assigned a unique name. Each
          table consists of a set of attributes (columns or fields) and usually stores a large set of tuples
          (records or rows). Each tuple in a relational table represents an object identified by a unique key
          and described by a set of attribute values. A semantic data model, such as an entity-relationship
          (ER) data model, is often constructed for relational databases. An ER data model represents the
          database as a set of entities and their relationships.
          Some important points regarding the RDBMS are as follows:
          1.   In RDBMS, tables can also be used to represent the relationships between or among multiple
               relation tables.
          2.   Relational data can be accessed by database queries written in a relational query language,
               such as SQL, or with the assistance of graphical user interfaces.
          3.   A given query is transformed into a set of relational operations, such as join, selection, and
               projection, and is then optimised for efficient processing.
          4.   Trends and data patterns can be searched by applying data mining techniques on relational
               databases, we can go further by searching for trends or data patterns.


                 Example: Data mining systems can analyse customer data for a company to predict the
          credit risk of new customers based on their income, age, and previous credit information. Data
          mining systems may also detect deviations, such as items whose sales are far from those expected
          in comparison with the previous year.
          Relational databases are one of the most commonly available and rich information repositories,
          and thus they are a major data form in our study of data mining.

          Data Warehouses

          A data warehouse is a repository of information collected from multiple sources, stored under a
          unified schema, and that usually resides at a single site. Data warehouses are constructed via a
          process of data cleaning, data integration, data transformation, data loading, and periodic data
          refreshing. Figure 2.6 shows the typical framework for construction and use of a data warehouse
          for a manufacturing company.
          To facilitate decision making, the data in a data warehouse are organised around major subjects,
          such as customer, item, supplier, and activity. The data are stored to provide information from
          a  historical  perspective  (such  as  from  the  past  510  years)  and  are  typically  summarised.  For



                                           LoveLy professionaL university                                    35
   36   37   38   39   40   41   42   43   44   45   46